How to distinguish EUV photons from out-of-band photons

Transcription

1 How to distinguish EUV photons from out-of-band photons Thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Physics Author: Student ID: Supervisors: 2 nd corrector: F.I. Hoeseni Dr. J. van Veldhoven Dr. D.J. Maas Dr. C.W. Hagen Prof. Dr. J.M. van Ruitenbeek Leiden, The Netherlands, October 30, 2016

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3 How to distinguish EUV photons from out-of-band photons Farshaad Hoeseni Huygens-Kamerlingh Onnes Laboratory, Leiden University P.O. Box 9500, 2300 RA Leiden, The Netherlands October 30,

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5 Abstract TNO is developing a carbon-contamination-insensitive EUV power sensor that uses the photo-electric effect to distinguish in- from out-of-band EUV photons. The central question of this MSc research project was to verify if the EUV power sensor signal can be purified by suppressing the out-of-bound secondary electron signal using an electrostatic barrier, and, if so, which potential difference suffices. To this end, we designed a Secondary Electron Energy Distribution (SEED) analyzer to characterize the e-beam-induced secondary electron emission of gold and carbon targets. It was shown that the SEED analyzer allows filtering of electrons on their kinetic energy and could perform SE yield measurements as well as SE energy distribution measurements. However, systematic errors occurred in the form of secondary electron emission of the grid inside the SEED analyzer, leakage current flow, a loss of emitted electrons through the SEED analyzer s opening and deflection of electrons due to lack of a field-free region. The SE yield measurement results were in good agreement with literature, after estimating the effect of the systematic errors. The SE energy distribution of both target materials were obtained and show similarities to experimental data reported in literature. However, the absence of a field-free region during the measurements causes a small mismatch between our acquired SE energy distribution and the reference data. 5

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7 Table of Contents Chapter 1. Introduction EUV lithography Einstein s photo-electric effect Scope of this project Chapter 2. Theory of secondary electron emission Secondary electron emission Secondary electron yield Backscattered electron yield Secondary electron energy distribution Surface properties Chapter 3. SEED analyzer design Design objectives Design choice Final design Chapter 4. Investigated materials Samples Gold Glassy carbon Sample analysis Optical microscopy Surface profile measurements SEM and EDX analysis Reference data Chapter 5. Experimental setup Requirements for the experimental setup Electron gun setup Scanning electron microscope Data acquisition and processing Chapter 6. Secondary electron yield measurements Measurement protocol & data processing Gold Glassy carbon Systematic measurement errors Loss of backscattered electrons Secondary electron emission at the grid Current leakage Intermediate conclusion Chapter 7. Secondary electron energy distribution measurements Measurement protocol & data processing Gold Glassy carbon Systematic measurement errors No field-free region Current leakage Chapter 8. Conclusion & outlook Conclusion

8 8.2 Outlook Follow-up experiments New measurement protocol for SE energy distribution measurements Improvement of the SEED analyzer s design Appendix A. Gold sample fabrication Appendix B. Electron gun characterization Appendix C. Grid Appendix D. Secondary electron yield of stainless steel References Acknowledgement

9 Chapter 1. Introduction 1.1 EUV lithography Extreme ultraviolet (EUV) lithography is a next generation optical lithography technique that makes use of 13.5 nm wavelength electromagnetic radiation. In the near future this technique will be used for the mass production of integrated circuits. ASML has defined the 13.5 nm wavelength (91.8 ev) radiation as in-band EUV photons, while photons with shorter or longer wavelengths are called out-of-band (OoB) photons, as indicated in figure 1.1. An important parameter in the lithography process is the exposure dose: the amount of light incident on resist-coated wafers. For the lithography process in EUV lithography machines, only the in-band EUV radiation is of interest. However, the EUV radiation source in these systems also emits OoB photons. In order to accurately control the exposure dose of EUV photons and detect changes in the optical transmission of the system and/or in the EUV source during the lithography process, it is desired to have an EUV sensor that is sensitive to in-band EUV photons only. The OoB photons with a wavelength shorter than 13.5 nm are absorbed before they reach the wafer (and/or sensor). The OoB photons with a wavelength longer than 13.5 nm (DUV photons), however, are transmitted through the system and can reach the EUV sensor. Therefore, the EUV sensor s ability to distinguish EUV photons from OoB (DUV) photons is one of its most important features, in addition to robustness to EUV radiation, high spatial uniform responsivity and low noise [1]. Figure 1.1: In-band EUV, defined as 13.5 nm wavelength radiation, and OoB radiation in the electromagnetic spectrum [2]. 1.2 Einstein s photo-electric effect The sensor s sensitivity to in-band EUV photons can be optimized by distinguishing them from OoB photons. A way to do this is to use the photo-electric effect to filter and suppress the photoelectron signal generated by OoB photons [3]. The photo-electric effect, discovered by Albert Einstein and for which he famously received the Nobel Prize in physics in 1921, occurs when photons interact with a material. Energy transfers from a photon to an electron within a material when a photon is absorbed, causing an increase in the energy of the electron. As a result, it may be possible for the electron to be emitted from the material, depending on its energy. If, after photon absorption, the electron has acquired more energy than the work function of the material, the electron is emitted. If, after photon absorption, the electron has an energy lower than the work function, the electron is unable to escape the material. The process of electron emission will be explained in more detail in the next chapter. For now, it is important to note that the energy of an emitted electron (partially) depends on the energy of the incident photon and the local electron density of states of the target material. Since EUV photons have a higher energy (92 ev) than DUV (OoB) photons (200 nm wavelength, 6 ev energy), it is assumed that EUV photons generate higher energy photoelectrons than DUV photons. It has been reported in literature that for 92 ev incident photons, the photon-energy dependence of secondary electron yield measurements for ruthenium shows a photoemission signal around 2 ev and also around 80 ev [4]. This hints at the fact that it should be possible to make a distinction between EUV photon-induced electrons and OoB-photon induced electrons by applying a potential difference. 9

10 If it is possible to distinguish electrons on their energy, that can be used as a method to distinguish EUV photoninduced signal from OoB photon-induced signal. If this working principle proves to be feasible, it can be implemented in an EUV sensor application, such as the carbon-contamination-tolerant EUV power sensor that TNO is currently developing [5]. Experimental results obtained with TNO s EUV power sensor show a clear response to EUV photons. However, without a spectral purity filter, the EUV power sensor was also sensitive to DUV radiation emitted by the EUV source. The next step in the development of TNO s EUV power sensor would therefore be adjusting the sensor in order to distinguish its electrical output signal induced by EUV photons from the signal induced by OoB photons. 1.3 Scope of this project The aim of this project is to investigate if an electrostatic potential barrier can suppress the electron signal generated by OoB photons and, if so, which potential difference suffices. To this end, we need to obtain the secondary electron energy distribution from in-band EUV photons and OoB photons for different materials of interest. We designed an instrument, the Secondary Electron Energy Distribution (SEED) analyzer, for characterization of secondary electron emission of gold and glassy carbon targets. Gold is used as a literature benchmark, while glassy carbon is the material of interest, as it is used as target material in TNO s EUV power sensor. Ideally, the characterization would be done with EUV photons as primary beam, but unfortunately, TNO s EUV Beam Line was not available for experiments during this project. To benchmark the SEED analyzer s design against literature, ev electrons were used as primary beam to perform SE yield and SE energy distribution measurements from gold and glassy carbon targets. The structure of this thesis is as follows: in chapter 2 we will review the theory behind electron-induced SE emission, in chapter 3 we will discuss the design, construction and working principle of the SEED analyzer, chapter 4 gives an overview of the investigated materials and their properties, chapter 5 describes the experimental setup for the SE yield and SE energy distribution measurements, in chapter 6 the SE yield measurement results are discussed, in chapter 7 the SE energy distribution measurement results are discussed and, finally, chapter 8 gives an overview of the conclusions based on the results and an proposal for follow-up experiments. 10

11 Chapter 2. Theory of secondary electron emission 2.1 Secondary electron emission Secondary electron (SE) emission is defined as the emission of low-energy electrons (i.e. having energies below 50 ev) from a solid surface under bombardment with high-energy primary electrons, ions, or photons. In the 1950 s and 1960 s early theoretical models of SE emission were developed, predicting the SE yield as a function of primary electron (PE) energy and the energy distribution of the SEs [6, 7]. By now, this phenomenon has been widely investigated through experimental observations and numerical simulations for many different materials. The process of SE emission can be described in terms of three mechanisms: 1. The generation of internal SEs in a target material by kinetic impact of PEs; 2. The transport of the internal SEs through the target material towards the surface; 3. The escape of SEs out of the material into free space. In the process, momentum transfer between electrons and lattice plays an important role. The PEs entering the target material are assumed to travel in a straight electron trajectory and lose energy according to the power law [8]: de dx = A E ( (1) where E is the energy of a PE at a depth x and A is an arbitrary constant. SEs are produced when PEs excite valence electrons into the conduction band. The SEs lose energy through phonon scattering and become thermalized as they diffuse towards the surface of the target material. The number of SEs, N(x), generated in the layer dx is assumed to be equal to the ratio between the energy loss in the layer de and the average excitation energy B: N x dx = de B (2) Combining equation 1 and 2, leads to: N x = A 2, (-, 1 B(R x) ( (-, (3) and: R = E 2 (-, n + 1 A (4) where R is the maximum penetration depth and E 0 the energy of the primary electrons. Equation 3 shows that the number of generated SEs increases with the PE travel trajectory inside the material. Equation 4 shows that the penetration depth of the PEs increases with energy. High energy PEs have a high velocity and a relatively short time to interact with the lattice electrons. This results in a low internal SE yield per unit length. As the PEs travel further and lose more energy, the interaction time and thus the yield increases. So for increasing PE energy, the internal SEs are generated deeper beneath the surface of the target material. A high energy PE can induce many internal SEs. Most of these internal SEs lose their energy through collisions below the work function of the material and will not be emitted. The energy loss of the internal SEs in a conductor is determined by the interaction with conduction electrons, lattice vibrations and impurities. To escape the sample at the surface, an internal SE needs to have a kinetic energy of at least E F + φ, where E F is the Fermi energy and φ the work function of the material. The maximum escape depth for SEs is generally in the order of 5-10 nm [9]. 11

12 2.2 Secondary electron yield It is assumed that the SE yield, defined as the number of SEs escaping per incident PE, can be written as δ = 2 9 n(x, E 2 )f x dx = I ;< I =< (5) where n(x, E 2 ) represents the number of SEs produced per unit length at depth x below the surface per incident electron with initial energy E 0. f x represents the probability that a SE produced at depth x arrives at the surface and escapes. A typical SE yield curve as a function of PE landing energy is shown in figure 2.2. The parameters that are used to characterize a SE yield curve are shown in figure 2.1: E m is the PE energy where the SE yield takes its maximum value δ >. E I is the first crossover energy: this is the PE beam energy where the SE yield is equal to 1 and increases further with increasing E p. E II is the second crossover energy: this is the PE beam energy where the SE yield is equal to 1 and decreases further with increasing E p. The SE yield increases as a function of E p at primary energies below E m. This can be understood by the fact that as the energy of a primary electron increases, more SEs are generated, as mentioned in the previous section. However, SEs have a relatively small escape depth due to their low energy and for high enough PE energy, the penetration depth of PEs becomes larger than the escape depth of SEs. This is why the SE yield curve peaks at E m and decreases when the PE energy increases further. Figure 2.1: Typical SE yield curve as a function of primary electron energy for bulk samples [10]. The SE yield increases with the PE energy, before it reaches its peak, and then decreases for increasing PE energy. 12

13 2.3 Backscattered electron yield PEs do not only generate electrons with energies lower than 50 ev (SEs). By convention, electrons that escape from the sample with energies higher than 50 ev are defined as backscattered electrons (BSEs). BSEs are generated deeper inside the material and usually have a small escape angle with respect to the surface normal of the sample (see figure 2.2) [11]. Most BSEs escape the sample with energies close to the PE energy. The BSE yield is defined as the ratio between the number of BSEs per incident primary electron: The total electron (TE) yield is defined as the SE yield and BSE yield combined. η = I =< (6) Figure 2.2: The angular distribution of BSEs generated in gold (solid line) and aluminum (dashed line) for normal PE incidence angle and 60 PE incident angle [11]. The numbers in the middle of the curves represent the PE energy. It can be seen that at a normal incidence angle, most BSEs have a small escape angle with respect to the surface normal. 2.4 Secondary electron energy distribution A typical SE energy distribution curve is shown in figure 2.3. The curve shows the number of SEs as a function of their energy. It can be seen that most SEs are expected to have a low energy due to multiple scattering events in the target material. The energy of this peak does not depend on the primary electron energy, only the height of the peak does. At higher energies the inelastically scattered and elastically scattered BSEs are shown. As mentioned in section 2.1, the SE energy depends on the primary electron energy, the target work function and the electron escape path. The number of SEs with a certain energy depends on the local density of states of the target material. 13

