THE UNIVERSITY Chemical Analysis in the SEM Ian Jones Centre for Electron Microscopy OF BIRMINGHAM Elastic and Inelastic scattering Electron interacts with one of the orbital electrons Secondary electrons, X-rays Electron bounces off whole atom Inelastic energy is lost Elastic no loss of energy Sample-Electron Interaction Sample-Electron Interaction Electron beam Electron beam Electron beam High atomic number Monte Carlo simulation of 100 electron trajectories (E=25keV) in different materials. For SEM imaging backscattered and secondary electrons are important. Low atomic number Medium atomic number
Characteristic X-ray K α => transition from L to K Shell K β => transition from M to K Shell K γ => transition from N to K Shell L α => transition from M to L Shell L β => transition from N to L Shell Transitions Fluorescence yields Probability of a specific excited atom emitting a photon in preference to an Auger electron. E photon ~ Z 2 Fluorescence yields for K and L shells for 5 Z 110. O K Cu L Y L Ba L Intensity YBa 2 Cu 3 O 7 E 0 = 10 kev Simulated spectrum, as emitted Measurement challenges: Natural peak widths ~ 1 ev Complex spectra Complex background Poor P/B (relatively high continuum background) 0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 Photon energy (kev)
Monolithic Semiconductor Energy Dispersive X-ray Spectrometer EDX detector Fitzgerald, R, Keil, K. and Heinrich, K. Science v 159 (1968) 528 Solid-State Energy-Dispersion Spectrometer for Electron-Microprobe X-ray Analysis Liquid N2 Dewar 3 mm Gold electrode (rear) ( 0 V) Field Effect Transistor Window (FET) To pre amplifi er Si (Li) Detector Electron trap (detection crystal) -500V Collimator Woldseth, 1973 The last piece of authentic 1960s semiconductor electronics to still make a buck! (David Joy) 2005 Resolution (LN2, ~ 80 K): 129 ev at MnKα (10 mm2); 140 ev (50 mm2) Limiting count rate: ~ 2 khz (best resolution); 30 khz (resolution ~ 180 ev) A Typical EDX Spectrum Schematic of EDS detector (Reed) Schematic of EDS pulse processor (Reed) Schematic of sum peaks (Reed)
A Typical EDX Spectrum X-ray spectrum X-ray energy The first stage in quantification is to convert the EDX spectrum to numbers of characteristic x-rays. There are two approaches: Modelling Filtering The EDX units in the EM Centre use filtering. The spectrum is passed through a top hat filter, which effectively double differentiates it. This results in narrower peaks and aids deconvolution. Each peak included in your analysis is stored as a profile, along with its electronic characteristics (peak width etc). The relevant profiles are then converted to be compatible with your spectrum and fitted to it. Filtering Things under your control: Energy range of spectrum Discriminator setting (time constant) Count rate
EDS has now been replaced by SDD Peak width Sum peaks Energy Time constant Count rate Silicon Drift Detector (SDD) E. Gatti and P. Rehak, 1984 Mapping in the SEM X-rays SDDs are thin! 300 µm SDDs have a complex back surface electrode structure. SDD Backsurface Ring electrodes Resistor bridge Comment: Alumix 231 (Al14Si2.5Cu0.5Mg) Central anode, 80 µm diameter Area 5 mm 2 to 100 mm 2 The anode of an SDD is ~ 0.005 mm 2 for a 50 mm 2 detector, about 1/10,000 the area of EDS Dr MQ Chu 3 min 18 min SDD Count rate 130 kcps Electron beam WDX Detector 2dsinθ = λ Sample X-ray Analysing Crystal Schematic diagram of a WDX analysis system
How WDX works By continuously changing θ, different x-ray wavelengths can be selected in turn, and by appropriately positioning a detector, the x-ray intensity is measured as a function of wavelength. Examples Examples The ED spectrum from an alloy containing 0.15 wt% Si. The red line shows the expected peak position for Si, but it is difficult to be positive about reliable identification In the WD spectrum from the same sample as in, the improvement in peak to background ratio means there is no doubt that Si is present. ED and WD spectra from a nickel-based superalloy. The WD spectra shows the lines from W, Ta and Re clearly separated, whereas this is not the case in the ED spectrum Analysing crystals Name Formula Range λ (A) Range z (K α ) Range z (K β ) Lithium fluoride LiF 0.25 2.7 0.35 3.8 22 68 19-58 > 56 > 49 Quartz α-sio 2 0.58 6.3 15-46 > 49 PET C(CH 2 OH) 4 0.76 8.2 14-40 > 36 PbSt [CH 3 (CH 2 ) 16 CO] 2 Pb 8.7-94 5-12 20-36 Main characteristics Energy resolution: 5 ev Detection limit: Be Signal to noise ratio: 10 3 Time for analysis: long (300-3000 sec) sinθ = λ/2d
WDX Extracting the peak intensities is relatively straightforward, because the peaks are so narrow. Quantification For an element A, its concentration in wt% is N c A = specimen N N specimen A standard where A is the number of x-rays from the specimen N standard and A is the number of x-rays from the pure element standard under identical conditions. A ZAF corrections This rough first estimate is refined via five ZAF corrections: Z Backscattering Z Stopping power A Absorption F Fluorescence by characteristic x-rays F Fluorescence by Bremsstrahlung which are iterated. Notes 1. Specimens should be smooth. 2. Compound standards are OK. 3. The closer a standard s composition is to that of the specimen, the better. 4. Standards should be single phase and homogeneous. 5. Spatial resolution depends on beam voltage and Z but is likely to be a substantial fraction of a µm.
Microcalorimetry Approach to EDS X-ray E ν C Heat Capacity Thermometer Temperature G Thermal Conductance Need heat capacity C to be small: 1. Low temperature of operation 2. Small absorber volume 3. Insulators and superconductors E ν C Time C τ = G ΔE FWHM = 2.36 kt 2 C For area ~ mm 2, thickness ~ few µm ΔE FWHM ~ few ev at T = 100 mk Conventional Si(Li) EDS NIST Microcalorimeter Cryostat 1. Liquid N 2 to 77K 2. Liquid He to 4 K 3. Adiabatic demagnetization refrigerator to 100 mk JEOL 6400 SEM The end