A follow-up on the sulphur atom popping model for MoS$_2$ memristor
Sanchali Mitra, Santanu Mahapatra
TL;DR
This work defends the sulphur atom popping mechanism as the intrinsic driver of resistive switching in MoS2 memristors, using DFT-based analyses to complement prior ReaxFF MD and to critique claims about universal ML interatomic potentials. It emphasizes the necessity of dynamic charge treatment (e.g., QEq) in simulations and shows that without extra electrons, ground-state DFT cannot reproduce the field-induced popped state; field-induced charge localization and electron trapping emerge as key stabilizers. Through targeted ab-initio calculations and careful examination of NEB results, the authors provide a coherent, field-driven mechanism that reconciles ReaxFF observations with quantum-mechanical insights, while acknowledging the limitations of static DFT and MLIPs for such reactive, defect-rich systems. The work underscores the practical significance of incorporating charge dynamics and field effects to realistically model non-volatile switching in 2D memristors and cautions against over-relying on bulk-trained, charge-agnostic ML interatomic potentials for complex 2D/defective systems.
Abstract
The mechanism of resistive switching in two-dimensional (2D) semiconductor-based memristors is intriguing, and our conventional knowledge of bulk-oxide based memristors does not apply to these devices. Experimental data indicate that the genesis of resistive switching may be intrinsic to the 2D semiconducting active layer, as well as resulting from the movement of electrode atoms. Employing reactive-force field (ReaxFF) molecular dynamics simulations, we introduced the "sulphur atom popping model" [npj 2D Mater. Appl. 5, 33 (2021)] to elucidate the intrinsic nature of non-volatile resistive switching in 2D molybdenum disulfide-based memristors. In this paper we provide additional perspective to this model using density functional theory. We also discuss the limitations of universal machine learning interatomic potentials in reproducing ReaxFF simulation results.
