Graphene Based Adaptive Thermal Camouflage

Transcription

1 Supporting information for: Graphene Based Adaptive Thermal Camouflage Omer Salihoglu 1, Hasan Burkay Uzlu 1, Ozan Yakar 1, Shahnaz Aas 1, Osman Balci 1, Nurbek Kakenov 1, Sinan Balci 2, Selim Olcum 3, Sefik Süzer 4, and Coskun Kocabas 1,5 1 Bilkent University, Department of Physics, 06800, Ankara Turkey 2 Department of Photonics, Izmir Institute of Technology, Izmir, Turkey 3 Massachusetts Institute of Technology, Department of Biological Engineering Cambridge MA , 4 Bilkent University, Department of Chemistry, 06800, Ankara Turkey 5 School of Materials and National Graphene Institute, University of Manchester, Oxford Rd, Manchester, M13 9PL, UK coskun.kocabas@manchester.ac.uk Movie captions: Movie 1: Real time movie recorded by an IR camera of an operating device placed on the author s hand. The IR camera renders the thermograms assuming constant emissivity of 1. Movie 2: Real time thermal movie of a large area device placed on a hot plate at 55 C. Movie 3: Real time thermal movie of a small device placed on a hot plate at 55 C as the bias voltage varies from 0 to 3.5 V. Movie 4: Real time movie of the multipixel active thermal surface.

2 Figure S1. (a) Experimental setup used for the characterization of the active thermal surfaces. The IR camera renders the thermograms using constant emissivity. (b) The fabricated device placed on a hot plate at 55 C. (c) Thermal camera image of the device under bias voltage of 0 V.

3 Figure S2. (a) Photograph of the fabricated active thermal surface showing the flexibility of the device. The thickness of the device is around 50 µm. (b) Scanning electron microscope image of ML-graphene on polyethylene membrane.

4 Figure S3. (a) Photograph of the carbon nanotube forest grown on Si wafer used as a reference black surface with emissivity close to 1. (b) Scanning electron microscope image of the CNT forest. c, Extracted emissivity values of various materials.

5 Figure S4. (a) Thermograms of various ML-graphene samples grown at different growth temperature. The samples placed on a hot plate at 55 C. The thick samples look more metallic. (b) Apparent surface temperature of the samples varies with the thickness due to different emissivity. (c) Extracted emissivity of the samples using carbon nanotube forest as a reference black surface with emissivity of 1. (d) The variation of the sheet resistance with the growth temperature. The layer number increases with the growth temperature. Figure S5. (a) Snapshot thermograms of the device during intercalation process. (b) The time trace of the emitted thermal power as we switched the bias voltage between -2 V and 3 V. The device can be switched between high and low emissivity many times. (c-d) Normalized radiation plotted as a function of time for intercalation and de-intercalation cycles.

6 Figure S6. In situ optical characterization of the active thermal surfaces. (a) Schematic of the device used for the spectroscopic characterization of the multilayer graphene. A 5 mm-hole on the gold electrode allows us to measure reflection and transmission of the graphene electrode. This small hole allows intercalation of the free standing graphene. (b-c) Transmittance and reflectance spectra of multilayer graphene at different bias voltages. As the bias voltage increases, the transmittance is decreased by a factor of 10 at long wavelength and the modulation diminishes at 1.5 µm wavelength. On the other hand, the IR reflectivity increases significantly during the intercalation process due to the increased carrier concentration. The periodic oscillation of the reflectivity is due to the interference of 20 µm thick PE substrate soaked with room temperature ionic liquid.

7 Figure S7. Thermal radiation from a single-layer graphene device. (a) Photograph of single layer graphene on polyethylene membrane. (b) Thermogram of the sample placed on gold coated Si wafer on a hot plate at 55 C. (c) The variation of resistance of graphene with the bias voltage between graphene and back gold electrode. (d) Schematic electronic band structure of the doped graphene and the electronic transitions. Optical absorption of graphene is defined by the interband and intraband electronic transitions. Doping graphene opens an optical gap in the absorption due to Pauli blocking. Even pristine graphene has some unintentional doping (E F ~200 mev), which blocks IR absorption due to interband transitions leaving only contribution of intraband transitions. Therefore, increasing carrier concentration further leads to small enhancement (<1%) of IR absorption. (e) Calculated IR absorption of graphene at different doping level. (f) The modulation of the radiated thermal power from graphene surface with the voltage. We observed a small increase (~1.5%) in the radiated power which is associated with the increased rate of interband transitions.

