Nitrogen-doped carbon quantum dot-decorated In2O3 synaptic transistors for neuromorphic computing
Nitrogen-doped carbon quantum dots (N-CQDs) are promising materials for electronic devices due to their variable bandgap and structural stability. Here, we integrate N-CQDs into In2O3 synaptic transistors with electrolyte gating, resulting in a hybrid structure. The surface functional groups and defects of N-CQDs empower the charge trapping mechanism, permitting controlled conduction and charge regulation, which are crucial for emulating linear and symmetric artificial synaptic devices. Devices incorporating N-CQDs demonstrate enhanced stability and memory characteristics, low energy consumption, consistent retention, and a significant hysteresis window across multiple voltage cycles. Finally, the study emulates biological synapses and cognitive functions, achieving an energy consumption of 10 fJ per synaptic event and a pattern recognition accuracy of 91.2% on the MNIST dataset in hardware neural networks. This work demonstrates the potential of well-manipulating charge trapping in N-CQDs to develop high-performance, nonvolatile synaptic devices.
Authors
- Yunchao Xu (ORCID: https://orcid.org/0009-0003-7356-4325)
- Muhammad Tahir (ORCID: https://orcid.org/0000-0001-5181-1434)
- Fawad Aslam (ORCID: https://orcid.org/0000-0001-6016-6123)
- Muhammad Zahid
- Muhammad Irfan Sadiq (ORCID: https://orcid.org/0009-0003-3805-0230)
- Jia Sun (ORCID: https://orcid.org/0000-0003-4423-8128)
- Xiaofang Shi
- Chenxing Jin (ORCID: https://orcid.org/0009-0001-8035-4452)
- Wanrong Liu (ORCID: https://orcid.org/0000-0003-2054-469X)
- Junliang Yang
- Jingwen Wang (ORCID: https://orcid.org/0009-0002-6495-0884)
Institutions
- Central South University (CN)
- Hunan University (CN)
- State Key Laboratory of Transducer Technology (CN)
- Shanghai Institute of Microsystem and Information Technology (CN)
- South University (US)
Publication Details
- Journal
- Applied Physics Letters
- Published
- 2024-11-04
- DOI
- https://doi.org/10.1063/5.0231655
- Citations
- 13
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 2.71
Funders
- National Natural Science Foundation of China
- National Key Research and Development Program of China