Infrared In‐Sensor Computing Based on Flexible Photothermoelectric Tellurium Nanomesh Arrays

The inherent limitations of traditional von Neumann architectures hinder the rapid development of internet of things technologies. Beyond conventional, complementary metal-oxide-semiconductor technologies, imaging sensors integrated with near- or in-sensor computing architectures emerge as a promising solution. In this study, the multi-scale van der Waals (vdWs) interactions in 1D tellurium (Te) atomic chains are explored, leading to the deposition of a photothermoelectric (PTE) Te nanomesh on a polymeric polyimide substrate. The self-welding process enables the lateral vapor growth of a well-connected Te nanomesh with robust electrical and mechanical properties, including a PTE responsivity of ≈120 V W<sup>-1</sup> in the infrared light regime. Leveraging the PTE operation, the thermal-coupled bi-directional photoresponse is investigated to demonstrate a proof-of-principle in-sensor convolutional network for edge computing. This work presents a scalable approach for assembling functional vdWs Te nanomesh and highlights its potential applications in PTE image sensing and convolutional processing.

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Publication Details

Journal
Advanced Materials
Published
2025-03-04
DOI
https://doi.org/10.1002/adma.202419653
Citations
18
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
13.15

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article

Infrared In‐Sensor Computing Based on Flexible Photothermoelectric Tellurium Nanomesh Arrays

You Meng, Johnny Chung Yin Ho, Changyong Lan, Jiachi Liao et al.
18 citations
Advanced Materials
Advanced Memory and Neural Computing
13.15
article

Infrared In‐Sensor Computing Based on Flexible Photothermoelectric Tellurium Nanomesh Arrays

You Meng, Johnny Chung Yin Ho, Changyong Lan, Jiachi Liao, Pengshan Xie, Quan Quan, Boxiang Gao, Dong Chen, Yuxuan Zhang, Yan Yan, Ji Zeng, He Shao
article en
18 citations

Abstract

The inherent limitations of traditional von Neumann architectures hinder the rapid development of internet of things technologies. Beyond conventional, complementary metal-oxide-semiconductor technologies, imaging sensors integrated with near- or in-sensor computing architectures emerge as a promising solution. In this study, the multi-scale van der Waals (vdWs) interactions in 1D tellurium (Te) atomic chains are explored, leading to the deposition of a photothermoelectric (PTE) Te nanomesh on a polymeric polyimide substrate. The self-welding process enables the lateral vapor growth of a well-connected Te nanomesh with robust electrical and mechanical properties, including a PTE responsivity of ≈120 V W<sup>-1</sup> in the infrared light regime. Leveraging the PTE operation, the thermal-coupled bi-directional photoresponse is investigated to demonstrate a proof-of-principle in-sensor convolutional network for edge computing. This work presents a scalable approach for assembling functional vdWs Te nanomesh and highlights its potential applications in PTE image sensing and convolutional processing.

Advanced MaterialsVol. 37(15)
Kyushu University (JP), University of Electronic Science and Technology of China (CN), Hunan University (CN), City University of Hong Kong (HK), Changsha University (CN), National Engineering Research Center of Electromagnetic Radiation Control Materials (CN)
City University of Hong Kong, National Natural Science Foundation of China
Openalex Percentile: Top 1%
Advanced Memory and Neural Computing
13.15
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