Litcius/Paper detail

Design of Mixed-Dimensional QDs/MoS<sub>2</sub>/TiO<sub>2</sub> Heterostructured Resistive Random-Access Memory with Interfacial Analog Switching Characteristics for Potential Neuromorphic Computing

Shin‐Yi Tang, Yu‐Chuan Shih, Ying‐Chun Shen, Ruei‐Hong Cyu, Chieh-Ting Chen, Tzu‐Yi Yang, Mayur Chaudhary, Yu‐Ren Peng, Yao-Ren Kuo, Wen‐Chien Miao, Yi‐Jen Yu, Ling Lee, Hao‐Chung Kuo, Yu‐Lun Chueh

2024ACS Applied Electronic Materials13 citationsDOI

Abstract

Resistive random-access memory (RRAM) is one of the most promising candidates for next-generation nanoscale nonvolatile memory devices and neuromorphic computing applications. In this study, we developed a novel mixed-dimensional design for RRAM devices, incorporating zero-dimensional quantum dots (QDs), two-dimensional MoS 2, and a TiO 2 switching layer to achieve prominent interfacial switching behaviors. Compared with typical filamentary RRAM devices, the proposed heterostructure featured a light-sensitive QDs/MoS 2 layer that allowed for bias-controllable resistive changes during the set and reset processes without abrupt switching. This was endowed by effective electron–hole pair separations upon excitation and the generation of a thin molybdenum oxide (MoO x ) layer due to the accumulation of oxygen ions at the interface between MoS 2 and TiO 2 . The ITO/QDs/MoS 2 /TiO 2 /Pt RRAM device exhibited an on/off ratio of 10 with improved endurance under 515 nm laser illumination and wavelength-dependent resistive switching behavior, making it useful for multilevel storage. Furthermore, the heterostructured device demonstrated synaptic characteristics with enhanced potentiation and depression nonlinearities and asymmetry factors, revealing its potential for future neuromorphic applications.

Topics & Concepts

Neuromorphic engineeringResistive random-access memoryMaterials scienceOptoelectronicsQuantum dotNon-volatile memoryMemristorLayer (electronics)HeterojunctionNanotechnologyVoltageComputer scienceElectronic engineeringElectrical engineeringArtificial neural networkEngineeringMachine learningAdvanced Memory and Neural ComputingPerovskite Materials and Applications2D Materials and Applications