First-principles investigation of the resistive switching energetics in monolayer MoS2: insights into metal diffusion and adsorption
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Abstract
Abstract A deeper understanding of resistive switching (RS) in 2D materials is essential for advancing neuromorphic computing. The Dissociation-Diffusion-Adsorption (DDA) model offers a useful framework for probing RS mechanisms in non-volatile memory (NVM) and in-memory computing. We have employed first-principles density functional theory (DFT) to explore dissociation, diffusion, and adsorption phenomena within the DDA model, focusing on the interactions between exemplary metal atoms (Au, Ag, Cu) and monolayer MoS2. Nudged elastic band (NEB) calculations evaluated diffusion barriers in pristine and sulfur-vacancy MoS2. Charged systems were modeled to assess the impact of applied bias on migration pathways. We also examined metal dissociation from bulk electrodes and adsorption at S vacancies. Ag/MoS2 shows the lowest dissociation barrier (~0.034 eV), while Au and Cu exhibit similar values (~0.32 eV). These insights highlight Ag as a promising candidate for low-energy RS applications and provide guidance for optimizing switching efficiency in 2D memory devices.
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Research context
OpenAlex topics: Advanced Memory and Neural Computing · 2D Materials and Applications · Machine Learning and ELM
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References (48)
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