Mechanically Durable Intrinsically Stretchable Neuromorphic Devices via Molecular Microstructure Design
2026 · Small
저자
Kwan‐Nyeong Kim, Ho‐Eon Baek, Min‐Jun Choi, Min-Jun Sung, Seungwoo Lee, Chae-Yun Song, Hyun-Haeng Lee, Sangjun Ma, Karina Ayu Larasati, 선정윤 (Jeong‐Yun Sun), Hea‐Lim Park, Yun‐Hi Kim, Tae‐Woo Lee
연구주제
Advanced Memory and Neural Computing · Organic Electronics and Photovoltaics · Conducting polymers and applications
NTIS 과학기술표준분류
에너지/자원만에너지·환경·원자력 확장
가장 가까운 분류(전기/전자 > 반도체소자 및 시스템 > 반도체 재료)가 에너지·환경·원자력 확장 범위 밖이다.
AI 연구 키워드·방법
intrinsically stretchable semiconductor 뉴로모픽 소자 semiconducting polymer
키워드 (OpenAlex)
mechanical durability semiconducting polymers percolation network charge transport cycling stability reservoir computing wearable electronics stretchable electronics
초록
ABSTRACT Intrinsically stretchable neuromorphic devices (ISNDs) have been widely investigated for intelligent wearable on‐device computing. However, conventional material design strategies that soften the polymer conjugated moiety to impart stretchability have shown limited mechanical durability, typically 10 3 cycles at 50% strain, with severe electrical degradation. Here, we present a highly durable ISND that maintains stable electrical performance for up to 10 5 cycles at 50% strain, enabled by molecularly controlling chain stacking of the semiconducting polymer. This is achieved by incorporating a microstructure‐controlling moiety into the polymer backbone, which modulates the chain packing from a bundle‐like to a mesh‐like structure. The resulting mesh‐like morphology forms robust and long‐range percolation networks that preserve charge transport pathways and structural integrity un…
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교수 1
연구주제 1
Advanced Memory and Neural Computing