상세 보기
AlScN-based ferroelectric memristor for electrical synapse emulation and light-stimulated reservoir computing
- Park, Woohyun;
- Chae, Hyojeong;
- Park, Jeonguk;
- Kim, Seongmin;
- Park, Chanmin;
- ... Seo, Yeongkyo;
- 외 1명
WEB OF SCIENCE
1SCOPUS
1초록
In this study, we present a multifunctional indium tin oxide (ITO)/aluminum scandium nitride (AlScN)/n(+) Si ferroelectric memristor for integrated electrical-optical neuromorphic computing. The device, fabricated using radio frequency sputtering, exhibits robust ferroelectricity with an average remanent polarization of 48.46 mu C/cm(2) and stable endurance over 10(5) cycles. Electrical measurements confirm core synaptic behaviors, including potentiation and depression, with improved linearity and recognition accuracy using incremental pulse schemes. Spike-dependent plasticity modulated by pulse number, amplitude, and width is also demonstrated. In addition, the device exhibits a volatile photoresponse under 405 nm illumination conditions, enabling optically induced potentiation and depression depending on light intensity, mimicking short-term synaptic plasticity. Leveraging this dual electrical-optical modulation, we implemented a physical reservoir computing system using optically stimulated devices to process 4-bit encoded Modified National Institute of Standards and Technology inputs, achieving a classification accuracy of 96.35%. These results highlight the potential of the ITO/AlScN/n(+) Si memristor as a compact, energy-efficient platform for next-generation optoelectronic neuromorphic systems.
키워드
- 제목
- AlScN-based ferroelectric memristor for electrical synapse emulation and light-stimulated reservoir computing
- 저자
- Park, Woohyun; Chae, Hyojeong; Park, Jeonguk; Kim, Seongmin; Park, Chanmin; Seo, Yeongkyo; Kim, Sungjun
- 발행일
- 2025-12-21
- 유형
- Article
- 권
- 163
- 호
- 23