8 Figure S8. (a) Electronic bad structure of doped multilayer graphene and possible electronic transitions. (b) Energy spacing between the subbands plotted against the quantized perpendicular momentum of the thin film. The number of layer and interlayer coupling defines the spacing between the sub-bands ( γ 1 =370 mev) 9. (c) Measured optical conductivity of multilayer graphene taken from Ref(24). Although single layer graphene does not yield optical conductivity at IR frequencies due to unintentional doping, multilayer graphene has significant optical conductivity over a IR broad spectrum. (d-e) Calculated absorption and reflection from multilayer graphene with layer number of 80. We used the model developed by Bao et al. 10. Dielectric consonant of ML-graphene is written as 4π ε ( ω) = ε 1+ i ε 2 = ε + i σ ( ω) where σ(ω) is the frequency dependent optical conductivity ω of multilayer graphene. σ(ω) includes contribution from Drude conductivity as e2ef N σ d = where EF is the Fermi energy, γ is the relaxation rate, and N is the number π h ( γ iω) of layers. The second contribution is from interband transitions

9 2 πe N 2EF + hω 2EF hω ( Re( σ in ) = tanh( ) tanh( 2h where k is the Boltzmann constant and 4kT 4kT T is the temperature. These calculations reveals that both blocking of interband transitions and enhancement of intraband transition due to free carries contributes to the modulation of IR absorption and emissivity. As the Fermi energy increases, IR absorption is suppressed and reflectivity is enhanced. Back Gated C1s N+ N1s F1s N V V Binding Energy (ev) Figure S9. Estimation of the ion excess within the graphene layer. C1s, F1s, and N1s regions of the intercalated thick graphene layer with the IL at +2.5 and -2.5V back gate voltages. The quantitative nature of XPS enables us to estimate the charge imbalance from the intensity ratio of the two N1s peaks, for example at +2,5 V as (N+/N- = 1.20 ± 0.05) as shown in the figure. Using the stoichiometric atomic ratio of the F/C = 0.05 derived from the intensities of the two strong C1s and F1s peaks, and the chemical formula of the IL, we get approximately 1 ionic pair for ~100 C atoms of the graphene. Hence the 0.2 excess positive charge derived from the nitrogen intensity corresponds to 1 excess positive charge for every ~500 C atoms of the graphene layer.

10 Figure S10. (a) Time varying background temperature and the adaptive variation of the apparent surface temperature. (b) Time trace of the control voltage applied to the graphene electrode to control emissivity. The maximum range of the control voltage is from -2.5 to 3.5 V.

11 Background temperature ( C) Apparent temperature ( C) Time (s) Figure S11. Time trace of background temperature and apparent surface temperature when we set large gain in the algorithm. Un-optimized gain of the feedback circuit results temperature overshoots and large oscillation around the target temperature. With this gain setting the surface can follow the background temperature with time delay of 50 s. Figure S12. (a) Photograph of carbon nanotube and gold-coated samples placed on temperature controlled stage. (b) Thermal camera images of the samples. Temperature of the stage is 46 C.

12 Figure S13. (a) Illustration of the tunable thermal radiation and reflection from a multilayer graphene surface. (b) Schematic drawing of the 5x5 arrays of multipixel active thermal surface conformally coated over a coffee cup. This device is using passive matrix addressing to define a pixel. (c-d) Reconfigurable thermal images of the coffee cup filled with hot and cold water, respectively. When we applied voltage hot surfaces looks colder and cold surfaces looks hotter.

13 Figure S14. Photograph of the multipixel thermal surface integrated on a coffee cup and the wiring to the external switch box. The switch box is connected to a source meter.

14 Table S1. Table shows the comparison of electrochromic materials used for IR emissivity control. 1-8 Material Stimulus Response time Top electrode Graphene Voltage 0.1 sec - Ionic liquid (NV) WO3 Ta2O5 NiO Powder Of Monohydrated Tungsten Oxide (WO3.H2O) Poly-crystalline WO3 in PC- WO3/ Ta2O5/Amorph ous WO3/Al Vanadium dioxide (VO2) deposited on sapphire Sputtered(RFS) WO3 thin films Voltage - Conductive grid Voltage - Conductive Al grid Voltage - Conductive Al grid Electrolyte Reflection Modulation LiClO4 in propylene carbonate (V) LiPF6 in EC/DMC (V) LiClO4 in propylene carbonate (V) Emissivity Modulation Bandwidth (µm) Thickness of active layer (nm) Flexibility Ref. 150% 50% This Study 65% % 30% % 20% Temperature % Voltage - Pt counter electrode H3PO4 (V) Polyaniline Voltage - Gold/PANI H2SO4 in PVA (V) Electrochromic /Ion Storage layer Vanadium dioxide (VO2) Voltage - Metamateria l Li salt in solid fast ion conductor (NV) 73% and 50% 18% and 40% 3-5 and % 3-5 and % % 80% Temperature % - + 8

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