Authors
Hongguang Zhang, Junxin Liu, Rui Shi, Wei Li, Xinran Li, Xiaoyu Hou, Yiheng Sun, Liqing Liu, Mingdong Yi, Wen Li, Yongtao Li
Published in
The journal of physical chemistry letters. Volume 17. Issue 32. Pages 9153-9163. Aug 13, 2026.
Abstract
Organic memristors have potential applications in simulating biological synapses for neuromorphic computing. In this work, a solution-processed Al/P3BT/indium tin oxide (ITO) organic memristor was designed. The device exhibits stable resistive switching behavior and successfully emulates versatile synaptic plasticity, including excitatory postsynaptic current (EPSC), paired-pulse facilitation (PPF), spike-timing-dependent plasticity (STDP), the transition from short-term plasticity to long-term potentiation (STP-LTP), post-tetanic potentiation (PTP), and experiential learning. Fitting analyses of the I-V curves reveal that the resistive switching resulted from a combined contribution of direct tunneling, space-charge-limited conduction, Schottky emission, and Fowler-Nordheim tunneling. Moreover, the analog resistive switching behavior remains stable, even after exposure to ambient air for over 300 days. To exploit the nonlinear mappings through simple 3-bit pulse sequences, the constructed reservoir computing system achieves a recognition accuracy of 97.69% on the Modified National Institute of Standards and Technology (MNIST) handwritten digit classification task after only 20 training epochs, significantly outperforming conventionally trained network models. Furthermore, the system attains an accuracy of 87.02% on the Fashion-MNIST data set. This study provides valuable insights and perspectives on the emulation of artificial synaptic plasticity by using organic memristors and their application in neuromorphic computing.
PMID:
42593305
Bibliographic data and abstract were imported from PubMed on 13 Aug 2026.
Read full publication at:
Please sign in
to see all details.
Advertisement
Stats
- Recommendations n/a n/a positive of 0 vote(s)
- Views 9
- Comments 0