14 Figure 2.3: Typical example of the energy distribution of SEs [12]. Most SEs have an energy below 10 ev, due to experiencing multiple scattering events in the target material. Inelastically and elastically BSEs have higher energies. To fit the low-energy part of a SE energy distribution, Scholtz et al. have proposed a Gaussian function with a logarithmic argument [10]: f E = C exp ln E E 2 G 2τ G (7) where C is the normalization constant, E 0 the position of the maximum and τ the standard deviation of the Gaussian curve. This function proved to be in good agreement with their experimental data of gold for a PE energy of 60 ev. We will use this equation to fit the SE energy distribution measurement results, obtained with the SEED analyzer. 2.5 Surface properties In addition to primary beam energy, PE dose and the target material s local electron density of states, different surface properties of the investigated sample, such as the sample surface roughness, vacuum chamber pressure during electron beam exposure and contamination on the sample surface, also affect the SE emission of the target material. For example, SEs generated in a material with a rough surface have more surface area to escape from than a material with a flat surface. It is thus expected that a sample with a rougher surface will demonstrate a higher SE yield. Surface contamination on a sample is caused by the cracking of hydrocarbons present both in the vacuum chamber and on the sample and their subsequent surface diffusion to the spot being exposed. The gradual build-up of carbon layers on the sample surface will cause SE generation and emission of carbon. Quantitative analysis of carbon surface contamination has shown that the total number of carbon atoms deposited per time for a given electron beam intensity is roughly constant at room temperature [13]. The higher the pressure in the vacuum chamber, the faster the sample surface gets contaminated. 14

15 Chapter 3. SEED analyzer design 3.1 Design objectives To characterize the SE emission of different target materials, we developed the Secondary Electron Energy Distribution (SEED) analyzer. This instrument was specifically designed to perform electron-induced SE yield and SE energy distribution measurements in reflection configuration. In order to carry out these measurements, the SEED analyzer had to meet the following requirements: 1. The ability to measure the PE beam current in order to calculate yields 2. The ability to filter electrons on their kinetic energy in reflection configuration a. to perform SE yield measurements b. to perform SE energy distribution measurements 3. No distortion due to tertiary electrons 4. Properly shielded against primary electrons not entering the SEED analyzer 5. High SE and BSE collection efficiency 6. Low angular dependence for collecting SEs and BSEs 7. Vacuum and EUV compatibility 8. Satisfy the vacuum chamber dimensions of different setups 3.2 Design choice The objectives 1, 2 and 3 can be met by starting with a basic design consisting of three electrodes: a sample holder, a grid and a collector that are stacked, centered and electrically isolated in reflection configuration (see figure 3.1). PEs can enter the SEED analyzer through a hole in the collector and travel to the sample in the sample holder. This design was based on electron detectors (retarding grid analyzers) reported in literature [9, 14]. The grid can serve as a potential barrier to filter electrons on their kinetic energy. By applying the appropriate bias voltage settings on sample, grid and collector, it is possible to distinguish SEs, BSEs and tertiary electrons to perform the SE yield and SE energy distribution measurements. The measurement protocols are described in more detail in section 6.1 and section 7.1. Figure 3.1: Schematic figure of the collector, grid and sample holder in reflection configuration. The collector has an opening where the PE beam enters. The sample is placed perpendicular with its surface to the opening. The grid can serve as a potential barrier. Objective 4: proper shielding for primary electrons not entering the SEED analyzer, was achieved by packing the sample holder, grid and collector in a conducting housing that can be connected to ground. The three electrodes are isolated from the housing. 15

16 Objectives 5 and 6 are determined by the geometry of the grid and the collector in the SEED analyzer. Two possible geometries are a hemispherical grid and collector or a flat grid and collector. To quantify the collection efficiency and angular dependence of the two geometries, we define two parameters: the electron collection percentage and the collection angle. The electron loss percentage is defined as the ratio between the number of electrons emitted by the sample that do not reach the collector and the total number of electron emitted by the sample. The collection angle is defined as the difference between the minimum and maximum escape angle for which the electrons escaped from the sample reach the collector. Performing simulations of the electric field and the electron trajectories for two different geometries allowed us to opt for the design with the highest collection efficiency and lowest angular dependence. It is important that a geometry contains a clear potential barrier, where the energy selection of electrons takes place and where they are either transmitted or reflected. It should be noted that in the simulations a few assumptions were made that are not corresponding to reality. The simulations assume that the sample has a perfectly flat surface and that the SEs and BSEs are distributed in a uniform hemisphere when escaping from the sample. It is also assumed that the grid is 100% open and that the PE beam enters the SEED analyzer perfectly coaxial. Even though the simulations do not consider these aspects, it is expected that in reality the working principle of the SEED analyzer will not differ significantly from the simulations. Figure 3.2 displays the electrostatic potential when the grid is at -50 V while the sample and collector are at 0 V for both geometries. Note that the grid creates two potential barriers for this voltage bias setting: one between the sample and grid, prohibiting SEs from the sample to reach the collector, and another one between the grid and the collector, that prevents tertiary electrons (SEs created at the collector) from traveling towards the grid/sample. Figure 3.2: COMSOL simulation of the electrostatic potential inside two different SEED analyzer geometries, when V sample = 0 V, V grid = -50 V and V collector = 0 V. Cleary, there is an electric field between the sample and grid and the grid and collector. The color bar indicates the potential in V on collector, grid and sample holder. Figure 3.3 displays a COMSOL simulation of the electron trajectories for SEs escaping from the sample with an energy of 40 ev when the grid bias is -50 V, while the sample and collector bias are 0 V (see figure 3.2). The potential barrier of -50V between the sample and the grid prevents the SEs from reaching the collector by reflecting them back to the sample. It is peculiar that a fraction of SEs does reach the collector. Figure 3.4 shows the trajectories for SEs with an energy of 50 ev in the exact same voltage bias setting. For both geometries, some of the SEs overcome the potential barrier, while some of them are being deflected back to the sample. To overcome the potential barrier, the electron trajectory has to be perpendicular to the grid. The hemispherical geometry clearly has a higher electron collection efficiency than the flat geometry. In figure 3.5, BSEs with an energy of 60 ev are simulated in the same voltage bias setting. The hemispherical geometry again shows a higher electron collection efficiency than the flat geometry. 16

17 Figure 3.3: Electron trajectories for SEs escaping with an energy of 40 ev for both geometries when V sample = 0 V, V grid = -50 V and V collector = 0 V. The electrons depart the target at different angles, with 22.5 degrees increment. For the hemispherical geometry, all electrons are deflected back to the sample. Surprisingly, for the flat geometry, a fraction of electrons reaches the collector. The color bar indicates the electron energy in ev. Figure 3.4: Electron trajectories for SEs escaping with an energy of 50 ev for both geometries when V sample = 0 V, V grid = -50 V and V collector = 0 V. The electrons depart the target at different angles, with 22.5 degrees increment. For the hemispherical geometry, most electrons reach the collector, while a few are being deflected back to the sample holder due to the electric field between grid and sample. For the flat geometry, only a fraction of electrons reaches the collector, while the rest of the electrons are deflected back to the sample. The color bar indicates the electron energy in ev. Figure 3.5: Electron trajectories for BSEs escaping with an energy of 60 ev for both geometries when V sample = 0 V, V grid = -50 V and V collector = 0 V. The electrons depart the target at different angles with 22.5 degrees increment. For the hemispherical geometry, most electrons reach the collector, while a few are being deflected back to the sample holder due to the electric field between grid and sample. For the flat geometry, most electrons reach the collector, while a fraction of electrons is deflected back to the sample. The color scale indicates the electron energy in ev. 17

18 Without having to quantify it, we can conclude from the simulations shown in figures 3.3, 3.4 and 3.5, that a hemispherical geometry has a larger collection angle and a higher electron collection efficiency than a flat geometry. It should be noted that it is possible for SEs and BSEs, depending on their escape angle, to escape out of the SEED analyzer through the hole in the collector. As a result, the SE yield will be affected. Furthermore, for the SE energy distribution measurements it is desired to have a hemispherical grid and collector so that the electrons escaping from the sample with sufficient kinetic energy to overcome the potential barrier between sample and grid, will actually reach the collector. In the case of a flat grid, most electron trajectories are not perpendicular to the grid. As a result, electrons with sufficient kinetic energy to overcome the potential could be deflected back to the sample holder. As a consequence, the recorded SE energy distribution will be distorted. 3.3 Final design After we determined that a hemispherical geometry for the grid and collector is more efficient, we could finalize the design. The drawing with all the dimensions is shown in figure 3.7. Objective 7 is achieved by choosing vacuum compatible and EUV compatible materials to construct the SEED analyzer. The collector and sample holder are made from oxygen-free copper. The grid is made out of non-magnetic stainless steel. The three electrodes are electrically isolated from each other and the housing by five aluminum oxide (Al 2 O 3 ) rings. The housing is made of aluminum and contains three UHV fluor-free SMA connectors that are connected to the sample holder, grid and collector. Since the collector, grid and the sample are made out of different materials, they have different work functions. It should be noted that this could cause a shift in the SE energy distribution. Based on the work functions of the different materials, we can estimate that the shift in the SE energy distribution should not be more than 1-2 ev. Objective 8 was guided by the vacuum chamber dimensions of three different setups: a stand-alone vacuum chamber, a SEM and the TNO EUV Beam Line. The stand-alone vacuum chamber was the limiting factor, since it had the smallest dimensions. The final result is shown in figure 3.8. Figure 3.7: Cross-section of the final design of the SEED analyzer. The materials of the collector, grid, sample holder, housing and isolation material are numbered. The dimensions differ from the final result. 18

19 Figure 3.7: Construction drawing of the SEED analyzer (cross-section) mounted on its holder. The dimensions are given in mm. Figure 3.8: Photos of the SEED analyzer. Top left: the three SMA connectors connected to the sample holder, grid and collector. Top right: the opening where the primary electrons enter. Bottom left: what the grid inside the SEED analyzer looks like. Bottom right: the sample holder at the bottom of the SEED analyzer. 19

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21 Chapter 4. Investigated materials 4.1 Samples We chose to investigate the SE yield and SE energy distribution for two different materials: gold and glassy carbon. Gold samples are used as a literature benchmark in order to verify the setup, because this material has been extensively investigated. Glassy carbon is the material for which we want to know the SE energy distribution, since it is the target material in the EUV power sensor Gold The SE emission of gold has been well-studied [10, 11], which is why this material serves as a literature benchmark. By reproducing the BSE and SE yield of gold, we can verify our measurement protocol, the working principle of the SEED analyzer, the electron source and the rest of the setup. A Monte Carlo simulation of the trajectories of an electron beam pointed out that in the energy range of interest (300 ev 2000 ev), PEs will penetrate only a few nm s deep below the surface [15]. In the simulation, we considered a PE beam with energy 2 kev interacting with a 50 nm gold layer on top of a silicon substrate (see figure 4.1). The blue lines represent the PE trajectories, while the red lines represent the SE trajectories. As can be seen, the PEs and SEs do not penetrate further than 10 nm. This is why 50 nm gold thin films were fabricated as described in Appendix A. Gold has a work function of 5.38 ± 0.07 ev [16]. Figure 4.1: Monte Carlo simulation of the electron interaction with gold. The green line represents the incoming PE beam. The trajectories of the PEs through the gold layer are shown in blue. The SE trajectories are shown in red. The PEs do not penetrate further than 10 nm and there are no SEs generated below this depth. 21

