A Low Power‐consumption and Transient Nonvolatile Memory Based on Highly Dense All‐Inorganic Perovskite Films. (16th March 2022) - Abbas, Ghulam; Hassan, Muhammad; Khan, Qasim; Wang, Haifei; Zhou, Guigang; Zubair, Muhammad; Xu, Xiuru; Peng, Zhengchun
Abstract: Inorganic perovskite‐based memory devices have attracted tremendous attention due to their higher level of stability, more feasible synthesis conditions and better performance, as compared to organic–inorganic hybrid perovskite‐based devices. However, better film morphology is an essential issue for the performance of these devices. Here, the all‐inorganic halide perovskite cesium lead bromide (CsPbBr3 ) films are successfully fabricated via a unique solution processable deposition method at ambient conditions. These films possess satisfactory surface morphology with high crystallinity. These are utilized for reproducible resistive switching layers in the gold/CsPbBr3 /indium tin oxide/Glass memory applications. A series of resistive switching layers (i.e., CsPbBr3 ) with varied thicknesses in the range of 200–500 nm are precisely tailored. The resistive switching responses and retention properties of CsPbBr3 based‐memory devices exhibit long‐term retention (exceeding 10000 s), high on/off ratio (up to 10000), low power consumption (set voltage at 0.25V), and good reproducibility. A model for the formation of filaments in the CsPbBr3 layer is proposed to describe the resistive switching mechanism. Furthermore, the devices exhibit excellent transient behavior, which is beneficial for the security of data storage. These characteristics reveal that cesium lead halide based memristor is promising to be utilized as the next‐generation smart memory device. Abstract : Highly crystalline CsPbBr3 films with good surface morphology, highly dense and well‐connected grains, and uniform thickness for memory devices are fabricated by a solution‐processable two‐step spin coating method. The as‐fabricated device shows low power consumption and transient characteristics, making it a promising candidate for neuromorphic computation and future intelligent electronics.