High Polarization‐Sensitive Synaptic Transistor Based on Perovskite Nanowire Array for Efficient Biometric Recognition
Abstract In the digital age, biometric recognition technology is highly valued and widely used in biometrics, security detection, and personalized medicine. This demands more efficient and diverse extraction methods. Traditional techniques rely on natural light, often failing to capture all necessary information and facing issues like high energy consumption and bulky design due to component separation, thus not meeting current high demands. In this paper, a polarization‐sensitive synaptic phototransistor based on perovskite nanowire is developed using nanoimprint technology, effectively integrating artificial photonic synapses with polarized light detection to enhance system integration. Notably, this device achieves a high polarization ratio of 2.2 under different polarization angles. Additionally, it features memory‐like optical synapse functionality, improving fingerprint recognition accuracy by 225% compared to natural light. This technology overcomes the limitations of traditional optical systems, meeting the needs of security, medical, and research fields to a certain extent.
Authors
- Xipeng Yu
- Huipeng Chen (ORCID: https://orcid.org/0000-0003-1706-3174)
- Gengxu Chen (ORCID: https://orcid.org/0000-0001-8064-7645)
- Rengjian Yu
- Changsong Gao
- Tao Lin (ORCID: https://orcid.org/0009-0008-3932-8173)
- Peng Zhang (ORCID: https://orcid.org/0009-0004-7146-1805)
- Peng Yang (ORCID: https://orcid.org/0009-0006-7637-7885)
Institutions
- Tan Kah Kee Innovation Laboratory (CN)
- Fuzhou University (CN)
Publication Details
- Journal
- Advanced Functional Materials
- Published
- 2024-11-21
- DOI
- https://doi.org/10.1002/adfm.202416954
- Citations
- 17
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 3.55
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Fujian Province
- National Key Research and Development Program of China