Wafer‐Scale Organic Neuromorphic Sensors for Programmable Displaying

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Authors: Ting Jiang, Yuning Li, Zhong Chen, Tao Deng, Jiangtao Xu, Deyang Ji, Wenping Hu
Cited by: 3
References: 23

Abstract

ABSTRACT Conventional machine vision architectures suffer from intrinsic energy inefficiency and latency bottlenecks due to the physical segregation of sensing, memory, and processing units. Emerging organic neuromorphic devices offer a promising solution, yet concurrently achieving strong photoresponse, ultralow‐power operation, and reliable non‐volatile memory remains a critical challenge. Herein, we integrate a heterostructured dielectric layer, poly (amic acid) (PAA)/hafnium oxide, into wafer‐scale organic neuromorphic devices, significantly enhancing charge carrier mobility, photosensitivity, and memory performance. The optimized devices exhibit a suite of exceptional characteristics: high carrier mobility, ultralow light detection sensitivity (102 nW cm −2 ) with a fast response time (50 µs), minimal energy consumption (53 aJ per spike), long‐term memory retention (50 000 s), and robust endurance. We further demonstrate programmable organic thin‐film transistors (OTFTs) driving LED arrays, enabling repeatable light/mask‐induced pattern writing/erasing and integration of sensing‐memory‐display functions. Linear Dynamic Range Adjustment (LDRA) simulations reveal ultrahigh dynamic range and superior imaging capabilities of PAA‐optimized OTFTs. This hetero‐dielectric strategy establishes a universal platform for organic neuromorphic electronics, addressing key gaps in adaptive edge vision systems and human‐retina‐like interactive meta‐displays.

Fields of Study & Subjects

Advanced Memory and Neural Computing Organic Electronics and Photovoltaics Advanced Sensor and Energy Harvesting Materials

Publication details

Journal / source
Advanced Materials
Publisher
Wiley
Volume
38
Issue
13
Pages
e22289–e22289
Publication date
28 January 2026
Language
EN