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A-Site Cation Functional Engineering Enables Lead-free Perovskite Photosynapse for Neuromorphic Visual Computing

  • Xinyu Ma
  • , Zhihao Lei
  • , Beining Dong
  • , Tingting Mei
  • , Tianxu Huang
  • , Tianqi Huang
  • , Zijian Feng
  • , Xinwei Guan
  • , Fandi Chen*
  • , Tianruo Guo
  • , Mohit N. Shivdasani
  • , Long Hu*
  • , Jiabao Yi
  • , Shimul Kanti Nath*
  • , Chun Ho Lin*
  • , Dewei Chu*
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Optoelectronic synapses that directly couple light sensing with memory and computing functions offer a promising route toward energy-efficient neuromorphic vision systems. However, the development of high-performance perovskite synapses remains heavily reliant on lead-based perovskites, raising sustainability and toxicity concerns. Herein, we report a previously unexplored lead-free antimony halide perovskite, Cs2AgSb2I9, and demonstrate its application as an ultralow-power optoelectronic photosynapse, enabled by A-site cation functional engineering. Specifically, incorporation of Ag into the perovskite lattice fundamentally modulates the electronic structure, suppressing excitonic confinement, enhancing carrier transport, and introducing energetically favorable Ag interstitial states that act as reversible charge trapping/detrapping centers to enable short-term memory. As a result, Cs2AgSb2I9 devices exhibit extensive synaptic behaviors, including paired-pulse facilitation and spike-intensity-, spike-duration-, and spike-number-dependent plasticity, as well as Hebbian-like learning characteristics. Notably, the photosynapse can operate with an ultralow energy consumption of 6.18 × 10–14 J per synaptic event, approaching the energy scale of biological synapses. Artificial neural networks based on Cs2AgSb2I9 devices further demonstrate a high accuracy of 97.5% for image recognition. Overall, this work introduces a new lead-free perovskite platform and highlights A-site cation functional engineering as an effective strategy for realizing sustainable and low-power neuromorphic visual computing.

Original languageEnglish
Pages (from-to)23399-23409
Number of pages11
JournalACS Applied Materials and Interfaces
Volume18
Issue number16
DOIs
StatePublished - 29 Apr 2026

Bibliographical note

Publisher Copyright:
© 2026 American Chemical Society

Keywords

  • CsAgSbI
  • artificial synapse
  • lead-free perovskite
  • neuromorphic computing
  • optoelectronic

ASJC Scopus subject areas

  • General Materials Science

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