Suppressing endurance degradation in lead-free perovskite Cs3Bi2Br9 memristors: Grain engineering via annealing temperature and grain boundary passivation with PEG additive

Abstract

Lead-free Cs3Bi2Br9 perovskite memristors have emerged as promising candidates for nonvolatile memory and neuromorphic computing due to their environmental friendliness and stability. However, their practical applications are hindered by severe endurance degradation during repetitive resistive switching (RS) cycles, attributed to incomplete RESET of conductive filaments (CFs) at grain boundaries (GBs). Herein, we systematically investigate this degradation mechanism and propose two innovative strategies to enhance device endurance: (1) grain engineering via thermal annealing to reduce GB density and (2) GB passivation using polyethylene glycol (PEG) additives. By optimizing annealing temperatures (100–250 °C), Cs3Bi2Br9 films exhibit progressively larger grain sizes (158.6–295.2 nm), which delays high resistance state degradation by minimizing CF nucleation sites. However, residual GBs still permit partial Ag accumulation. To address this, PEG incorporation chemically passivates GBs, effectively blocking ion migration and trapping. The optimized PEG-passivated Ag/Cs3Bi2Br9:PEG/ITO memristor achieves remarkable improvements: endurance is extended from 100 to 1000 cycles, and the switching window expands from 6 to 176 times. Furthermore, the optimized device demonstrates continuous conductance modulation for multilevel storage and synaptic function emulation, enabling a 784–100–10 fully connected neural network to achieve 92.2% recognition accuracy on the MNIST dataset after 100 training epochs. This study elucidates the GB-mediated degradation mechanism and demonstrates that combining grain size optimization with GB passivation provides a universal framework for high-performance RS devices in neuromorphic computing and nonvolatile memory.