A Low-Voltage Stretchable Synaptic Transistor Array for Temperature Perception, Facilitated Associative Learning, and Neuromorphic Computing

Stretchable synaptic transistors are promising candidates for brain-inspired neuromorphic systems in soft robotics and wearable electronics, where temperature perception and low-power operation are critical for biological fidelity and energy efficiency. However, the interplay between mechanical strain, temperature perception, and synaptic properties remains underexplored in such devices. Here, we report a high-density, temperature-modulated stretchable synaptic transistor (TM-SST) array fabricated via a photolithography-based, transfer-free process, integrating a semiconductor carbon nanotube (s-CNT) network channel and an SU-8 dielectric layer. The devices exhibit a high on-off ratio (∼10<sup>5</sup>) at a low gate voltage (<i>V</i><sub>gs</sub>) between ±2.5 V and a drain-to-source voltage (<i>V</i><sub>ds</sub>) of -0.1 V. Importantly, the devices exhibit temperature-dependent synaptic characteristics across 10-40 °C, with effective modulation of postsynaptic current (PSC), plasticity, memory retention, and paired-pulse facilitation (PPF), while maintaining stable performance under 40% strain. Furthermore, temperature modulation enhances neuromorphic performance: a 15 °C cooling improves memory retention in associative learning from seconds to minutes, while simulations show accelerated learning with a 10× dynamic range. This work advances stretchable synaptic devices by enabling temperature perception to enhance neuromorphic functionality.

Authors

Institutions

Publication Details

Journal
ACS Applied Materials & Interfaces
Published
2025-12-05
DOI
https://doi.org/10.1021/acsami.5c17926
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Low-Voltage Stretchable Synaptic Transistor Array for Temperature Perception, Facilitated Associative Learning, and Neuromorphic Computing

Fugu Tian, Xiangyun Liao, Qi Zheng, Dingzhou Cui et al.
ACS Applied Materials & Interfaces
Advanced Memory and Neural Computing
article

A Low-Voltage Stretchable Synaptic Transistor Array for Temperature Perception, Facilitated Associative Learning, and Neuromorphic Computing

Fugu Tian, Xiangyun Liao, Qi Zheng, Dingzhou Cui, Zhiyuan Zhao, Chongwu Zhou, Wenbo Chen, Jingxin Zhang
article en

Abstract

Stretchable synaptic transistors are promising candidates for brain-inspired neuromorphic systems in soft robotics and wearable electronics, where temperature perception and low-power operation are critical for biological fidelity and energy efficiency. However, the interplay between mechanical strain, temperature perception, and synaptic properties remains underexplored in such devices. Here, we report a high-density, temperature-modulated stretchable synaptic transistor (TM-SST) array fabricated via a photolithography-based, transfer-free process, integrating a semiconductor carbon nanotube (s-CNT) network channel and an SU-8 dielectric layer. The devices exhibit a high on-off ratio (∼10<sup>5</sup>) at a low gate voltage (<i>V</i><sub>gs</sub>) between ±2.5 V and a drain-to-source voltage (<i>V</i><sub>ds</sub>) of -0.1 V. Importantly, the devices exhibit temperature-dependent synaptic characteristics across 10-40 °C, with effective modulation of postsynaptic current (PSC), plasticity, memory retention, and paired-pulse facilitation (PPF), while maintaining stable performance under 40% strain. Furthermore, temperature modulation enhances neuromorphic performance: a 15 °C cooling improves memory retention in associative learning from seconds to minutes, while simulations show accelerated learning with a 10× dynamic range. This work advances stretchable synaptic devices by enabling temperature perception to enhance neuromorphic functionality.

ACS Applied Materials & InterfacesVol. 17(50)
University of Southern California (US), Minghsin University of Science and Technology (TW), California Southern University (US)
Openalex Percentile: Top 61%
Advanced Memory and Neural Computing
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.