Two-Dimensional InSe Artificial Synapses with fJ Energy Consumption
As Moore’s Law approaches its physical limits, the traditional von Neumann architecture faces challenges, and memristors offer hope as a new type of device structure. In this study, we realized the ultralow energy consumption (1.1 fJ) artificial synapse based on 2D InSe with small effective electron mass and high electron mobility. Furthermore, we simulated the synaptic behaviors of post-tetanic potentiation, classical conditioning, spike-rate-dependent plasticity (SRDP), and Bienenstock–Cooper–Munro (BCM) learning rule. This study not only provides a simulation of synaptic behavior but also achieves edge recognition in images through an effective adjustability.
Authors
- Caihong Jia (ORCID: https://orcid.org/0000-0002-4723-9524)
- Weifeng Zhang (ORCID: https://orcid.org/0000-0002-8926-1842)
- Kun Zhang (ORCID: https://orcid.org/0000-0003-1782-6995)
- Na Xu (ORCID: https://orcid.org/0000-0001-9151-432X)
- Mengyuan Duan
Institutions
- Henan University (CN)
- Quantum (Australia) (AU)
- Henan Academy of Sciences (CN)
Publication Details
- Journal
- ACS Applied Energy Materials
- Published
- 2025-05-07
- DOI
- https://doi.org/10.1021/acsaem.4c03324
- Citations
- 5
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 3.65