Advances in Organic In‐Sensor Neuromorphic Computing: from Material Mechanisms to Applications

In‐sensor neuromorphic computing integrates sensing and processing within a single material system, enabling real‐time, ultralow‐power computation for biomedical signal analysis, artificial skin, and brain‐machine interfaces. Organic sensors, organic electrochemical transistors, and memory‐based synaptic devices serve as key components, utilizing ion–electron coupling and nonvolatile synaptic weight modulation for energy‐efficient neuromorphic functions. Reflecting the potential of the aforementioned in‐sensor computing, this review provides a comprehensive analysis of organic‐based in‐sensor computing for wearable and bioelectronic applications. It explores the design and mechanisms of organic synaptic devices, with a focus on memory‐based and organic electrochemical transistor‐based architectures. The fundamental principles of neuromorphic computing are examined, highlighting various organic neuromorphic computing devices and their operational characteristics. Through an in‐depth discussion of recent advancements, challenges, and future perspectives, this review aims to offer valuable insights into the potential of organic electronics in advancing intelligent systems.

Authors

Institutions

Publication Details

Journal
Advanced Intelligent Discovery
Published
2025-07-24
DOI
https://doi.org/10.1002/aidi.202500053
Citations
3
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
2.19

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Advances in Organic In‐Sensor Neuromorphic Computing: from Material Mechanisms to Applications

Woojo Kim, Eun Kwang Lee, Hocheon Yoo, Dong Hyun Lee
3 citations
Advanced Intelligent Discovery
Advanced Memory and Neural Computing
2.19
article

Advances in Organic In‐Sensor Neuromorphic Computing: from Material Mechanisms to Applications

Woojo Kim, Eun Kwang Lee, Hocheon Yoo, Dong Hyun Lee
article en
3 citations

Abstract

In‐sensor neuromorphic computing integrates sensing and processing within a single material system, enabling real‐time, ultralow‐power computation for biomedical signal analysis, artificial skin, and brain‐machine interfaces. Organic sensors, organic electrochemical transistors, and memory‐based synaptic devices serve as key components, utilizing ion–electron coupling and nonvolatile synaptic weight modulation for energy‐efficient neuromorphic functions. Reflecting the potential of the aforementioned in‐sensor computing, this review provides a comprehensive analysis of organic‐based in‐sensor computing for wearable and bioelectronic applications. It explores the design and mechanisms of organic synaptic devices, with a focus on memory‐based and organic electrochemical transistor‐based architectures. The fundamental principles of neuromorphic computing are examined, highlighting various organic neuromorphic computing devices and their operational characteristics. Through an in‐depth discussion of recent advancements, challenges, and future perspectives, this review aims to offer valuable insights into the potential of organic electronics in advancing intelligent systems.

Advanced Intelligent DiscoveryVol. 1(3)
University of San Diego (US), University of California San Diego (US), Hanyang University (KR), Pukyong National University (KR)
National Research Foundation, Ministry of Trade, Industry and Energy, National Research Foundation of Korea, Ministry of Science and ICT, South Korea, Institute for Information and Communications Technology Promotion
Openalex Percentile: Top 11%
Advanced Memory and Neural Computing
2.19
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Advances in Organic In‐Sensor Neuromorphic Computing: from Material Mechanisms to Applications — Woojo Kim, Eun Kwang Lee, et al. · Advanced Intelligent Discovery (2025) | TGRS Research Map | TGRS