Related Experiment Video
Updated: Feb 26, 2026
08:07
Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes
Published on: March 9, 2019
8.4K
Sustainable All-Inorganic Double Perovskite Memristors Enabling Synaptic Learning and Cognitive Emulation
Jnanaprakash Dash1, Sandaap Sathyanarayana1, Muhammed Sahad E1
1eNDR Laboratory, School of Physics, IISER Thiruvananthapuram, Trivandrum, Kerala, India.
Small (Weinheim an Der Bergstrasse, Germany)
|February 25, 2026
Summary
We developed a lead-free perovskite memristive device using Cs2AgBiBr6 (CABB) for sustainable electronics. This eco-friendly material demonstrates reliable resistive switching and emulates synaptic functions for brain-inspired computing.
Area of Science:
- Materials Science
- Solid-State Physics
- Neuro-inspired Computing
Background:
- Lead-free halide perovskites are crucial for sustainable next-generation electronics and neuromorphic applications.
- Cs2AgBiBr6 (CABB) is a stable, non-toxic, all-inorganic double perovskite with potential for advanced device fabrication.
- Memristive devices are key components for energy-efficient computing and artificial intelligence hardware.
Purpose of the Study:
- To fabricate and characterize a memristive device using Cs2AgBiBr6 (CABB) thin films.
- To investigate the resistive switching mechanism and synaptic emulation capabilities of CABB-based devices.
- To evaluate the potential of CABB for neuromorphic computing and cognitive applications.
Main Methods:
- Thin-film deposition of Cs2AgBiBr6 (CABB) via cooling-induced crystallization.
- Fabrication of ITO/CABB/Au memristive structures.
- Electrical characterization including I-V measurements, impedance spectroscopy, and scanning tunneling spectroscopy (STS).
- Evaluation of synaptic behaviors (e.g., EPSC, PPD, LTP/LTD) and pattern recognition using spiking neural networks.
Main Results:
- Reproducible analog resistive switching with well-defined hysteresis observed in ITO/CABB/Au devices.
- Filamentary switching mechanism confirmed, driven by reversible Ag+ ion migration.
- Successful emulation of essential synaptic functions and demonstration of tunable plasticity.
- High accuracy (>95%) in MNIST dataset pattern recognition using trained spiking neural networks.
- Evidence of adaptive learning and associative memory, including Pavlovian conditioning.
Conclusions:
- Cs2AgBiBr6 (CABB) is a promising, eco-friendly perovskite material for memristive applications.
- CABB-based devices exhibit reliable resistive switching and versatile neuromorphic functionalities.
- The material's multifunctionality supports the development of compact, energy-efficient, and sustainable brain-inspired hardware.
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