Theoretical investigation of the Ag filament morphology in conductive bridge random access memories

Conductive bridge random access memories (CBRAMs) usually involve active Ag or Cu metals, where the formation of metal filaments accounts for the low resistance state. For the application of neuromorphic computation, it is highly desirable to develop artificial neurons and synapses, which utilize the complicated volatile or nonvolatile resistive switching phenomena, respectively. This can be achieved by controlling the morphology and stability of the filaments, which requires a deep understanding of the filament formation and disruption mechanisms. Using ab initio calculations, we explored the physical mechanism behind various Ag filament morphologies and growth modes, using GeSe, ZrO2, SiO2, and a-Si as the examples. The roles of Ag and Ag+ stability inside the dielectric, the migration barrier of Ag+, and the Ag+ solvation effect have been investigated in detail. A comprehensive model has been proposed, which in particular could explain the diverse Ag filament morphology experimentally observed in sputtered SiO2 and PECVD SiO2. Our theoretical approach can serve as a pre-screening method in designing new solid-state electrolyte materials of CBRAM, aiming at new functionalities in neuromorphic computation or in-memory logic computing. Published by AIP Publishing.