22 4.1.2 Glassy carbon The target material in the EUV power sensor is glassy carbon (or vitreous carbon). It is a form of pure carbon produced by the thermal decomposition of a three-dimensional cross-linked polymer. The most important properties are the low electrical resistance and zero open porosity which gives a low permeability to gases. This results in extreme resistance to chemical attack and impermeability to gases and liquids, making this material suitable for an EUV environment. In addition, it is expected that a (glassy) carbon target is much less sensitive to OoB photons than to EUV photons, which is a favorable property for the target material of an EUV sensor [5]. The SE yield curve and the SE energy distribution of this material could not be found in literature. We did find the SE yield curve for carbon (although it is not clear what kind of carbon) and it is assumed that the SE yield for glassy carbon shows similar features. The reference data is presented in section 4.3. Carbon has a work function of 5 ev [12]. This material was bought from Goodfellow. 4.2 Sample analysis As discussed in chapter 2, the SE emission of a material depends on different parameters such as surface roughness, elemental composition and possible surface contamination. Different analysis methods were carried out prior to experiments to get a complete overview of these different parameters that could affect the SE emission. Optical microscopy was used to investigate the particle contamination on the micro-scale. Surface profile measurements were performed to measure the surface roughness of the different samples. A scanning electron microscope (SEM) was used to investigate the surface structure and particle contamination on the nanoscale. Energy Dispersive X-ray spectroscopy (EDX) analysis was done to study the elemental composition of the samples Optical microscopy Optical microscopy is used to inspect the surface of the samples for any dirt particles before measurements. The microscope that was used was the Keyence VHX From the microscope images below (figures 4.2 and 4.3), we can see that the surfaces of the two samples do not contain many dirt particles on the micro-scale. Figure 4.2: Optical microscopy picture of the gold sample. The black spots are small dirt particles on the surface of the sample and were removed before electron exposure by blowing the sample with nitrogen gas. 22

23 Figure 4.3: Optical microscopy picture of the glassy carbon sample. The black spots are small dirt particles on the surface of the sample and were removed before electron exposure by blowing the sample with nitrogen gas Surface profile measurements The SE emission also depends on the roughness of the sample surface. For example, it is expected that a surface with a higher roughness will have a higher SE yield than a surface with a lower roughness, because it has a larger surface from which SEs can escape. Of course, the angular distribution of the SEs and collection efficiency of the detector also play a role in quantifying the SE yield. To determine the surface roughness of the samples, surface profile measurements were taken with a Dektak Profilometer before e-beam exposure (see figure 4.4). From the surface profile, the R a value (roughness average) and the R q value (RMS roughness) can be calculated (see table 4.1). The scanning length was 100 µm for both samples and it can be seen that their surface roughness is comparable. 23

24 Figure 4.4: Surface profile measurement of gold and glassy carbon samples. The samples have a similar roughness. Table 4.1. Surface roughness parameters for the gold sample and glassy carbon sample. Gold Glassy carbon R a (nm) R q (nm) SEM and EDX analysis To investigate the surface of the samples on the nanometer scale, a SEM (FEI Nova NanoSEM 650) was used. The images made with a SEM give topographical as well as compositional information of the sample surface. The SEM contains four detectors that operate in high vacuum mode: the Everhart-Thornley Detector (ETD), the Through Lens Detector (TLD), the Circular Backscatter Detector (CBS) and Energy-Dispersive X-Ray Spectroscopy Detector (EDS) to perform EDX analysis. The ETD detects SEs and is a low-resolution detector used for sample navigation. The TLD can collect both SEs and BSEs and is used for high resolution image formation after the area of interest is found with the ETD. The CBS detects BSEs and is used to highlight the topography. The primary beam energy was 15 kv during imaging. The obtain images are shown in figures 4.5 and 4.6. In figure 4.5 we see the image, formed by the TLD, of the gold sample. The grain structure due to sputter deposition is clearly visible. Figure 4.6 displays the image, formed by the TLD, of the glassy carbon sample. The low contrast in the image indicates a low surface roughness and a pure elemental composition. 24

25 Figure 4.5: SEM images, obtained with the TLD, of a gold sample fabricated by sputter deposition. The crystal structure of gold results in the grain structure visible in this image. 25

26 Figure 4.6: SEM image of a glassy carbon sample obtained with the TLD. The low contrast in the image indicates that the sample surface is flat and has a pure elemental composition. To analyze the elemental composition of the sample, energy-dispersive X-ray spectroscopy (EDX) measurements were done before e-beam exposure. EDX is a technique used for the elemental analysis of a sample. This technique makes use of the fact that each element has a unique atomic structure allowing a unique set of peaks in its X-ray emission spectrum. The energy levels of the X-rays are associated with the elements present on the sample and the shell levels that generated them. The EDX measurements were performed with the same SEM. The primary e-beam of the SEM interacts with the sample and causes X-ray emission. The EDS detects the X- rays. From the results of the EDX analysis, shown in figures 4.7 and 4.8, we can conclude that the gold sample contains some carbon contamination, while the glassy carbon sample contains no other elements than carbon. The high peak for at Si for the gold sample (figure 4.7) can be explained due the relatively high PE energy of 15 kev. At this energy, the PEs penetrate through the 50 nm gold layer and also interact with the silicon substrate. 26

27 Figure 4.7: EDX results of the sputtered gold sample. The sample consists of 83.9% Si, 5.7% C and 10.4% Au. Figure 4.8: EDX results of a glassy carbon sample. The sample does not contain any other elements than carbon. 4.3 Reference data To benchmark the results that we obtain with the SEED analyzer for SE yield measurements and SE energy distribution measurements, we use experimental SE yield and BSE yield data reported in literature as well as Monte Carlo simulations as references. For the experimental reference data, we consulted a database on electron-solid interactions compiled by D. Joy [17]. This database contains SE yields and BSE yields as a function of PE energy for a large number of elements, including gold (see figure 4.9) and carbon (see figure 4.10). The data was collected from published sources, but has not been judged on quality. Discrepancies between the different data sets (different sources) of a material could be the result of surface contamination and different measurement setups and/or environmental conditions. In addition to experimental reference data, we also use Monte Carlo simulations to compare our data to [18]. The simulation package contains a combination of Mott cross-sections with phonon-scattering based cross- 27

28 section for the elastic scattering of electrons and a dielectric function theory approach for inelastic scattering and generation of SEs. In the simulations, an incident PE beam interacts with the surface of a target material and generates SEs and BSEs. From these simulations we can obtain the SE yield and BSE yield for the investigated materials, gold and glassy carbon (plotted in figure 4.9 and figure 4.10), and also the SE energy distributions. In chapter 6, where we present the results of the SE yield measurements performed with the SEED analyzer, we will use the SE yield and BSE yield reference data in figures 4.9 and 4.10 to compare to the SE yield and BSE yield that we obtained for gold and glassy carbon. The results of the SE energy distribution measurements are presented in chapter 7, for which we will use the Monte Carlo simulations in figure 4.11 to compare with the data that we obtained. Figure 4.9: Reference data for the SE yield and BSE yield as a function of PE energy for gold. The reference data consists of experimental results reported in literature as well as Monte Carlo simulations [17, 18]. The large spread in the yields can be explained by the fact the data is obtained by different sources that performed the experiments with different measurement setups and/or under different environmental conditions. 28

29 Figure 4.10: Reference data for the SE yield and BSE yield as a function of PE energy for carbon. The reference data consists of experimental results reported in literature as well as Monte Carlo simulations. The large spread in the yields can be explained by the fact the data is obtained by different sources that performed the experiments with different measurement setups and/or under different environmental conditions. 29

30 Figure 4.11: Monte Carlo simulations of the SE energy distribution of gold and glassy carbon. The (relative) number of electrons is given as a function of their energy. These SE energy distributions will be used as references for the data that we obtained with the SEED analyzer. 30

31 Chapter 5. Experimental setup 5.1 Requirements for the experimental setup The experimental setup to perform SE yield and SE energy distribution measurements needs to consist of a vacuum chamber containing an electron beam source and the SEED analyzer with its opening placed perpendicular to the electron source. In order to limit the interaction of electrons with molecules in the gas phase, the desired chamber pressure during measurements is < 10-6 mbar (high vacuum). It is inevitable that the surface of the sample mounted in the SEED analyzer will get contaminated, but the lower the pressure, the longer the sample surface remains clean. For the materials that we investigate, it is expected that their maximum SE yield lies between ev, as can be seen in figures 4.9 and Based on this, we require that the electron source has an energy range of at least ev to observe the maximum SE yield. The opening of the SEED analyzer has a diameter of 1.5 mm, so the spot size of the PE beam has to be smaller than 1.5 mm. The emission current of the PE source has to be larger than 1 pa, in order to read out the currents of the sample, grid and collector with three source meters (Keithley 2450 source meter). The source meters also function as three separate voltage sources. To connect the source meters to the SEED analyzer, it is necessary to have a feedthrough with 3 SMA connectors. For the alignment of the SEED analyzer with the electron source and to set the working distance, it is of importance to mount the SEED analyzer on a stage that moves in x,y,z-direction. Figure 5.1 shows a schematic overview of the required experimental setup. To meet these requirements, we considered two different experimental setups: a self-built setup consisting of a vacuum chamber and electron gun, and a scanning electron microscope. Figure 5.1: Schematic overview of the measurement setup for SE yield and SE energy distribution measurements. The setup consists of an electron source mounted on the vacuum chamber and the SEED analyzer with its opening placed perpendicular to the electron gun. 5.2 Electron gun setup The first setup that we considered to use for our experiments was a self-built setup consisting of an electron flood gun (Kimball Physics EFG-7) and a manipulator mounted on opposite sides of a vacuum chamber. According to its specifications, the electron gun operates at pressures lower than 10-5 mbar, has an energy range of 100 ev 5000 ev, an emission current range of 1 na to 100 µa and a spot size of 1 mm at 25 mm working distance. Its tunable parameters are the beam energy, the source voltage in order to set the emission current, the focus voltage and x/y deflection voltages. Outside the vacuum chamber the electron gun is connected to its controller (Kimball Physics EGPS-2017). 31

32 The vacuum chamber is mounted on a turbo pump with pre-pump and can reach a pressure of mbar during measurements. The manipulator holds the SEED analyzer and moves in x,y,z-direction to manually align it with the electron gun. From its center, the manipulator can move about 3 mm in both x- and y-direction. The working distance was about 3 cm for the minimum PE beam spot size. A feedthrough with three SMA connectors is mounted on the vacuum chamber to connect the SEED analyzer to the three source meters outside the vacuum chamber. The vacuum chamber also contains two pressure sensors: a Pfeiffer compact capacitance gauge and a Granville Philips ion gauge. The capacitance gauge has a measuring range down to 10-3 mbar, while the ion gauge is used to measure the pressure below 10-6 mbar. The advantage of this setup is that it can reach a relatively low pressure (< 10-7 mbar). The disadvantage of this setup is the electron gun: its minimum spot size is larger than expected (and specified), long warm-up time (about 2 hours) after turning on and long stabilization time when varying the beam energy. More information about the characterization of the electron gun can be found in Appendix B. Based on these disadvantages, we decided not to use this setup for SE yield nor SE energy distribution measurements. Figure 5.2: The SEED analyzer mounted inside the vacuum chamber onto to the manipulator. The SEED analyzer is aligned with the electron gun and connected to the source meters with three UHV SMA cables via the feedthrough on the opposite side of the viewport. 5.3 Scanning electron microscope The second experimental setup that we considered for our experiments is a FEI Nova NanoSEM 650 scanning electron microscope (SEM). It is a dual beam system with a beam energy range of 200 ev 30 kev. By using aperture 7, with an opening diameter of 30 µm, the primary beam current is in the range of 0.6 pa 200 na. The spot size is mm and the working distance is 21 mm. The SEED analyzer is mounted on the sample stage of the SEM with a Teflon holder that also serves as an insulator between the analyzer and the stage (see figure 5.3). The alignment is done with the ETD in the software of the SEM. The SEM can be operated in scanning mode in order to minimize carbon deposition on the sample in the SEED analyzer during PE exposure. The vacuum 32

