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

Jiachi Liao; He Shao; Yuxuan Zhang; Yan Yan; Ji Zeng; Changyong Lan; Boxiang Gao; Dong Chen; Quan Quan; Pengshan Xie; You Meng; Johnny C. Ho

doi:10.1002/adma.202419653

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

Jiachi Liao, He Shao, Yuxuan Zhang, Yan Yan, Ji Zeng, Changyong Lan, Boxiang Gao, Dong Chen, Quan Quan, Pengshan Xie, You Meng^*, Johnny C. Ho^*

^*Corresponding author for this work

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

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⁻¹ 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. © 2025 Wiley-VCH GmbH.

Original language	English
Article number	2419653
Journal	Advanced Materials
Volume	37
Issue number	15
Online published	4 Mar 2025
DOIs	https://doi.org/10.1002/adma.202419653
Publication status	Published - 16 Apr 2025

Funding

The project was supported by the Innovation and Technology Fund (Project no. MHP/126/21) from the Innovation and Technology Commission of Hong Kong SAR, China, the National Natural Science Foundation of China (Project no. 12204248), the Research Grants Council of the Hong Kong SAR, China (Project No. CRS_CityU101/24), the Science Technology and Innovation Committee of Shenzhen Municipality (Project No. JCYJ20230807114910021), Guangdong Basic and Applied Basic Research Fund (Project no. 2024A1515011922), and City University of Hong Kong (Project no. 7006109 and 7020088).

Research Keywords

convolutional image processing
in-sensor computing
photothermoelectric detectors
tellurium nanomesh

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10.1002/adma.202419653

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@article{dc21d82602db4ed8914320aea09a368c,

title = "Infrared In-Sensor Computing Based on Flexible Photothermoelectric Tellurium Nanomesh Arrays",

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−1 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. {\textcopyright} 2025 Wiley-VCH GmbH.",

keywords = "convolutional image processing, in-sensor computing, photothermoelectric detectors, tellurium nanomesh",

author = "Jiachi Liao and He Shao and Yuxuan Zhang and Yan Yan and Ji Zeng and Changyong Lan and Boxiang Gao and Dong Chen and Quan Quan and Pengshan Xie and You Meng and Ho, {Johnny C.}",

year = "2025",

month = apr,

day = "16",

doi = "10.1002/adma.202419653",

language = "English",

volume = "37",

journal = "Advanced Materials",

issn = "0935-9648",

publisher = "Wiley-Blackwell",

number = "15",

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TY - JOUR

T1 - Infrared In-Sensor Computing Based on Flexible Photothermoelectric Tellurium Nanomesh Arrays

AU - Liao, Jiachi

AU - Shao, He

AU - Zhang, Yuxuan

AU - Yan, Yan

AU - Zeng, Ji

AU - Lan, Changyong

AU - Gao, Boxiang

AU - Chen, Dong

AU - Quan, Quan

AU - Xie, Pengshan

AU - Meng, You

AU - Ho, Johnny C.

PY - 2025/4/16

Y1 - 2025/4/16

N2 - 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−1 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. © 2025 Wiley-VCH GmbH.

AB - 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−1 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. © 2025 Wiley-VCH GmbH.

KW - convolutional image processing

KW - in-sensor computing

KW - photothermoelectric detectors

KW - tellurium nanomesh

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DO - 10.1002/adma.202419653

M3 - RGC 21 - Publication in refereed journal

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JO - Advanced Materials

JF - Advanced Materials

IS - 15

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ER -

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

Abstract

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NSFC-CRS: 1D van der Waals Atomic Chains for 3D-integrated Retinomorphic Optoelectronics

ITF: Preparation of GaSb-based Artificial Visual Synapses with Ultra-low Energy Consumption

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

Abstract

Funding

Research Keywords

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Other Access Options

Permanent Link

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Projects

NSFC-CRS: 1D van der Waals Atomic Chains for 3D-integrated Retinomorphic Optoelectronics

ITF: Preparation of GaSb-based Artificial Visual Synapses with Ultra-low Energy Consumption

Cite this