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The development of low size, weight, and power (SWAP) long wave infrared (LWIR) hyperspectral imaging tools is challenging due to a need for either heterogenous integration of bandwidth limited pixels, dispersive filtering, or time varying spectral filtering (i.e. FTIR). Ideally, a high information yield, low SWAP imager should have high spatial resolution and temporal resolution as well as spectral sensitivity and require few hardware components. An imager composed of electrically tunable stacked graphene may be able to address many of these requirements. AB stacked bilayer graphene (BLG) exhibits bright exciton resonances at the 1s (P1) and 2p (P2) exciton states. These exciton resonances result in large peaks in the photocurrent, and previous works have shown that the location of these excitons can be tuned across the 10μm to 20μm spectral band by applying a vertical electric field across a gate/insulator/BLG/insulator/gate stack. An array of bilayer graphene infrared detectors can be individually gate-tuned to create a set of devices that each have a unique responsivity as a function of wavelength. Our work is the first to show via simulations based on experimentally measured, spectrally resolved bilayer graphene pixel responsivity data that complex spectral signatures can be reconstructed from 650cm-1 to 750cm-1 using fewer than 25 bilayer graphene detectors. Spectra reconstructions were performed using an Elastic Net algorithm that solves a least-squares minimization problem with additional L1 and L2 norm penalty terms. Then, we show for the first time that a single bilayer graphene pixel cooled to 80K can be used to detect the presence of atmospheric concentrations of CO2 either by direct evaluation of the pixel’s photocurrent or through the Elastic Net reconstruction technique which relies on previous characterization of the detector’s responsivity as a function of gate voltage and wavelength.
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