33 chamber has an opening to mount a feedthrough flange with three SMA connectors, which makes it possible to connect the SEED analyzer to the three source meters. Advantages of using this setup for measurements with the SEED analyzer are the smaller spot size, electron source stability and easier PE beam alignment with the SEED analyzer s opening. The disadvantage is that the system operates at a relatively high pressure ( mbar), compared to the setup described in section 5.1, making carbon deposition on the sample surface during e-beam exposure more likely. Nevertheless, the SEM proved to be a more suitable setup for our experiments, because of its smaller spot size and stable primary current. Because of these reasons, we used the SEM for SE yield and SE energy distribution measurements. Figure 5.3: Top view of the SEED analyzer mounted the Teflon holder on the stage of the SEM. The collector, grid and sample holder of the SEED analyzer are connected via three UHV SMA cables to the source meters. 33

34 5.4 Data acquisition and processing The three source meters are controlled via USB by software on a measurement PC. The source meters are used as three separate voltage sources, while reading out the currents from the collector, grid and sample with pa precision. The software allows to set the bias voltage on each source meter separately and log the currents. Ideally, the source meters measure only the currents due to PEs, SEs and BSEs. However, in reality, insulators are imperfect. As a result, additional current flows through a source meter when a bias voltage is applied. This is generally referred to as leakage current or background current. Since the PE beam of a SEM has a relatively small current (in the order of na s), the background current from the source meters (in the order of na) is not negligible. To correct for this, a background current measurement is performed for every bias voltage setting with the PE beam blanked, to subtract from the current measurement during PE exposure. The background current should be a small fraction of the PE (total) current to avoid systematic errors in the BSE yield, TE yield and calculated SE yield. The exact measurement protocols for SE yield measurements and SE energy distribution measurements are described in chapter 6 and chapter 7, respectively. 34

35 Chapter 6. Secondary electron yield measurements The SE yield measurements serve as a verification of the measurement setup. By comparing the measured SE yields of gold and glassy carbon targets with literature data we can conclude to what extend the SEED analyzer and the rest of the setup functions properly. In this chapter we present our experimental results obtained with the SEED analyzer in a SEM, starting with a description of the measurement protocol for SE yield measurements, followed by a discussion of the obtained data and a comparison with reference data. 6.1 Measurement protocol & data processing The SE yield can only be quantified indirectly by distinguishing the low energy SEs from the TEs (total emitted electrons: SEs and BSEs) per PE energy. This is achieved by performing two measurements with different voltage bias settings of the SEED analyzer s collector, grid and sample holder. In the first measurement, called the TE measurement mode, the TEs are measured. From this measurement, the TE yield can be determined. The second measurement, called the BSE measurement mode, measures the BSEs and is used to determine the BSE yield. Subtracting the BSE yield from the TE yield results in the SE yield. The SE yield measurements for both gold and glassy carbon are performed in the primary electron energy range 300 ev 2000 ev according to the following protocol: 1) The PE beam is aligned with the opening of the SEED analyzer by moving the stage in the x,y-direction. The working distance is set 21 mm by moving the stage in the z-direction. 2) The PE energy is set to 300 ev and the primary beam current is set to 1 na. 3) In the TE measurement mode, a bias voltage of +50 V is applied to the grid, while the sample and collector remain at 0 V. All electrons (SEs and BSEs) escaping from the sample are accelerated with +50 V to the grid and reach the collector (see figures 6.1a and 6.1b). The collector current, grid current and sample current are measured for 20 seconds. The TE current will be given by the sum of the grid current and the collector current. The PE current will be given by the sum of the collector current, grid current and sample current. 4) A background current measurement is done by blanking the PE beam and repeating step 3. The measurement time is 20 seconds. 5) In the BSE measurement mode, a bias voltage of -50 V to the grid, while the sample and collector remain at 0 V. Only the electrons that escape from the sample with an energy higher than 50 ev (BSEs) can overcome the potential barrier between the sample and grid will reach the collector (see figure 6.1d). The electrons with an energy lower than 50 ev (SEs) are repelled back towards the sample (see figure 6.1c). The collector current, grid current and sample current are measured for 20 seconds. The BSE current will be given by the collector current. The PE current will be given by the sum of the of the collector current, grid current and sample current. 6) A background current measurement is done by blanking the PE beam and repeating step 5. The measurement time is 20 seconds. 7) The PE energy is increased and steps 3-6 are repeated for the energies 400 ev, 500 ev, 600 ev, 700 ev, 800 ev, 900 ev, 1000 ev, 1200 ev, 1400 ev, 1600 ev, 1800 ev, 2000 ev. The primary beam current increases automatically when the PE energy is increased. 35

36 Figure 6.1: COMSOL simulations of the trajectories of electrons escaping from the sample in the TE measurement mode and BSE measurement mode. a) TE measurement mode: V sample = 0 V, V grid = +50 V, V collector = 0 V. SEs escaping from the sample with 40 ev are attracted to the grid and overcome the -50 V potential barrier between grid and collector. b) TE measurement mode: V sample = 0 V, V grid = +50 V, V collector = 0 V. BSEs escaping from the sample with 60 ev are attracted to the grid and also reach the collector. c) BSE measurement mode: V sample = 0 V, V grid = -50 V, V collector = 0 V. SEs escaping from the sample with 40 ev do not overcome the -50 V potential barrier between the sample and grid. d) BSE measurement mode: V sample = 0 V, V grid = -50 V, V collector = 0 V. SEs escaping from the sample with 60 ev overcome the potential barrier between sample and grid and reach the collector. After the measurement is completed, the SE yield is determined as follows: 1) The raw data consists of the twelve measured currents (I collector, I grid and I sample during PE exposure and during a background measurement, per measurement mode) as a function of time. The background currents (where the beam was blanked) are subtracted from the corresponding PE beam exposure currents. All currents are averaged over their measurement time for every PE energy. This results in three new arrays, I C, I G and I S, per measurement mode. 2) The TE current, I TE, is determined by taking the sum of the grid current and collector current, measured in the TE measurement mode: I I< = I J + I K (8) The PE current in the TE measurement mode, I PE1, is determined by taking the sum of the collector current, grid current and sample current: I =<, = I K + I J + I ; (9) 36

37 The BSE current is equal to the collector current, measured in the BSE measurement mode: = I K (10) The corresponding PE current in the BSE measurement mode, I PE2, is determined by taking the sum of the collector current, grid current and sample current: I =<G = I K + I J + I ; (11) This results in 4 new data arrays: I TE, I PE1, I BSE, I PE2. I TE consists of the average TE current values as a function of PE energy. I PE1 consists of the average PE current values of the TE measurement. I BSE consists of the average BSE current values as a function of PE energy. I PE2 consists of the average PE current values of the BSE measurement. 3) The TE yield is then calculated as a function of PE energy: 4) The BSE yield is calculated as a function of PE energy: TE yield = I I< I =<, (12) BSE yield = I =<G (13) 5) Finally, the SE yield as a function of PE energy is calculated by subtracting the BSE yield from the TE yield: SE yield = TE yield BSE yield (14) 6.2 Gold Figure 6.2 shows the raw data of a gold sample in the SEED analyzer during the TE measurement mode (steps 3 and 4 in the measurement protocol). In this measurement mode, the voltage bias settings were V sample = 0 V, V grid = +50 V and V collector = 0 V, in order to attract all SEs and BSEs to the grid and collector. The graph shows the collector current I collector (blue), the grid current I grid (red) and the sample current I sample (yellow) as a function of time during PE beam exposure and subsequent background (blanked PE beam) measurements. This, combined with the fact that the PE energy, and thus the primary beam current, increase as a function of time, explains the square wave and step trend in the graph. The high positive current values for I grid and I collector and the low negative current values for I sample represent the current measurement during primary electron exposure. The lower current value steps in between represent the background measurements. The negative values of I sample indicate that there are more electrons escaping the sample than entering. As expected, the SEs and BSEs travel from the sample towards the grid and collector, which expresses itself in the positive values of I grid and I collector. The positive values for I collector is a result of the electrons that have an energy larger than 50 ev and can overcome the potential difference between the grid and collector. 37

38 Figure 6.2: The raw data of SE yield measurements on a gold sample. The data consists of current measurements during PE exposure and during background (blanked beam) current measurements in the TE measurement mode. The collector current, the grid current and the sample current are plotted as a function of time. During the measurement, the PE beam current increases when the PE beam energy is increased, hence the square wave and step trend in the graph. The negative sample current and positive grid and collector currents indicate that electrons escape from the sample and travel to the grid or collector. In figure 6.3 the measured currents of the collector (blue), grid (red) and sample (yellow) are shown during the BSE measurement mode (steps 5 and 6 in the measurement protocol). Again, the data shows a square wave and step trend due to subsequent current measurements during primary electron exposure and (blanked beam) background measurements for increasing PE beam current when the primary electron beam energy is increased. During this measurement only the BSEs escape from the sample towards the collector, while the SEs are retracted back to the sample. Since the number of SEs is much larger than the number of BSEs, I sample is larger than I collector. The grid current I grid is negative due to the fact that its biased at -50 V. 38

39 Figure 6.3: The raw data of SE yield measurements on a gold sample. The data consists of current measurements during PE exposure and during background (blanked beam) current measurements in the BSE measurement mode. The collector current, the grid current and the sample current are plotted as a function of time. During the measurement, the PE beam current increases when the PE beam energy is increased, hence the square wave and step trend in the graph. Only the BSEs escape from the sample towards the collector, while the SEs are retracted back to the sample. The next step in the data analysis process is the subtraction of the background current measurements from their corresponding current measurement during PE beam exposure. In this step we correct for the background signal originating from the source meters and the rest of the setup, as was explained in section 5.4. Averaging the resulting current signals over the measurement time per primary beam energy for both TE and BSE measurement modes, leads to the currents shown in figure 6.4 and figure 6.5, respectively. The graphs show the averaged collector current, grid current, sample current and the PE current as a function of the PE beam energy. In figure 6.4, the TE current is given by the sum of the collector current and the grid current. The PE current is given by the sum of all three electrode currents. It is striking that the extent to which the grid current increases, as a function of PE energy, is much larger than the extent to which the sample current decreases. This suggests that (a fraction of) PEs is interacting with the grid, since the grid current and total (primary) current are almost equal, while the grid bias remains +50 V during the whole measurement. From the settings for the PE beam (see section 5.3), we would assume that there are no PEs interacting with the grid, because the PE beam is aligned with the center of the opening in the SEED analyzer, has a spot size of mm and is scanning over an area of mm 2, which is much smaller than the mm 2 opening in the grid. However, the grid inside the SEED analyzer is not perfectly concentric with the opening in the collector (see Appendix C), making it not impossible for PEs to interact with the grid. This will clearly result in a TE yield higher than expected and thus will also impact the SE yield. 39

40 Figure 6.4: The collector current (blue), grid current (red), sample current (yellow) and primary current (sum of the three) (purple) as a function of PE energy in the TE measurement mode during measurements on a gold sample. This data is obtained by subtracting the background current from its corresponding current measurement during PE beam exposure and averaging the resulting current data over the measurement time. The negative sample current indicates the emission of TEs, while the positive grid and collector currents represent the TEs. The primary current (purple) is equal to the sum of the three currents. The relatively large grid current can be explained by the interacting of PEs with the grid. In figure 6.5 the BSE current is given by the collector current, while the PE current is given by the sum of the collector current, grid current and sample current. The positive values of the sample current indicate that there are more incoming electrons at the sample than outgoing. Since the number of BSEs is relatively small compared to the number of SEs, which are retracted back to the sample, the sample current is much larger than the collector current. The fact that the grid current is negative and decreases as a function of PE energy, indicates that there are also SEs (or BSEs) generated at the grid by either the primary electrons or the BSEs escaping from the sample (or both). If PEs would interact with the grid, the grid current would most likely be in the order of the total PE current, as we saw in figure 6.4. So, based on the fact that the grid current is relatively small compared to the primary current, we can conclude that the BSEs originating from the sample are responsible for the decrease in grid current as function of the PE energy. Since the SEs, generated at the grid, experience an accelerating voltage of +50 V in both directions (towards the sample and towards the collector), we do not know to what extent the collector current and/or the sample current are affected by these SEs. If most of them travel to the collector, the measured BSE yield will be increased. If most of them travel to the sample, the measured BSE yield will be lowered. What we can conclude is that the SE emission of the grid affects the BSE yield and, as a result, the SE yield of the target material. This is discussed in more detail in section

