Recent advances in artificial neuromorphic applications based on perovskite composite

Abstract

High-performance perovskite materials with excellent physical, electronic, and optical properties play a significant role in artificial neuromorphic devices. However, the development of perovskites in microelectronics is inevitably hindered by their intrinsic non-ideal properties, such as high defect density, environmental sensitivity, and toxicity. By leveraging materials engineering, integrating various materials with perovskites to leverage their mutual strengths presents great potential to enhance ion migration, energy level alignment, photo-responsivity, and surface passivation, thereby advancing optoelectronic and neuromorphic device development. This review initially provides an overview of perovskite materials across different dimensions, highlighting their physical properties and detailing their applications and metrics in two- and three-terminal devices. Subsequently, we comprehensively summarize the application of perovskite in combination with other materials, including organics, nanomaterials, oxides, ferroelectrics, and crystalline porous materials (CPMs), to develop advanced devices such as memristors, transistors, photodetectors, sensors, light-emitting diode (LED), and artificial neuromorphic systems. Lastly, we outline the challenges and future research directions in synthesizing perovskite composites for neuromorphic devices. Through the review and analysis, we aim to broaden the utilization of perovskites and their composites in neuromorphic research, offering new insights and approaches for grasping the intricate physical working mechanisms and functionalities of perovskites.

Article information

Article type
Review Article
Submitted
12 maj 2024
Accepted
17 jul 2024
First published
20 jul 2024

Mater. Horiz., 2024, Accepted Manuscript

Recent advances in artificial neuromorphic applications based on perovskite composite

H. Li, Q. Li, T. Sun, Y. Zhou and S. Han, Mater. Horiz., 2024, Accepted Manuscript , DOI: 10.1039/D4MH00574K

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