Ordered Donor-Regulated ZnO Microwire for Ultralow-Power Artificial Synapses
Defect engineering via oxygen vacancy modulation has enabled a remarkable persistent photoconductivity effect in wide-bandgap semiconductors, spawning diverse artificial synapse architectures. However, stochastic defect distributions fundamentally limit device reproducibility and energy efficiency. Here, we advance defect engineering through an "ordered donor regulation" strategy, where Ga doping in single-crystalline ZnO microwires selectively passivates random oxygen vacancies, preserving nonvolatile memory while transforming transport from disordered defect-dominated to stable donor-regulated mode. This deterministic transition eliminates stochastic carrier-trapping kinetics, enabling precise conductance modulation at an ultralow bias of 300 μV; notably, a minimum energy consumption of 2.8 fJ per pulse is achieved at 1 mV─rivaling biological synapse efficiency. The device exhibits exceptional synaptic plasticity, characterized by a robust short-to-long-term memory transition; a nonvolatile retention time exceeding 15,000 s, as well as a 14% improvement in the paired-pulse facilitation index and an EPSC amplitude 3.3 times that of pristine ZnO. A three-layer neural network achieves 94.44% and 83.41% recognition accuracy on MNIST and Fashion-MNIST data sets, respectively. This work establishes ordered donor regulation as a paradigm for precision defect engineering in wide-bandgap semiconductor synapses, laying the material foundation for energy-efficient neuromorphic computing.
Authors
- Hai Zhu (ORCID: https://orcid.org/0000-0003-2874-5509)
- Z Chen
- Mingming Jiang (ORCID: https://orcid.org/0000-0003-1784-582X)
- Hailong Zhang (ORCID: https://orcid.org/0000-0002-8951-7094)
- Xianghu Wang (ORCID: https://orcid.org/0000-0002-7556-1051)
- Shichen Su (ORCID: https://orcid.org/0000-0001-5786-8933)
- Junxing Dong
- Lihan Li
- Rustamjon Rakhimov
- Ulugbek Erkaboev
Institutions
- Sun Yat-sen University (CN)
- Namangan State University (UZ)
- South China Normal University (CN)
- Integrated Optoelectronics (Norway) (NO)
- Shanghai Dianji University (CN)
- Namangan davlat texnika universiteti (UZ)
- Nanjing University of Aeronautics and Astronautics (CN)
Publication Details
- Journal
- Langmuir
- Published
- 2026-07-16
- DOI
- https://doi.org/10.1021/acs.langmuir.6c02747
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00