41 Figure 6.5: The collector current (blue), grid current (red), sample current (yellow) and primary current (sum of the three) (purple) as a function of PE energy in the BSE measurement mode during measurements on a gold sample. This data is obtained by subtracting the background current from its corresponding current measurement during PE beam exposure and averaging the resulting current data over the measurement time. The collector current equals to the BSEs. The SEs escaping from the sample are retracted by to the sample. Since the number of SEs is larger than the number of BSEs, the sample current is larger than the collector current. The fact that the grid current decreases as a function of PE energy denotes SE emission at the grid induced by BSEs originating from the sample. With the average collector current I C, grid current I G, sample current I S and primary current I PE1 as a function of PE energy we can now determine the BSE yield and TE yield and calculate the SE yield. By taking the sum of the grid current and the collector current in the TE measurement mode as the TE current (equation 8) and the corresponding PE current (equation 9), we can calculate the TE yield with equation 12. The same was done for the BSE yield. By dividing the collector current I C in the BSE measurement mode (equation 10) with the calculated corresponding PE current I PE2 (equation 11), we can determine the BSE yield (equation 13). Finally, the SE yield is calculated with equation 14. The resulting TE yield, BSE yield and SE yield of gold as a function of the primary electron landing energy are shown in figure 6.6. It should be noted that the SE yield curve follows the shape of the universal theoretical SE yield curve shown in figure 2.1. The SE yield increases with primary electron energy, reaches a maximum value and then decreases with increasing primary electron energy. The maximum SE yield value is 1.4 ± 0.3 at 700 ev. 41

42 Figure 6.6: The measured TE (SE+BSE) yield, measured BSE yield and resulting SE yield of gold as a function of the primary electron landing energy. The SE yield peaks at 700 ev with a value of 1.4. To benchmark the SE yield (and BSE yield) curves, shown in figure 6.6 against literature, we use the experimental reference SE yield and BSE yield data reported in literature and Monte Carlo simulations of the SE yield and BSE yield for gold, as discussed in section 4.3. We start with the BSE yield, since it was directly measured, and then follow with the SE yield. Figure 6.7 compares the BSE yield of gold, directly measured with the SEED analyzer, with experimental reference data and a Monte Carlo simulation. The graph shows that the BSE yield is 15-20% lower than what has been reported in literature [13, 14]. In previous chapters we have mentioned different factors that could affect the SE yield and/or BSE yield, including surface contamination (carbon deposition) during PE exposure and systematic measurement errors, such as the loss of BSEs through the opening of the SEED analyzer or (high) current leakage in the electrical circuit. By looking at the raw measurement data (figures 6.2 and 6.3), current leakage can be rejected as a cause of the discrepancy. The background current values are all in the order of na and vary over a very small range compared to the measured current during PE exposure. The effect of surface contamination on the BSE yield is expected to be small, since (most) BSEs have a much larger escape depth ( nm) and energy than SEs [12]. This means that the BSEs will penetrate through a contamination layer, usually in the order of 1 nm or less, during their outward trajectory. The effect of (a fraction of) BSEs escaping the SEED analyzer, however, could be a possible explanation for the discrepancy between our BSE yield data and the reference data. Since most BSEs have a small escape angle with respect to the surface normal of the sample, it is likely that (a fraction of) BSEs escape through the opening of the SEED analyzer and are not measured at the collector. This would result in a lower BSE yield than expected. A more in-depth analysis of this problem is given in section 6.4, after we have presented the experimental results for glassy carbon in section 6.3. The PE energy dependence (and thus PE current dependence) of the grid current in the BSE measurement mode (see figure 6.5) indicated that SE emission at the grid occurs. The fact that the BSE yield is lower than the 42

43 reference data hints at an increased sample current as a result of (most) SEs, generated at the grid, traveling to the sample. Since we do not know to what extent this effect occurs, we make a rough estimation for both possibilities, i.e. SE emission from the grid towards the collector and SE emission from the grid towards the sample. Making the assumption that all SEs from the grid reach the collector, we use the largest deviation for the grid current with respect to the expected value for the grid current (~ 0.01 na), which is at 1800 ev (see figure 6.5). At 1800 ev, the sample current is 2.24 na, the grid current is na, the collector current is 0.72 na and the total (PE) current is 2.73 na. We correct for SEs of the grid at the collector by subtracting 0.25 na (the grid current) from the collector current and adding 0.25 na to the grid current. Calculating the BSE yield, results in a value of 0.18 at 1800 ev, which deviates with from the value in figure 6.6. Assuming that the SEs of the grid travel to the sample, we subtract 0.23 na (grid current) from the sample current and add 0.24 na to the grid current. This gives a BSE yield of 0.26, which deviates with 0.08 from the value in figure 6.6. From this, we can conclude that the SE emission at the grid causes an error up to 0.08 in the BSE yield. The effect of the loss BSEs through the opening of the grid, described in section 6.4.1, estimates that 3.5% of the BSEs is lost. The (rough) correction for the combination of these two effects leads to a BSE yield that is roughly 0.12 higher than is shown in figure 6.7, which is close to the reference data. Figure 6.7: The BSE yield of gold as a function of the primary electron energy. The BSE yield was directly measured with the SEED analyzer and is here compared with experimental data reported in literature and a Monte Carlo simulation. The graph shows that the data obtained with the SEED analyzer has a lower BSE yield than the reference data. Figure 6.8 illustrates how the SE yield in figure 6.6 compares to the experimental reference data as well as a Monte Carlo simulation of the SE yield of gold. It can be seen that our data fits in well within the large spread of 60% in the reference data. The observed maximum SE yield of 1.4 at 700 ev PE energy also agrees with the PE energy at the maxima of the reference curves. However, as discussed above, there are two effects that influence the TE yield. The PE energy dependence and relatively large values of the grid current in figure 6.4 indicated that PEs interacted with the grid during exposure. This results in SE emission at the grid and increases the TE yield. A 43

44 second effect influencing the TE yield, is the loss of TEs through the opening of the SEED analyzer. The BSEs escaping from the sample already have a small escape angle with respect to the surface normal. Additionally, n the TE measurement mode, the electron trajectories are converged (see figure 6.1) due to the voltage bias setting. This means that it is very likely that a significant fraction of SEs also escapes through the opening of the SEED analyzer. The loss of BSEs and SEs during the TE measurement lowers the TE yield. It is not clear to what extent these two effects, i.e. PE interaction with the grid and loss of TEs through the SEED analyzer s opening (including the lens effect due to the voltage bias setting), are affecting the TE yield, which makes it difficult to estimate an error in the resulting SE yield after subtracting the BSE yield. Nonetheless, we do expect that the error would be within the 60% spread of the reference data. Figure 6.8: The SE yield of gold obtained with the SEED analyzer compared with experimental data reported in literature and a Monte Carlo simulation. The graph shows that our data obtained is in good agreement with the reference data. 6.3 Glassy carbon Next, we present the experimental results of a SE yield measurement on glassy carbon. In the same manner as for the gold sample, the TE yield and BSE yield were directly measured with the SEED analyzer according to the measurement protocol in section 6.1. Figure 6.9 shows the raw data of a glassy carbon target in the SEED analyzer during the TE measurement mode (steps 3 and 4 in the measurement protocol), in which all SEs and BSEs travel to the grid and collector. The graph shows the collector current I collector (blue), grid current I grid (red) and sample current I sample (yellow) as a function of time during PE exposure. The graph also shows the subsequent background measurements during which the PE beam is blanked. Again, we see the square wave and step trend in the graph due to the blanking of the beam and the increase of the PE beam current when the PE energy is increased. As expected, the grid current is larger than the collector current and the sample current, because all SEs and BSEs emitted by the sample are attracted to the grid. BSEs can also overcome the potential barrier between grid and collector, hence the positive values for the collector current. It should be noted that the grid has a very large background current compared to the background currents of the sample and collector. 44

45 As we have seen in section 6.2, this was not the case for the measurements on gold. A possible explanation for this could be leakage current flowing in the electrical circuit of the setup. Since the background currents for the sample and collector are low, as expected, we can conclude that the current is not leaking through the insulating layers between the three electrodes (sample holder, grid, collector) in the SEED analyzer. Furthermore, it can be seen that the sample current is only negative during the first 300 seconds and becomes positive after. This means that during the first 300 seconds, there are more electrons (TEs) escaping than coming in. After 300 seconds, the number of incident electrons is larger than TEs. Figure 6.9: The raw data of SE yield measurements on a glassy carbon sample. The data consists of current measurements during PE exposure and during background (blanked beam) current measurements in the TE measurement mode. The collector current, the grid current and the sample current are plotted as a function of time. During the measurement, the PE beam current increases when the PE energy is increased, hence the square wave and step trend in the graph. The BSEs and SEs travel from the sample to the grid/collector. The high background current for the grid indicates that there is a (large) leakage current flowing. The measured currents of the collector (blue), grid (red) and sample (yellow) during the BSE measurement mode (steps 5 and 6 of the measurement protocol) are shown in figure The currents show the same trend as the data in figure 6.9. During this measurement only the BSEs escape from the sample towards the collector, while the SEs are retracted back to the sample. Since the number of SEs is larger than the number of BSEs, the sample current is larger than the collector current. The grid current is negative due to the fact that it is at -50 V. Again, the grid experiences a very large background current compared to the sample and collector, indicating a leakage current flowing during this measurement also. The fact that there is not a large difference in the grid current between background measurements and measurements during PE exposure demonstrates that there is almost no interaction of electrons with the grid. 45

46 Figure 6.10: The raw data of SE yield measurements on a glassy carbon sample. The data consists of current measurements during PE exposure and during background (blanked beam) current measurements in the BSE measurement mode. The collector current, the grid current and the sample current are plotted as a function of time. During the measurement, the PE beam current increases when the PE beam energy is increased, hence the square wave and step trend in the graph. Only the BSEs escape from the sample towards the collector, while the SEs are retracted back to the sample. The grid experiences a large background current, caused by a leakage current. In the next step of the data analysis process, the background currents are subtracted from their corresponding current during PE beam exposure. In this step we correct for the large background current for the grid, as well as the (smaller) background currents for the sample and collector. Averaging the resulting current signals over the measurement time per PE beam energy for both TE and BSE measurement modes, leads to the currents shown in figure 6.11 and figure The graphs show the averaged collector current I C (blue), grid current I G (red), sample current I S (yellow) and the PE current I PE (the sum of the three currents) (purple) as a function of the PE energy. In figure 6.11, the TE current is given by the sum of the grid current and collector current. The grid is at +50 V, so all SEs and BSEs are accelerated with 50 ev on their way to the grid. The SEs and BSEs that do not interact with the grid can reach the collector, because they have an energy larger than 50 ev and can overcome the potential barrier of -50 V between the grid and collector. This results in a positive grid current and collector current. The graph also exhibits that the sample current goes from negative to positive values at 700 ev. This means that the number of electrons escaping from the sample becomes smaller than the number of incident PEs at 700 ev and on, indicating that the TE yield is 1 at 700 ev and decreases for higher PE energy. In contrast to the data for gold in figure 6.5, we see that the grid current is significantly lower, which can be explained by the fact that the PE beam was properly aligned during this measurement. 46

47 Figure 6.11: The collector current (blue), grid current (red), sample current (yellow) and PE current (sum of the three) (purple) as a function of PE energy, in the TE measurement mode during measurements on a glassy carbon sample. This data is obtained by subtracting the background current from its corresponding current measurement during PE beam exposure and averaging the resulting current data over the measurement time. During this measurement the TEs (SEs and BSEs) travel from the sample to grid and collector. In figure 6.12 the BSE current is given by the collector current, while the PE current is given by the sum of the collector current, the grid current and sample current. The positive values for the sample current indicate that there are more incoming electrons than outgoing. Since the number of BSEs is relatively small compared to the number of SEs, which are retracted back to the sample, the sample current is much larger than the collector current. Just as we saw for gold (see figure 6.5), the grid current is negative and experiences a small decrease as a function of PE energy. There are two possible explanations for this. Either the BSEs, coming from the sample, generate SEs at the grid. Or the variation in the grid current as function of PE energy is a result of a systematic error due to the high background current. However, by comparing the grid current to the PE (total) current, we can conclude that this will have a very small effect on the BSE yield. The fact that the collector current (BSE current) is less than the BSE current for the gold sample (see figure 6.5) is material dependent. It demonstrates that the number of BSEs generated in glassy carbon is lower than the number of BSEs generated in gold within the PE energy range ev. 47

