Engineering of A-site cations in APbI3 (A = Cs, Rb, K) perovskites for resistive switching control and self-rectifying memristors for next-generation computing applications

IF 16.8 1区 材料科学 Q1 CHEMISTRY, PHYSICAL
Muskan Jain , Bismiya Fasnick CK , Manish Khemnani , Lotte Kortstee , Bhawana Andola , Mayur Jagdishbhai Patel , Antonio Guerrero , Yogesh Kumar Srivastava , Ivano E. Castelli , Ankur Solanki
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引用次数: 0

Abstract

The resistive switching in memristor devices is highly influenced by structural and electronic properties, which can be tailored through material composition. Unlike optoelectronic devices, lattice distortion driven by A-site cation variation (A = Cs, Rb, K) is a key mechanism for enhancing the switching properties of APbI3-based flexible memristor devices. This distortion, particularly noticeable in KPbI3’s orthorhombic phase, alters crystal structure, electronic as well as charge transport properties. Density functional theory (DFT) calculations are performed to calculate ionic migration barriers in the orthorhombic structures, while X-ray photoelectron spectroscopy (XPS) analysis provides insights into the chemical environment and bonding states. Leveraging this effect, KPbI3 exhibits exceptional non-volatile data storage performance, with a high ON/OFF ratio (∼10³) and self-rectification (∼10³). Conversely, CsPbI3 with subtle lattice distortion, displays superior synaptic behavior and efficient spike-timing-dependent plasticity (STDP), ideal for neuromorphic computing. CsPbI3 demonstrates remarkable potential for artificial neural networks (ANNs), achieving ∼97 % accuracy in Modified National Institute of Standards and Technology (MNIST) dataset, image classification with minimal training, and 85 % accuracy in convolutional neural networks (CNNs) on the Canadian Institute for Advanced Research (CIFAR-10) dataset. Our findings highlight the critical role of small cation size in modulating Schottky barriers, morphology, and ionic migration, and their direct impact on resistive switching properties. These results underscore the potential of cation size modulation as an effective strategy for designing memristors for a wide range of applications, including neuromorphic computing, signal processing, logic gates, and quantum computing.

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来源期刊
Nano Energy
Nano Energy CHEMISTRY, PHYSICAL-NANOSCIENCE & NANOTECHNOLOGY
CiteScore
30.30
自引率
7.40%
发文量
1207
审稿时长
23 days
期刊介绍: Nano Energy is a multidisciplinary, rapid-publication forum of original peer-reviewed contributions on the science and engineering of nanomaterials and nanodevices used in all forms of energy harvesting, conversion, storage, utilization and policy. Through its mixture of articles, reviews, communications, research news, and information on key developments, Nano Energy provides a comprehensive coverage of this exciting and dynamic field which joins nanoscience and nanotechnology with energy science. The journal is relevant to all those who are interested in nanomaterials solutions to the energy problem. Nano Energy publishes original experimental and theoretical research on all aspects of energy-related research which utilizes nanomaterials and nanotechnology. Manuscripts of four types are considered: review articles which inform readers of the latest research and advances in energy science; rapid communications which feature exciting research breakthroughs in the field; full-length articles which report comprehensive research developments; and news and opinions which comment on topical issues or express views on the developments in related fields.
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