Sustainable All‐Inorganic Double Perovskite Memristors Enabling Synaptic Learning and Cognitive Emulation

Lead-free halide perovskites are emerging as sustainable alternatives for next-generation electronic and neuromorphic technologies. In this work, we present a memristive device based on cooling-induced crystallization followed by thin-film deposition of Cs<sub>2</sub>AgBiBr<sub>6</sub> (CABB), a stable, non-toxic all-inorganic double perovskite. Uniform CABB thin-film of roughness about 3.5 nm, integrated in ITO/CABB/Au structures, exhibits reproducible analog resistive switching with well-defined pinched hysteresis, validated by macroscopic I-V measurements and nanoscale c-AFM/STM-based spectroscopy results. Comprehensive structural and compositional analyses confirm phase-pure crystallization, while impedance spectroscopy and localized current mapping images with the scanning tunneling spectroscopy (STS) reveal a filamentary switching mechanism precisely driven by reversible Ag<sup>+</sup> ion migration. Beyond non-volatile memory, the devices successfully emulate essential synaptic behaviors, including excitatory postsynaptic current, paired-pulse facilitation, and long-term potentiation/depression with tunable weight states, enabling robust plasticity. Notably, pattern recognition with trained spiking neural networks yields > 95% accuracy on the MNIST dataset, surpassing practical application benchmarks. Furthermore, sequenced pulse training enables adaptive learning and associative memory, evidencing Pavlovian conditioning at the device level. This multifunctionality highlights CABB as a promising and eco-friendly perovskite material that unites reliable resistive switching, neuromorphic learning, and cognitive adaptability, paving the way toward compact, energy-efficient, and sustainable brain-inspired hardware building blocks.

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Small
Published
2026-02-25
DOI
https://doi.org/10.1002/smll.202511750
Primary Topic
Advanced Memory and Neural Computing
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article
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article

Sustainable All‐Inorganic Double Perovskite Memristors Enabling Synaptic Learning and Cognitive Emulation

Bikas C. Das, Sandaap Sathyanarayana, Saptarshi Bej, Muhammed Sahad E et al.
Small
Advanced Memory and Neural Computing
article

Sustainable All‐Inorganic Double Perovskite Memristors Enabling Synaptic Learning and Cognitive Emulation

Bikas C. Das, Sandaap Sathyanarayana, Saptarshi Bej, Muhammed Sahad E, Jnanaprakash Dash
article en

Abstract

Lead-free halide perovskites are emerging as sustainable alternatives for next-generation electronic and neuromorphic technologies. In this work, we present a memristive device based on cooling-induced crystallization followed by thin-film deposition of Cs<sub>2</sub>AgBiBr<sub>6</sub> (CABB), a stable, non-toxic all-inorganic double perovskite. Uniform CABB thin-film of roughness about 3.5 nm, integrated in ITO/CABB/Au structures, exhibits reproducible analog resistive switching with well-defined pinched hysteresis, validated by macroscopic I-V measurements and nanoscale c-AFM/STM-based spectroscopy results. Comprehensive structural and compositional analyses confirm phase-pure crystallization, while impedance spectroscopy and localized current mapping images with the scanning tunneling spectroscopy (STS) reveal a filamentary switching mechanism precisely driven by reversible Ag<sup>+</sup> ion migration. Beyond non-volatile memory, the devices successfully emulate essential synaptic behaviors, including excitatory postsynaptic current, paired-pulse facilitation, and long-term potentiation/depression with tunable weight states, enabling robust plasticity. Notably, pattern recognition with trained spiking neural networks yields > 95% accuracy on the MNIST dataset, surpassing practical application benchmarks. Furthermore, sequenced pulse training enables adaptive learning and associative memory, evidencing Pavlovian conditioning at the device level. This multifunctionality highlights CABB as a promising and eco-friendly perovskite material that unites reliable resistive switching, neuromorphic learning, and cognitive adaptability, paving the way toward compact, energy-efficient, and sustainable brain-inspired hardware building blocks.

Small
Indian Institute of Science Education and Research Thiruvananthapuram (IN)
Responsible consumption and production
Openalex Percentile: Top 45%
Advanced Memory and Neural Computing
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