48 Figure 6.12: The collector current (blue), grid current (red), sample current (yellow) and primary current (sum of the three) (purple) as a function of PE energy, in the BSE measurement mode during measurements on a glassy carbon sample. This data is obtained by subtracting the background current from its corresponding current measurement during PE beam exposure and averaging the resulting current data over the measurement time. The collector current equals to the BSEs. The SEs escaping from the sample are retracted by to the sample. Since the number of SEs is larger than the number of BSEs, the sample current is larger than the collector current. The fact that the grid current decreases as a function of PE energy denotes SE emission at the grid induced by BSEs originating from the sample. With the average collector current, grid current, sample current and PE current as a function of PE energy we can now determine the BSE yield and TE yield and calculate the SE yield for glassy carbon. By taking the sum of the grid current I G and the collector current I C we first determine the TE current, I TE (equation 8). The corresponding PE current, I PE1, is calculated with equation 9. The TE yield is then given by the ratio between I T E and IP E1 (equation 12). To determine the BSE yield, we first calculate the BSE current, I BSE, with equation 10 and the PE current, I PE2, with equation 11. The BSE yield is then given by the ratio between the BSE current and PE current, as in equation 13. Finally, the SE yield is calculated by subtracting the BSE yield from the TE yield (equation 14). Figure 6.13 shows the measured TE yield and BSE yield and the calculated SE yield as a function of PE energy. The SE yield decreases with PE energy starting at 300 ev. 48

49 Figure 6.13: SE yield, BSE yield and TE (SE+BSE) yield of glassy carbon as a function of PE energy. The SE yield was indirectly determined by subtracting the measured BSE yield from the measured TE yield. The SE yield most likely peaks at 300 ev. To compare our data with literature, we used the same sources as for the reference data of gold, as mentioned in section 4.3 (see figure 4.3). The database also contains information about carbon, however, it is unclear what type of carbon exactly was investigated in the sources of the database. Nevertheless, the reference data does give an indication how well the SEED analyzer performs during SE yield measurements. In figure 6.14, we compare our measured BSE yield with the BSE yields reported in literature as well as with a Monte Carlo simulation. Just as for gold (see figure 6.8), our data is about 15% lower than the reference data. This strengthens the argument that a systematic loss of BSEs through the opening of the SEED analyzer occurs. In the following section we will investigate this problem in more detail. The combination of the loss of BSEs and not knowing to which extent the large leakage current for the grid affects the measurement, makes it difficult to estimate the error in the BSE yield. In figure 6.12, we saw that there is barely any SE emission at the grid, so this error can be neglected. If we assume that the loss of BSEs (discussed in the following section) is the same as for gold, which is 3.5%, then the BSE yield could be correct by increasing it with As a result, the BSE yield would agree with the reference data. At the moment, it is not clear what causes a larger discrepancy at low PE energy than at higher PE energy. It should be noted again that there is no information, such as elemental composition and surface roughness, available on the investigated samples of the reference data, other than that it is carbon. 49

50 Figure 6.14: The BSE yield from glassy carbon as a function of the PE energy. The BSE yield was directly measured with the SEED analyzer. For comparison, experimental data reported in literature and a Monte Carlo simulation are added. The graph shows that the data obtained with the SEED analyzer has a lower BSE yield than the reference data. A possible explanation for this is the loss of BSEs through the opening of the SEED analyzer. A comparison of the SE yield of glassy carbon with reference data is shown in figure Unlike for gold, the SE yield curve of glassy carbon does not show a clear peak, but, as we can see in the graph, the peak should be located between ev. The spread of 80% in SE yield reference data for glassy carbon is much larger than in the reference data for gold. Most likely, this is caused by the fact that the different datasets have been obtained with different experimental setups, and/or under different environmental conditions. It is also possible that the target materials, used by the different sources, have a different elemental composition. The SE yield curve that we obtained for glassy carbon is in good agreement with the reference data, since it fits within the 80% spread. The reference data exhibits a maximum SE yield around 300 ev PE energy, which is most likely also the peak for glassy carbon. 50

51 Figure 6.15: The SE yield from glassy carbon obtained with the SEED analyzer compared with experimental data reported in literature and a Monte Carlo simulation. The graph shows that the data obtained with the SEED analyzer is in agreement with the reference data, as most reference curves peak between 200 ev and 300 ev. 6.4 Systematic measurement errors The experimental results for both gold and glassy carbon indicate that three systematic errors have occurred during the measurements. From the results, it appears that there are BSEs escaping through the opening in the SEED analyzer. The results also exhibit that the grid emits electrons during the BSE measurement mode, for both materials, although the effect is very small for glassy carbon. For glassy carbon, there is also a relatively large background signal for the grid compared to the sample and collector. The measured BSE yield for both materials is significant lower than the BSE yields reported in literature, caused by the systematic errors during measurements. In this section, we will discuss these three observations in more detail Loss of backscattered electrons The BSE yields that we obtained for gold and glassy carbon are both lower than the reference data. This is most likely due to the fact that BSEs have a small escape angle, which results in loss of BSEs through the opening of the SEED analyzer. To get an idea of the significance of this effect, we calculate the opening angle 2α of the SEED analyzer in figure The opening has a diameter of 1.5 mm and the perpendicular distance from the center of the opening to the sample is 23 mm. The calculation is given by equation 15 and equation 16: 51

52 Figure 6.16: The opening diameter of the SEED analyzer is 1.5 mm and its perpendicular distance to the sample is 23 mm. The opening angle 2α of the SEED analyzer is 3.7. tan α = (15) 0.75 [, α = tan (16) So the opening angle of the SEED analyzer is 2α 3.7. We do not have the angular distributions of BSEs for gold and glassy carbon in the PE range ev, but to get an idea of how many BSEs have an escape angle smaller than 3.7, we look at the angular distribution of gold for a PE energy of 5 kev and 30 kev, shown in figure 2.2. The angular distributions look similar for both PE energies and show that most of the BSEs have an escape angle smaller around 0. For normal incidence, the curves are equal to a cosine distribution. If we assume that the angular distribution of BSEs for 1 kev primary electrons looks similar, we can conclude that BSEs escaping through the opening is indeed the cause for the low BSE yield. We estimate the percentage of BSEs lost, by integrating a normalized cosine distribution from to 1.87 (see figure 6.17). The loss of BSEs escaping through the opening of the SEED analyzer is estimated at 3.5%. This effect does not only affect the BSE yield. Since in the TE measurement mode BSEs and SEs are travelling towards the grid, the TE yield is also affected by this error. Due to the voltage bias settings in the TE measurement mode, the SEs and BSEs are converged. As a result, the effect is expected to be worse during the TE measurement than during the BSE measurement. Figure 6.17: Normalized cosine distribution similar to the BSE angular distribution of gold. The grey area under the curve represents the relative number of BSEs that escapes through the opening of the SEED analyzer. The opening angle of the SEED analyzer is 3.7, which is why the cosine distribution was integrated from to The percentage of lost BSEs is estimated at 3.5%. 52

53 6.4.2 Secondary electron emission at the grid The PE energy dependence of the negative grid currents during the BSE measurement mode for both materials (see figures 6.5 and 6.12) illustrates that the stainless steel grid emits electrons. As explained previously, the SEs of the grid must be generated by BSEs originating from the sample, since the PEs do not interact with grid. The BSEs have energies in the range 50 ev 2000 ev and the SE yield of stainless steel is larger than one within this range (see Appendix C). This explains the negative grid current. The fact that the absolute grid current for gold is larger than for glassy carbon can be explained due to the fact that the BSE yield for gold is larger than for glassy carbon. This means that there are more BSEs generated at the gold sample, which then travel to the grid. The SEs generated are attract to either the sample or the collector, as they experience a potential difference of +50 V in both directions. This affects the total (PE) current and/or the collector current during the measurement and, as a result, also the BSE yield. Since we do not know if the SEs emitted by the grid are measured at the sample or collector, we cannot quantify the error in the BSE yield. However, in the worst case, for which we assume that all SEs from the grid go to the collector, we estimate that BSE yield for gold should be 8% higher Current leakage The raw data of glassy carbon for both the TE measurement mode and BSE measurement mode shows a relatively large background signal for the grid compared to the signals of the collector and sample. The large current, obtained during a measurement in which the PE beam was blanked, indicates that there is a leakage current in the electrical circuit of the grid. A leakage current is a current that flows from a conductor through an (not-ideal) insulator to ground. Especially when the current leaks through the insulation layers between the collector, grid and sample, it can distort the yield measurements. However, because we observed the high background current only for the grid, we corrected for it by subtracting it from the current measurement during PE exposure. This problem occurred during both measurements for glassy carbon and recurred during the SE energy distribution measurements on glassy carbon. 6.5 Intermediate conclusion Even though the measured BSE yield for both gold and glassy carbon targets are lower than the reference data, comparison with the reference data shows that the SE yields obtained with the SEED analyzer are in good agreement. The deviations in the measured BSE yields from the reference BSE yields is for both materials smaller than the spread in the SE yield reference data. For gold, the measured BSE yield has a discrepancy of 15% with the reference data, but the spread in the SE yield reference data is 60%. For glassy carbon, the measured BSE yield also deviates with 15% from the reference data, while the spread in SE yield reference data is 80%. There are several possible factors that account for the discrepancies in yields, such as surface contamination, surface roughness and elemental composition. In addition, the systematic errors discussed in section 6.4, also affected the yields we obtained. The combination of the three types of systematic errors makes it difficult to quantify the measurement error in the TE yield, BSE yield and also in the SE yield. The loss of BSEs through the opening of the SEED analyzer is expected, based on the angular distribution of BSEs for gold, to be roughly 3.5%. We estimated that the SE emission of the grid during the BSE measurement mode lowers the BSE yield with 8%. However, qualitatively, we can conclude that without those measurement errors the SE yield of both gold and glassy carbon would still fit within the spread of the reference data. The SEED analyzer functions properly within an estimated error margin of 12%. 53

54 54

55 Chapter 7. Secondary electron energy distribution measurements The SE energy distribution of glassy carbon is what we are ultimately interested in. SE energy distribution measurements were performed with the SEED analyzer in a SEM for both gold and glassy carbon targets. In this chapter we describe the measurement protocol and data analysis process, followed by a presentation and discussion of the data. 7.1 Measurement protocol & data processing SE energy distribution measurements were performed for gold and glassy carbon targets at the PE energy of 1000 ev. During the measurements, the SEs and BSEs escaping from the sample towards the collector are filtered on their energy by varying the bias voltage on the grid from -100 V to +10 V. The voltage sweep is continued from 0 V to +10 V to correct for the difference in work function of the different materials inside the SEED analyzer, as explained in section 3.3. The measurements were carried out according to the following protocol: 1) The PE beam is aligned with the opening of the SEED analyzer by moving the SEM stage in the x,ydirection. The working distance is set at 21 mm by moving the stage in the z-direction. 2) The PE energy is set to 1000 ev and the primary beam current is set to 1.9 na. 3) The bias voltage on the grid is swept from -100 V to +10 V, while the sample remains at 0 V and the bias voltage on the collector is swept with +50 V with respect to the bias voltage on the grid. For example, at -80 V on the grid, only electrons with an energy higher than 80 ev (BSEs) will reach the collector, as illustrated in figure 5.5. At 0 V on the grid, for example, all SEs and BSEs reach the collector. The collector current, grid current and sample current are measured for 30 seconds. 4) A background measurement is performed by blanking the PE beam and repeating step 3. Figure 7.1: COMSOL simulations of the electron trajectories during a SE energy distribution measurement. a) When V sample = 0 V, V grid = -80 V and V collector = -30 V, BSEs escaping from the sample with 60 ev cannot overcome the potential barrier between the sample and grid and are deflected back to the sample. b) When V sample = 0 V, V grid = -80 V and V collector = -30 V, BSEs escaping from the sample with 90 ev can overcome the potential barrier between the sample and grid and will reach the collector. After the measurement is completed, the SE energy distribution is determined as follows: 1) The raw data consists of the six measured current (I collector, I grid and I sample obtained during step 3 and step 4 in the measurement protocol) as a function of time (bias settings). The background currents (during which the beam was blanked) are subtracted from their corresponding current measurement during PE exposure. 55

