Visualized in-sensor computing

Yao Ni; Jiaqi Liu; Hong Han; Qianbo Yu; Lu Yang; Zhipeng Xu; Chengpeng Jiang; Lu Liu; Wentao Xu

doi:10.1038/s41467-024-47630-9

Visualized in-sensor computing

Nat Commun. 2024 Apr 24;15(1):3454. doi: 10.1038/s41467-024-47630-9.

Authors

Yao Ni^#^{1

2}, Jiaqi Liu^#^{1

2}, Hong Han^#^{1

2}, Qianbo Yu^{1

2}, Lu Yang^{1

2}, Zhipeng Xu^{1

2}, Chengpeng Jiang^{1

2}, Lu Liu^{1

2}, Wentao Xu^{3

4}

Affiliations

¹ Institute of Optoelectronic Thin Film Devices and Technology, Key Laboratory of Optoelectronic Thin Film Devices and Technology of Tianjin, College of Electronic Information and Optical Engineering, National Institute for Advanced Materials, Nankai University, Tianjin, 300350, China.
² Shenzhen Research Institute of Nankai University, Shenzhen, 518000, China.
³ Institute of Optoelectronic Thin Film Devices and Technology, Key Laboratory of Optoelectronic Thin Film Devices and Technology of Tianjin, College of Electronic Information and Optical Engineering, National Institute for Advanced Materials, Nankai University, Tianjin, 300350, China. [email protected].
⁴ Shenzhen Research Institute of Nankai University, Shenzhen, 518000, China. [email protected].

^# Contributed equally.

Abstract

In artificial nervous systems, conductivity changes indicate synaptic weight updates, but they provide limited information compared to living organisms. We present the pioneering design and production of an electrochromic neuromorphic transistor employing color updates to represent synaptic weight for in-sensor computing. Here, we engineer a specialized mechanism for adaptively regulating ion doping through an ion-exchange membrane, enabling precise control over color-coded synaptic weight, an unprecedented achievement. The electrochromic neuromorphic transistor not only enhances electrochromatic capabilities for hardware coding but also establishes a visualized pattern-recognition network. Integrating the electrochromic neuromorphic transistor with an artificial whisker, we simulate a bionic reflex system inspired by the longicorn beetle, achieving real-time visualization of signal flow within the reflex arc in response to environmental stimuli. This research holds promise in extending the biomimetic coding paradigm and advancing the development of bio-hybrid interfaces, particularly in incorporating color-based expressions.

Publication types

Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

Animals
Biomimetics / instrumentation
Biomimetics / methods
Bionics / instrumentation
Bionics / methods
Coleoptera* / physiology
Color
Neural Networks, Computer
Synapses / physiology
Transistors, Electronic
Vibrissae / physiology