Lead‐free inorganic halide perovskite‐based synaptic memory for next generation neuromorphic computing

Abstract Inorganic halide perovskites (IHPs) have emerged as promising materials for next‐generation synaptic memory, owing to their tunable bandgap, long charge‐carrier diffusion lengths, fast ion migration, and environmental sustainability. Their unique properties make them particularly attractive for resistive switching memory devices (RSMDs), which are increasingly being explored as artificial synaptic devices for neuromorphic computing. Pb‐free IHPs can emulate biological synapses at both electrical and optical levels, enabling low‐power, multifunctional, and highly efficient neuromorphic architectures. Their versatility enables multimodal sensing, adaptive synaptic responses, and associative learning, which are crucial for advanced neuromorphic functions such as pattern recognition, in‐memory logic operations, and optoelectronic sensory processing. Additionally, the chemical flexibility of IHPs allows for compositional tuning and structural engineering, which can be leveraged to enhance switching uniformity, reduce power consumption, and improve device reliability, making them strong candidates for large‐scale integration. This review provides a comprehensive overview of Pb‐free IHP‐based RSMDs, covering synthesis strategies, switching mechanisms, key performance metrics, and material‐dependent behaviors. Device architectures and engineering approaches to improve stability, efficiency, and scalability have also been discussed. Current challenges are examined, and perspectives are presented for advancing high‐performance, non‐toxic IHP‐based synaptic memory as a potential platform for next‐generation neuromorphic computing. image

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Publication Details

Journal
InfoMat
Published
2026-03-15
DOI
https://doi.org/10.1002/inf2.70131
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
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article

Lead‐free inorganic halide perovskite‐based synaptic memory for next generation neuromorphic computing

Manisha Sharma, Sejoon Lee, Iman Biswas, Deepak Kumar et al.
InfoMat
Advanced Memory and Neural Computing
article

Lead‐free inorganic halide perovskite‐based synaptic memory for next generation neuromorphic computing

Manisha Sharma, Sejoon Lee, Iman Biswas, Deepak Kumar, Subhasish Chanda, Sejoon Lee, Sanjeev Kumar Sharma, Aniruddha Mondal
article en

Abstract

Abstract Inorganic halide perovskites (IHPs) have emerged as promising materials for next‐generation synaptic memory, owing to their tunable bandgap, long charge‐carrier diffusion lengths, fast ion migration, and environmental sustainability. Their unique properties make them particularly attractive for resistive switching memory devices (RSMDs), which are increasingly being explored as artificial synaptic devices for neuromorphic computing. Pb‐free IHPs can emulate biological synapses at both electrical and optical levels, enabling low‐power, multifunctional, and highly efficient neuromorphic architectures. Their versatility enables multimodal sensing, adaptive synaptic responses, and associative learning, which are crucial for advanced neuromorphic functions such as pattern recognition, in‐memory logic operations, and optoelectronic sensory processing. Additionally, the chemical flexibility of IHPs allows for compositional tuning and structural engineering, which can be leveraged to enhance switching uniformity, reduce power consumption, and improve device reliability, making them strong candidates for large‐scale integration. This review provides a comprehensive overview of Pb‐free IHP‐based RSMDs, covering synthesis strategies, switching mechanisms, key performance metrics, and material‐dependent behaviors. Device architectures and engineering approaches to improve stability, efficiency, and scalability have also been discussed. Current challenges are examined, and perspectives are presented for advancing high‐performance, non‐toxic IHP‐based synaptic memory as a potential platform for next‐generation neuromorphic computing. image

InfoMat
National Institute of Technology Durgapur (IN), Dongguk University (KR), Chaudhary Charan Singh University (IN)
Openalex Percentile: Top 21%
Advanced Memory and Neural Computing
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