Synergistic Pyroelectric‐Bolometric Coupling in Tellurene Nanowire for Energy‐Efficient Artificial Vision
Source abstract
Abstract
ABSTRACT Thermal–energy harvesting, which converts heat into electrical signals, offers a promising route toward sustainable energy utilization. However, achieving efficient and stable thermal–electrical conversion in low‐dimensional materials remains challenging. Although few‐layer Tellurene (Te) exhibits pyroelectricity owing to intrinsic broken symmetry, this effect is confined to the trilayer limit, ‐restricting its practical applications. Here, we demonstrate that Te nanowires (Te NWs) overcome this limitation through edge‐induced symmetry breaking, enabling robust and persistent pyroelectric polarization. Under photothermal excitation, Te NWs exhibit a synergistic pyroelectric–bolometric coupling, wherein photothermal modulation of polarization and resistance cooperatively enhances the thermally driven photocurrent. Without external bias, the device operates in a fully self‐driven mode, exhibiting excitatory synaptic responses governed solely by thermally driven charge dynamics. With biases, the response becomes bidirectional, emulating both excitatory and inhibitory synaptic characteristics. Leveraging these dual mechanisms, a Te NW‐based artificial vision system achieves 97% digit recognition accuracy through light‐driven learning without external electrical bias, demonstrating energy‐efficient, self‐stimulated neuromorphic functionality. This work establishes Te NWs as a promising material platform that bridges thermal–energy harvesting, bioinspired sensing, and self‐stimulated neuromorphic computing.
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Research context
OpenAlex topics: 2D Materials and Applications · Topological Materials and Phenomena · Advanced Thermoelectric Materials and Devices
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
SKKU Advanced Institute of Nanotechnology (SAINT) Sungkyunkwan University Suwon South Korea
Faculty of Material Science and Engineering Phenikaa School of Engineering Phenikaa University Hanoi Vietnam
Department of Electrical and Computer Engineering Sungkyunkwan University Suwon South Korea
Department of Energy Science Sungkyunkwan University Suwon South Korea
Department of Smart Fab. Technology Sungkyunkwan University Suwon South Korea
Funding
National Research Foundation of Korea
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