Carbon nanotube noise characterization

Harold Szu; Bassam Noaman

doi:10.1117/12.670047

17 April 2006 Carbon nanotube noise characterization

Harold Szu, Bassam Noaman

Proceedings Volume 6247, Independent Component Analyses, Wavelets, Unsupervised Smart Sensors, and Neural Networks IV; 62470S (2006) https://doi.org/10.1117/12.670047
Event: Defense and Security Symposium, 2006, Orlando (Kissimmee), Florida, United States

Abstract

Without relying on the cumbersome liquid Nitrogen coolant, necessary for the conventional mid IR (3~5 μm wavelength) cameras, we designed a new mid wave IR camera, according to biomimetic human vision 2 color receptor system. We suspended over the non-cryogenic long wave IR (HgCdTe) CCD backplane with Single Wall Carbon NanoTubes (SWNT) pixels, which have the band gap energy ε_BG ~1/d tuned at the few nanometer diameter d for the mid wave. To ascertain noise contribution, in this paper, we provided a simple derivation of frequency-dependent Einstein transport coefficient D(k) = PSD(k), based on Kubo-Green (KG) formula, which is convenient to accommodate experimental data. We conjectured a concave shape of convergence 1/k^α at α=-2 power law at optical frequency against the overly simplest 1-D noise model about 1/2 K_BT, and the ubiquitous power law 1/k^α where α=1 gave a convex shape of divergence. Our formula is based on the Cauchy distribution [1+(kd)²]^-1 derived from the Fourier Transform of the correlation of charge-carrier wave function been scattered against lattice phonons spreading over the tubular surface of the diameter d, similar to the Lorentzian line shape in molecular spectral exp(-|x|/d). According to the band gap formula of SWNT, a narrower tube of SWNT worked similarly as Field Emission Transistor (FET) can be tuned at higher optical frequencies revealing finer details of lattice spacing, a and b. Experimental determination of our proposed multiple scales responses formula remained to be confirmed.

Citation Download Citation

Harold Szu and Bassam Noaman "Carbon nanotube noise characterization", Proc. SPIE 6247, Independent Component Analyses, Wavelets, Unsupervised Smart Sensors, and Neural Networks IV, 62470S (17 April 2006); https://doi.org/10.1117/12.670047

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