FIG. 8.4 (a) Schematic of a self-leveling capacitive VOC sensor. (b) SEM image of the self-leveling sensor (i) 450 µm long device with PDMS polymer and (ii) magnified image of the suspended top electrode of the device with etch holes (i) Reproduced with permission from Likhite et al., Sens. Actuators B Chem. 311 , 127817 (2020). Copyright 2020 Elsevier. (c) SEM images of AlGaN/GaN heterostructure based dual channel MC heater design [(i) and (ii)] SEM images of a monolithic tip dual channel MC heater. The sensor and heater channels are visible in (ii). (iii) and (iv) Split tip dual channel MC heater with sensor and heater channels marked in (iv). Reproduced with permission from Jahangir and Koley, Sci. Rep. 6 , 28735 (2016). Copyright 2020 Author(s), licensed under a Creative Commons Attribution 3.0 Unported License. (d) Graphene membrane resonators (i) angled SEM image of suspended graphene membranes over fabricated trenches in SiO₂. (ii) Angled SEM of an array of graphene membranes. (iii) Optical image of a large array of graphene membranes. Reprinted with permission from van der Zande et al., Nano Lett. 10 (12), 4869–4873 ( 2010 ). Copyright 2010 American Chemical Society. More about this image found in (a) Schematic of a self-leveling capacitive VOC sensor. (b) SEM image of th...

FIG. 2.8 (a) Thermal expansion coefficient of monoatomic two-dimensional honeycomb lattices of graphene, silicene, germanene, and phosphorene and (b) strain-dependent phonon frequency of GaSe. Reproduced with permission from Ge et al., Phys. Rev. B 94 , 165433 (2016). Copyright 2016 American Physical Society; and Longuinhos and Ribeiro-Soares, Phys. Rev. Appl. 11 , 024012 (2019). Copyright 2019 American Physical Society. More about this image found in (a) Thermal expansion coefficient of monoatomic two-dimensional honeycomb l...

FIG. 2.14 Plot showing the two tight-binding bands of graphene in the first BZ. The two bands touch at six points. In the vicinity of those points, the bands are linearly dispersing bearing signatures of (pseudo-)relativistic physics. More about this image found in Plot showing the two tight-binding bands of graphene in the first BZ. The t...

FIG. 2.16 Geometry of a zigzag graphene nanoribbon is shown. The white and the red circles represent A and B sublattices respectively. (m, n) denote the unit cell index in x and y) directions. More about this image found in Geometry of a zigzag graphene nanoribbon is shown. The white and the red ci...

FIG. 2.17 The Hofstadter butterfly is shown for graphene. The fractal structure as a function of the external flux (scaled by the flux quantum), that is, Φ/Φ₀ can be seen. More about this image found in The Hofstadter butterfly is shown for graphene. The fractal structure as a ...

FIG. 2.18 Plot showing the Landau levels in graphene for different indices, n. More about this image found in Plot showing the Landau levels in graphene for different indices, n...

FIG. 2.20 Plot showing the Landau levels in graphene for different values of flux, ϕ. The values of the fluxes are ϕ = Φ 0 100 (for left upper panel), ϕ = Φ 0 200 (for right upper panel), ϕ = Φ 0 500 (for left lower panel) and ϕ = Φ 0 1600 (for right lower panel). Here Φ 0 = h e is the flux quantum. More about this image found in Plot showing the Landau levels in graphene for different values of flux, ...

FIG. 2.22 Plot of the scanning tunneling spectra ( d I d V ) for graphene. (a) shows spectra at zero field taken in the regions “A” and “B” marked by squares in (b). A single-layer graphene is shown by the black curve, which vanishes at zero voltage. The spectra for graphite is shown for comparison. (b) shows the map of d I d V at energy as marked by arrows in (a). d I d V vanishes in the dark region, but is finite in the bright region. (c) shows the field dependence of the tunneling spectra in the region “A.” The peaks are labeled with LL index n. In (d) the energies of the Landau levels showing a square-root dependence on the level index, n (that is, n ) and for a few distinct field values. The symbols correspond to the peaks in (c). The figure is taken from Li et al. (2009) . More about this image found in Plot of the scanning tunneling spectra ( d I d V ) for graphen...

FIG. 2.2 Optical image of one to nine layers of graphene deposited on the SiO₂/Si substrate, (a)–(f) graphene with N > 10, and thickness increases from (a)–(f). Reprinted with permission from Ni et al., Nano Lett. 7 , 2758–2763 (2007). Copyright 2007 American Chemical Society. (g) Optical image of graphene on the 72 nm Al₂O₃ film/Si substrate. (h) Calculated color bar of graphene with the number corresponding to N. (i) TCD values (experimental) of graphene calculated from RGB data. (j) Comparison of the total color difference (theoretical vs experimental) for different N from the marked positions 1–6 in (g). Reprinted with permission from Gao et al., ACS Nano 2 , 1625–1633 (2008). Copyright 2008 American Chemical Society. More about this image found in Optical image of one to nine layers of graphene deposited on the SiO₂...

FIG. 2.8 Zeta spectra for a fresh graphene—SDBS dispersion, an SDBS dispersion, and an aged (6 week old) graphene—SDBS dispersion. Inset: Zeta potential as a function of pH for SDBS—graphene dispersions. Reprinted with permission from Lotya et al., J. Am. Chem. Soc. 131 , 3611–3620 (2009). Copyright 2009 American Chemical Society. More about this image found in Zeta spectra for a fresh graphene—SDBS dispersion, an SDBS dispersion, and ...

FIG. 3.1 Raman spectroscopic image of different graphene-based structures. Reproduced with permission from J. Wu et al., Chem. Soc. Rev. 47 , 1822 (2018). Copyright 2018 Royal Society of Chemistry. More about this image found in Raman spectroscopic image of different graphene-based structures. Reprod...

FIG. 3.2 Raman spectra of graphene exhibiting significant layer number dependence. Reprinted with permission from Y. Liu et al., Nanoscale Res. Lett. 8 , 335 (2013). Copyright 2013 Springer. More about this image found in Raman spectra of graphene exhibiting significant layer number dependence. ...

FIG. 8.5 Characterization of graphene-based porous carbon nanosheets (CNSs). (a) Nitrogen adsorption/desorption isotherms and corresponding BET surface areas, (b) cumulative pore volume. Reprinted with permission from Yuan et al., Chem. Electro. Chem. 3 (5), 822–828 (2016). Copyright 2016 Wiley-VCH. (c) Representative sample adsorption isotherm, typical for hierarchical layered micro-mesoporous material constructed as a linear combination of type I (Langmuir function), II (BET function) and IV (BET + logistic function) isotherms. Reprinted with permission from Roth et al., Chem. Soc. Rev. 45 (12), 3400–3438 (2016). Copyright 2016 Royal Society of Chemistry. More about this image found in Characterization of graphene-based porous carbon nanosheets (CNSs). (a) Nit...

FIG. 8.7 Simulated N₂ adsorption isotherms for graphene materials with different layer numbers at 77 K, plotted on (a) normal and (b) logarithmic pressure scales. (c) Relative surface areas as a function of layer numbers of graphene in various BET pressure ranges. Reprinted with permission from Ohba et al., Carbon 61 , 40–46 (2013). Copyright 2013 Elsevier. More about this image found in Simulated N₂ adsorption isotherms for graphene materials with di...