Bio-Inspired Edge Intelligence: Pathways to Ultra-Low Energy Perovskite Synaptic Devices
Journal
ACS Energy Letters
Journal Volume
11
Journal Issue
8
Start Page
5267
End Page
5274
ISSN
2380-8195
Date Issued
2026-08-14
Author(s)
Abstract
Metal halide perovskites, with their unique mixed ionic-electronic conductivity, offer a viable solution for neuromorphic hardware to break through the “energy consumption barrier” and overcome the von Neumann bottleneck. This perspective highlights strategic approaches for achieving ultralow power consumption in perovskite-based artificial synapses, summarizing relevant advancements around three key technological pillars: composition and dimension engineering, the construction of single-crystal structures, and the combined application of nanocrystal dynamics and surface passivation techniques. Furthermore, it explores the emerging trend toward Sn-based and Pb−Sn hybrid systems, as well as the ongoing optimization of three-terminal synaptic transistors, identifying these as key development directions for next-generation hardware. Overall, these strategies lay the foundation for building autonomous, energy-efficient in-sensor computing architectures, bringing edge computing progressively closer to biological-level energy efficiency.
Publisher
American Chemical Society (ACS)
Type
review article