Tellurium Sub-Oxides Infrared Phototransistors for Adaptive Super-Resolution Image Reconstruction.
basic_science · Level V
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- Record sourced from PubMed, PMID 41492983.
- Also identified by DOI 10.1002/adma.202521147.
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Abstract
Infrared (IR) detection using crystalline silicon or III-V compounds is commonly utilized but often challenged by bulkiness and inefficiency. With the development of autonomous driving and machine vision, there is a growing need for IR technology to incorporate compact neural architectures. In this study, IR-sensitive p-type disordered tellurium sub-oxides (TeO<sub>x</sub>) thin films are deposited via an inorganic blending strategy. By integrating a luminescent dielectric layer, synergistic charge transfer and photon-induced secondary excitation endow TeO<sub>x</sub>-based IR-visible adaptive sensors (IVAS) with broadband detection and memory capabilities. The IR-driven modulation of IVAS convolutional weights enables super-resolution image reconstruction even under suboptimal conditions. This IVAS-based system achieves a peak signal-to-noise ratio of 27.55 dB (compared to 26.85 dB conventionally), a structural similarity index measure of 0.94 (compared to 0.88 conventionally), and a 13.8% reduction in mean absolute error. These findings highlight TeO<sub>x</sub>-based IVAS as a robust and adaptive solution for IR machine vision systems.