56 2) After subtracting the background, the PE current is calculated by taking the sum of the collector current, grid current and sample current: I^_^`a = I b_a + I cde + I f`> (17) 3) Averaging for every voltage setting over their measurement time leads to three current signals I C, I G, I S, I PE as a function of V grid. 4) The collector current is used to calculate the electron (TE) yield at the collector: Electron yield = I K I =< (18) 5) By differentiating the electron yield with respect to the absolute grid voltage (the electron energy), we obtain the SE energy distribution: SE energy distribution = d de Electron yield (19) 7.2 Gold Figure 7.2 shows the raw SE energy distribution measurement data of a gold sample in the SEED analyzer. The graph shows the collector current I collector (blue), grid current I grid (red) and sample current I sample (yellow) as a function of time during PE exposure and during a background measurement. Throughout the measurement, the grid voltage is varied from -100 V to +10 V, while the collector voltage is varied from -50 V to +60 V. This explains the increasing current signal of the grid and collector till ~800 seconds. The sample remains at 0 V during the whole measurement, but the sample current decreases as a function of time. This points out that, as the grid voltage and collector voltage increase, more electrons (SEs and BSEs) are escaping from the sample and travel towards the collector. The measurement time for every bias voltage setting is 20 seconds, causing the stabilization of the current signals every 20 seconds. The background currents of the collector, grid and sample are all relatively small compared to the measured current during PE exposure. After 800 seconds, the grid voltage and collector voltage are both positive and all SEs and BSEs are attracted to the collector. 56

57 Figure 7.2: The raw current signals of the collector, grid and sample as a function of time during a SE energy distribution measurement on a gold sample. The measured currents during PE beam exposure and during background measurement are plotted separately. As a function of time, the grid voltage and collector voltage are increased, which explains the increasing current signals of the grid and collector. The decreasing sample current can be explained due to the fact that more electrons are emitted by the sample and overcome the potential barrier between the sample and grid as it becomes smaller as a function of time. Next, the background current measurements are subtracted from the corresponding current measurements during PE beam exposure. This step corrects for the background signal coming from the source meters and the electrical circuit. The sum of the three currents equals to the PE current. Averaging the resulting current signals over the measurement time per voltage bias setting (20 seconds), results in the average collector current, average grid current, average sample current and average total current as a function of the grid voltage, shown in figure 7.3. The graph illustrates the behavior of the SEs and BSEs more clearly than the raw data. The absolute value of the grid bias voltage represents the minimum energy of the electrons escaping from the sample and overcoming the potential barrier between the sample and grid. It can be seen that the sample current, remaining at 0 V during the whole measurement, starts out positive and decreases as a function of the grid voltage. This illustrates that more electrons are escaping from the sample and are overcoming the potential barrier between the sample and grid as the potential difference becomes smaller. When the grid voltage becomes positive, the sample current becomes negative, which means that more electrons are escaping from the sample (and attracted to the grid) than coming in. The grid current is negative for negative bias voltages till -5 V and then becomes positive, indicating that, from -5 V and on, a fraction of electrons escaping from the sample are entering the grid. The number of electrons measured at the grid increases as more electrons escape from the sample, which explains the increasing grid current. The collector current increases as a function of the grid voltage, because more electrons overcome the potential barrier between sample and grid as the grid voltage increases. These electrons are then accelerated from the grid to the collector. The fact that the collector current increases faster than the sample current is decreasing, indicates that there are electrons emitted by the grid and attracted to the collector, as observed in the SE yield measurements. 57

58 Figure 7.3: The collector current (blue), grid current (red), sample current (yellow) and total (PE) current (sum of the three) (purple), after subtracting the background signal and averaging, as a function of the grid voltage for a gold sample. During the measurement, the bias voltage on the grid is varied from -100 V to + 10 V, the bias voltage of the collector is varied with +50 V with respect to the grid and the sample remains at 0 V. The decreasing sample current and increasing collector current show that more electrons are escaping from the sample towards the collector/grid as the potential difference the between sample and grid becomes smaller. With the average currents for collector, grid and sample, after being corrected for the background signal, we can determine the SE energy distribution. First, we calculate the electron yield at the collector according to equation 18. By differentiating the electron yield with respect to the absolute grid voltage (the electron energy), we obtain the SE energy distribution for gold (see equation 19), shown in figure 7.4. The graph shows the relative number of electrons as a function of their energy. It can be seen that most electrons have an energy below 10 ev, which is in agreement with figure 2.3. The data is fitted with the Gaussian function with logarithmic argument (equation 7), proposed by Scholtz et al. [10], as mentioned in Chapter 2. As a reference, the fit of the experimental data obtained by Scholtz et al. is also plotted in the graph with the reference fit parameters. The fit parameters are listed in table 7.1. The shape of the curves is similar, but it can be seen that there is a mismatch between the data measured with the SEED analyzer and the experimental reference data at low electron energies. The SE energy distribution we obtained is lower than the reference data between 4 ev and 60 ev. This discrepancy hints at an inaccuracy in the energy selection of electrons emitted by the sample, due to lack of a field-free region between the sample and grid. We discuss this in more detail in section 7.3, after we have presented the SE energy distribution data for glassy carbon. The loss of BSEs (and a small fraction of SEs) through the opening of the SEED analyzer, as discussed in section 6.4.1, can also be considered as part of the cause of the mismatch. Although it is expected that this has a smaller effect than the lack of a field-free region. In addition to the comparison with experimental reference data, we also compare our data for gold with a Monte Carlo simulation of the SE energy distribution. The simulation was performed using the same simulation package as for the Monte Carlo simulations of the SE yields shown in chapter 6. The simulation shown in figure 7.4 is 58

59 normalized, just like the data that we obtained. The graph shows an even larger deviation, compared to the reference data, between the simulation and the data that we obtained. In addition to the lack of a field-free region between sample and grid, this deviation can be explained by the fact that the simulation considers an ideal experiment and does not consider effects like loss of electrons, surface contamination, surface roughness, etcetera. Figure 7.4: The SE energy distribution of gold for a PE energy of 1 kev. The experimental data that we obtained with the SEED analyzer has been fitted with equation 7 (see fit parameters in table 7.1). A plot of the fit used for reference data obtained by Scholtz et al. [10] and a Monte Carlo simulation are also shown. The discrepancy between the reference curves and our data can be explained due to the fact that there was no field-free region between the sample and grid during the measurement. Table 7.1: Fit parameters for the SE energy distribution of gold and the literature reference data, presented in figure 7.4. C is the normalization constant, E 0 the position of the maximum and τ the standard deviation of a Gaussian distribution. Parameter Value for data Value in reference C E 0 (ev) τ (ev)

60 7.3 Glassy carbon A SE energy distribution measurement was also performed for glassy carbon according to the measurement protocol described in section 7.1. Figure 7.5 displays the raw measurement data at 1 kev PE energy. The graph shows the collector current I collector (blue), grid current I grid (red) and sample current I sample (yellow) as a function of time during PE exposure and during a background measurement separately. Again, the grid voltage is increased from -100 V to +10 V, while the collector voltage is varied from -50 V to +60 V. This explains the increasing current signal for the grid and collector. The decreasing current of the sample, which remains at 0 V during the measurement, can be explained due to the fact that more electrons (SEs and BSEs) are emitted by the sample and overcome the potential barrier between sample and grid as it becomes smaller as a function of time. Compared to the background current of the collector and sample, the grid current has a relatively large background signal, revealing a leakage current in the electrical circuit of the grid. This was not the case in the previous measurement on gold (see figure 7.2). Figure 7.5: The raw current signals of the collector (blue), grid (red) and sample (yellow) during a SE energy distribution measurement on a glassy carbon sample as a function of time PE energy 1 kev. The measured currents during PE beam exposure and during background measurement are plotted separately. As a function of time, the grid voltage and collector voltage are increased, which explains their increasing current signal. The decreasing sample current can be explained due to the fact that more electrons are emitted by the sample and overcome the potential barrier between sample and grid as it becomes smaller as a function of time. The large background current for the grid is an indication of a leakage current flowing through the electrical circuit. The following step in obtaining the SE energy distribution for glassy carbon is the subtraction of the background signal from the measured current during PE exposure and averaging the resulting current data. The sum of the collector current, grid current and sample current, after subtracting the background signal, is equivalent to the PE current and is also averaged per grid bias voltage. Figure 7.6 shows the average collector current, grid current, sample current and primary current as a function of the grid voltage. The grid current exhibits Ohmic behavior 60

61 between -100 V and -5 V, which is a clear indication for a leakage current. Subtracting the background current from the current signal measured during PE exposure, has not corrected for the background signal. This also affects the total (PE) current. A closer look at the background signal is presented in section The sample current and collector current do demonstrate what we expect, which is a decrease in sample current and increase in the collector current below 20 ev. This illustrates that the electrons, emitted by the sample, are overcoming the potential barrier between the sample and grid as the bias voltage on the grid increases and the potential barrier becomes smaller. After overcoming the potential barrier, the SEs and BSEs are accelerated to the collector. Figure 7.6: The collector current (blue), grid current (red), sample current (yellow) and PE current (sum of the three) (purple), after subtracting the background signal and averaging, as a function of the grid voltage for a glassy carbon sample. During the measurement, the bias voltage on the grid is varied from -100 V to + 10 V, the bias voltage of the collector is varied with +50 V with respect to the grid and the sample remains at 0 V. The decreasing sample current and increasing collector current show that more electrons are escaping from the sample towards the collector/grid as the potential difference the between sample and grid becomes smaller. The Ohmic behavior of the grid current indicates that there is a leakage current flowing. With the average currents for collector, grid and sample, after being corrected for the background signal, we can determine the SE energy distribution of glassy carbon. First, we calculate the electron yield at the collector, using equation 18. Then, the SE energy distribution is obtained by differentiating the electron yield with respect to the absolute grid voltage, using equation 19. The result is shown in figure 7.4. The graph shows the relative number of electrons as a function of their energy. We see that most SEs have an energy below 10 ev, which is in agreement with figure 2.3. Again, the data is fitted with the Gaussian function with logarithmic argument (equation 7), which indicates that our data is in agreement with theory. The fit parameters are listed in table

62 The data is also compared with a Monte Carlo simulation of the SE energy distribution for glassy carbon. The simulation is normalized, but shows a large discrepancy with our experimentally obtained data. It is possible that the simulation package is just not reliable for glassy carbon. In addition, we applied a correction to the fit of our experimental data as a rough indication of how the SE energy distribution should look like. This was done by compensating for the electrons with sufficient energy to overcome the potential barrier, but are deflected due to the lack a field-free region. From the discrepancy between our experimental data and the literature reference data for gold, shown in figure 7.4, we calculate correction factors by taking the ratio of the fit for the experimental data and the literature reference fit. This results in an array of correction factors as a function of SE energy. Multiplying the fit of the experimental data with the correction factor array leads to a correction fit, also shown in figure 7.7. The consequence of the lack of a field-free region on the electrons that escape from the sample, is explained in more detail in section 7.4. Figure 7.7: The SE energy distribution of glassy carbon for a PE energy of 1 kev. Our experimental data has been fitted with equation 7 (see fit parameters in table 7.1). A plot of the fit used for reference data obtained by Scholtz et al. [10] and a Monte Carlo simulation are also shown. The discrepancy between the reference curves and our data can be explained due to the fact that there was no field-free region between the sample and grid during the measurement. Table 7.2: Fit parameters for the SE energy distribution of glassy carbon, presented in figure 7.7. C is the normalization constant, E 0 the position of the maximum and τ the standard deviation of a Gaussian distribution. Parameter Value for data C E 0 (ev) 0.9 τ (ev)

