Litcius/Paper detail

Understanding filamentary growth and rupture by Ag ion migration through single-crystalline 2D layered CrPS4

Mi Jung Lee, Sunghoon Kim, Sangik Lee, Chansoo Yoon, Kyung‐Ah Min, Hyunsoo Choi, Suklyun Hong, Sungmin Lee, Je‐Geun Park, Jae‐Pyoung Ahn, Bae Ho Park

2020NPG Asia Materials24 citationsDOIOpen Access PDF

Abstract

Abstract Memristive electrochemical metallization (ECM) devices based on cation migration and electrochemical metallization in solid electrolytes are considered promising for neuromorphic computing systems. Two-dimensional (2D) layered materials are emerging as potential candidates for electrolytes in reliable ECM devices due to their two-dimensionally confined material properties. However, electrochemical metallization within a single-crystalline 2D layered material has not yet been verified. Here, we use transmission electron microscopy and energy-dispersive X-ray spectroscopy to investigate the resistive switching mechanism of an ECM device containing a single-crystalline 2D layered CrPS 4 electrolyte. We observe the various conductive filament (CF) configurations induced by an applied voltage in an Ag/CrPS 4 /Au device in the initial/low-resistance/high-resistance/breakdown states. These observations provide concrete experimental evidence that CFs consisting of Ag metal can be formed inside single-crystalline 2D layered CrPS 4 and that their configuration can be changed by an applied voltage. Density functional theory calculations confirm that the sulfur vacancies in single-crystalline CrPS 4 can facilitate Ag ion migration from the active electrode layer. The electrically induced changes in Ag CFs inside single-crystalline 2D layered CrPS 4 raise the possibility of a reliable ECM device that exploits the properties of two-dimensionally confined materials.

Topics & Concepts

Materials scienceElectrolyteResistive random-access memoryElectrodeElectrochemistryNeuromorphic engineeringResistive touchscreenTransmission electron microscopyNanotechnologyOptoelectronicsFast ion conductorChemistryMachine learningEngineeringPhysical chemistryElectrical engineeringArtificial neural networkComputer scienceAdvanced Memory and Neural ComputingFerroelectric and Negative Capacitance DevicesConducting polymers and applications