Advances in perovskite-based neuromorphic computing devices

Yixin Cao, Yuanxi Li, Ganggui Zhu, Linhui Li, Guohua Lu, Eng Gee Lim*, Wenqing Liu, Yina Liu, Chun Zhao*, Zhen Wen*

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

Abstract

Neuromorphic computing devices, inspired by the architecture and functionality of the human brain, offer a promising solution to the limitations imposed by the von Neumann bottleneck on contemporary computing systems. Perovskite materials are widely used in the photosensitive layer of neuromorphic computing devices due to their high light absorption coefficient and excellent carrier mobility. Here, we summarise the latest research progress on neural morphology computing devices based on perovskite materials with different structures and summarise different application scenarios. Finally, we discussed the issues that still need to be addressed and looked forward to the future development of neural morphology calculations based on perovskite materials.

Original languageEnglish
JournalNanoscale
DOIs
Publication statusAccepted/In press - 2025

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