63 7.4 Systematic measurement errors The results for the SE energy distribution measurements of gold and glassy carbon show some unexpected features caused by systematic errors. In addition to the loss of backscattered electrons through the SEED analyzer s opening (discussed in section 6.4.1), the two main problems during the measurements were the lack of a field-free region between the sample and the grid and a leakage current during the measurements on glassy carbon. In this section we discuss the effect of these two errors in more detail No field-free region The difference between the SE energy distributions that we obtained with the SEED analyzer and the reference data, can be partially explained on the basis of the measurement protocol described in section 7.1. During the measurements, the bias voltage on the grid is varied, while the bias voltage on the sample remains 0 V. This means that there is no field-free region between the grid and the sample, causing electrons to deflect within that region and inhibiting them to reach the collector. The effect is more pronounced when the electric field between the grid and the sample holder is stronger. There is also a 50 V bias between the grid and collector to suppress the effect of SE emission from the collector. Unfortunately, now we realize that this induces an energydependent electric field strength above the sample, which impairs the SEED analyzer s sensitivity. As an example, the problem is illustrated in figure 7.8, where a simulation of the electron trajectories is shown at a certain bias voltage setting during a SE energy distribution measurement. SEs with an energy of 2 ev are escaping from the sample, while the bias voltage on the sample is 0 V, the bias on the grid is -2 V and the bias on the collector is +48 V. Ideally, in this situation all SEs with an energy of 2 ev (and higher) should be able to overcome the potential barrier between sample and grid and reach the collector. However, since not all SEs follow a trajectory perpendicular to the grid, they are deflected and will not reach the collector. As a result, the the derivative of the electron yield (the SE energy distribution) ends up being lower than it should be. This systematic error occurred during the measurement for both gold and glassy carbon. Figure 7.8: COMSOL simulation of a primary electron beam with energy 1 kev coming in and generating 2 ev electrons at the sample. V sample = 0 V, V grid = -2 V, V collector = +48 V. The simulation shows that a significant number of electrons with 2 ev energy are deflected between the grid and the sample holder and are not reaching the collector. This results in a SE energy distribution curve lower than the reference data, because there are less electrons measured at the collector within that energy range. 63

64 7.4.2 Current leakage A second problem that occurred only during the measurement on glassy carbon, is the relatively high background current flowing through the electrical circuit of the grid. Figure 7.9 shows the background currents of the collector, grid and sample, averaged, during a measurement on glassy carbon where the PE beam was blanked. During the measurement, the grid voltage is varied from -100 V to +10 V, while the collector voltage is varied from -50 V to +60 V. The sample remains at 0 V, which explains the flat line. The graph reveals that the (absolute) grid current is much larger than the collector current. It can be deduced that the grid current experiences a resistance of 22 GΩ, while the resistance for the collector is 200 GΩ. The large difference in resistance cannot be explained by the different material resistivity s and indicates that there is a current leakage flowing. In figure 7.10 we also plotted the background currents as a function of the grid voltage for the SE energy distribution measurement on gold. The graph displays the current range of the background measurements that we also would expect for the measurement on glassy carbon. It can be seen that the resistance for the grid current is 625 GΩ, which is more than 28 times larger than the background current obtained during the SE energy distribution measurement on glassy carbon. For clarification: the SE yield measurement and SE energy distribution measurement were done subsequently per material, first for gold and second for glassy carbon. Since this error started occurring after the measurements on the gold sample were finished, but recurred during multiple measurements on glassy carbon, we consider it as a systematic error. Figure 7.9: The background currents of the collector, grid and sample, during SE energy distribution measurements on a glassy carbon sample, as a function of the bias voltage on the grid. During this measurement the voltage on the grid was varied from -100 V to +10 V, the voltage on the collector from -50 V to + 60 V and the sample remained at 0 V. It can be seen that the grid current experienced a much smaller resistance than the collector, indicating that a leakage current is flowing. 64

65 Figure 7.10: The background currents of the collector, grid and sample, during SE energy distribution measurements on a gold sample, as a function of the bias voltage on the grid. During this measurement the voltage on the grid was varied from -100 V to +10 V, the voltage on the collector from -50 V to + 60 V and the sample remained at 0 V. The graph displays the range of currents that is expected for background measurements. It can be seen that the grid current experiences a much larger resistance compared to the grid current shown in figure

66 Chapter 8. Conclusion & outlook 8.1 Conclusion SE energy distribution measurements were performed for both gold and glassy carbon at a primary electron energy of 1 kev. The most important conclusion from the results obtained with the SEED analyzer, is that it is possible to filter electrons on their kinetic energy. Hence, the SEED analyzer and its working principle, presented in this thesis, can be used to perform SE energy distribution measurements. The shape of the SE energy distribution curves that we obtained for gold and glassy carbon are both similar to experimental reference data and the theory. However, the performed experiments suffer from a mismatch with the reference data. The difference in the results between our data and the SE energy distribution of gold, reported in literature, can be explained by four errors that occur during the measurements. 1. The lack of a field-free region between the grid and the sample during measurements causes a deflection of electrons between the grid and sample and inhibits a significant number of electrons from reaching the collector. As a result, the SE energy distribution curve lies lower than expected. 2. Another inaccuracy in the data that we obtained, is caused by a large leakage current flowing through the electrical circuit of the grid. Subtracting the background signal from the current measurement during PE exposure did not correct for this error. This affected the total (primary) current that we use to determine the SE energy distribution. Consequently, we suspect that this also lowers the SE energy distribution. 3. From the SE yield measurements performed on gold and glassy carbon, it appeared that (a fraction of) BSEs are escaping through the opening of the SEED analyzer during measurements. This error has a large effect on the SE yield measurements and a smaller effect on the SE energy distribution measurements. 4. The data of the SE yield measurements and SE energy distribution measurements shows that there are SEs generated at the grid by BSEs escaping from the sample. These SEs travel towards the collector or the sample, depending on the bias voltage setting of the specific measurement. This is a small effect but affects the resulting SE yield and SE energy distribution measurements. We are confident that stopping the current leakage and preventing the electrons, escaping from the sample during PE exposure, to deflect between the sample and grid, will lead to accurate SE energy distribution measurements with the SEED analyzer. Once the leakage current is minimized to a reasonable value, it is possible to correct for the SE emission at the grid. The experimental measurements of the SE yield from both gold and glassy carbon targets are in agreement with literature, even though the reference data exhibits a large spread. The measured BSE yield was lower than reported in literature, but by estimating the effect of the systematic errors that occurred during the measurements, the deviation could be explained. We concluded that the SEED analyzer functions properly during SE yield measurements within an estimated error margin of 12%. 8.2 Outlook To complete the development of TNO s EUV power sensor, some additional experiments regarding the properties of glassy carbon and its suitability as target material have to be performed. An EUV sensor is used to control the dose, to monitor the transmission of the optical path and used for the detection of change in EUV source performance. A suitable EUV sensor needs to fulfill the following requirements [1]: Robustness to EUV radiation doses and aggressive environments. High spatially uniform responsivity to 13.5 nm radiation that remains unchanged over time. Low noise, i.e. low dark current, to achieve good electrical performance. 66

67 To meet these requirements, it is necessary to obtain the SE energy distribution of glassy carbon with EUV photons to check what potential difference suffices to suppress the electron signal from OoB photons. For the application of an EUV power sensor, it is also necessary to investigate if the signal response of glassy carbon remains constant over time and to test the robustness in a H 2 gas environment Follow-up experiments As mentioned in the first chapter, it is necessary to perform a SE energy distribution with EUV photons in order to investigate what potential difference suffices to suppress the signal from OoB photons. As a first step, a synchrotron can be used to measure the energy distribution of SEs only induced by in-band EUV photons (13.5 nm). Once this test has been completed, it is also of interest to repeat a SE energy distribution measurement with an EUV radiation source that is typically used in ASML s EUV lithography machines. By comparing the SE energy distributions for the two radiation sources, we can conclude if it is possible set a threshold potential barrier to suppress SEs induced by out-of-band photons. Finally, repeating these tests in a H 2 gas environment, similar to the cleaning mode of an EUV lithography machine, shall prove if glassy carbon is robust enough and will not significantly degrade in this condition. A more detailed investigation on glassy carbon is also necessary to verify if it is a suitable target material for TNO s EUV power sensor. An experiment where the effect of carbon contamination on the SE yield is investigated would indicate if this material is indeed carbon contamination tolerant. One way to carry out this experiment is to perform two SE yield measurements on a glassy carbon sample. The first measurement is on a clean sample. The second measurement is on a glassy carbon sample after e-beam induced carbon deposition. If the SE yield is the same for both measurements, then glassy carbon is a suitable target material for the EUV power sensor New measurement protocol for SE energy distribution measurements To perform more accurate SE energy distribution measurements, it is desired to have a field-free region between the grid and the sample. A way to achieve this, is by applying the same voltage on sample and grid and vary the bias voltage on the sample along with the grid voltage. This would mean that the primary electron landing energy also varies during the measurements, but as was mentioned in chapter 2, the shape of the SE energy distribution curve does not depend on the primary electron energy. Only the peak heights of the curve depend on the primary electron energy. Figure 8.1 shows a simulation of the electron trajectories in case of a field-free region. Primary electrons with an energy of 1 kev generate 2 ev SEs at the sample. Since the bias voltages on the sample and grid are equal, -2 V, there is a field-free region between the sample and grid, allowing all SEs to be measured at the collector. The disadvantage of this measurement protocol is that the bias voltage on the sample not only affects the landing energy of the PEs, but, possibly, also affects the landing trajectories of the PEs by deflecting them. 67

68 Figure 8.1: COMSOL simulation of the electron trajectories in the case of a field-free region between the grid and sample. V sample = -2 V, V grid = -2 V, V collector = +48 V. The simulation shows that SEs with an energy of 2 ev reach the collector without being deflected Improvement of the SEED analyzer s design An alternative to the adjusted measurement protocol described above, is to construct a new, improved, SEED analyzer with a second grid between the sample and the collector (see figure 8.2). The addition of a second grid allows to perform SE energy distribution measurements without varying the bias voltage on the sample and affecting the landing trajectories of PEs, while maintaining a field-free region between sample and the (first) grid. The bias voltage settings during the measurement would be as follows. The sample and grid 1 remain at 0 V, while the bias on grid 2 is varied from -100 V to + 10 V and the collector voltage is varied from +50 V to +60 V. This way, there is a field-free region between the sample and grid 1 to prevent deflection of SEs and BSEs. The selection of electrons on their energy is done between grid 1 and grid 2. The +50 V bias on the collector with respect to grid 2 prevents SEs generated at the collector to escape. To illustrate how this works, we give an example. In figure 8.3, a COMSOL simulation displays the electric potential (left) and the trajectories of SEs escaping from the sample. The sample voltage and grid 1 voltage are 0 V, the bias on grid 2 is -10 V and the bias on the collector is +40 V. In this particular case, the SEs escape with an energy of 11 ev from the sample, travel through the field-free region between the sample and grid 1 without being deflected, overcome the potential barrier between grid 1 and grid 2, and are accelerated towards the collector. Figure 8.2: New design for the SEED analyzer with a second grid added. The second grid allows for a field-free region during SE energy distribution measurements without varying the landing energy of the PEs. 68

69 Figure 8.3: A COMSOL simulation displaying the electric potential (left) and the trajectories of SEs with a certain energy during a SE energy distribution measurement. The SEs, escaping from the sample with 11 ev, travel through a field-free region between the sample and grid 1. They overcome the potential barrier of -10 V between grid 1 and grid 2 and reach the collector. 69

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71 Appendix A. Gold sample fabrication Si substrates were cleaned for 10 minutes in acetone in an ultrasonicator before it was washed in isopropanol (IPA) for 30 seconds and blow dried with a nitrogen gas. The substrates were sputtered with gold in a Leica EM ACE500. The set thickness layer was 50 nm, the pressure 2e-5 mbar, the sputter rate 0.08 nm/sec, the current 30 ma and the Ar pressure 5e-2 mbar. 71

72 Appendix B. Electron gun characterization Characterization of the Kimball Physics electron gun pointed out that the emission current was unstable over time and that it had a very long warm-up time (see figure B.1). Another disadvantage was that the spot size was relatively big compared to the opening of the SEED analyzer. Figure B.2 shows a phosphorescence screen that shows the electron beam spot size. The spot size is about 2 mm. The large spot size could cause a distortion while doing measurements if primary electrons do not enter the SEED analyzer through the hole in the collector, but land on the top of the collector. Because of these reasons, we chose to do the experiments with a different setup. Figure B.1: The emission current of the electron gun as a function of time after turning it on. The current was measured with the SEED analyzer. The source volt was V, the source current A, The focus V, the working distance 3 cm and the pressure 6.86*10-8 mbar. Figure B.2: A phosphorescence screen in place of the SEED analyzer. The screen lights up when it interacts with electrons. The spot size at this distance was about 1.5 mm. 72

73 Appendix C. Grid Figure C 1: SEM image of the opening in the collector of the SEED analyzer. It can be seen that the opening in the grid is not perfectly concentric with the opening in the collector. 73