Atomic Whispers to System Health Diagnosis and Prognosis: First-Principles-Based Degradation Modeling of 2D Materials in Next-Generation Bioelectronics

Abstract

Our results demonstrate that Cr intercalation into 2D transition metal dichalcogenide materials will significantly elevate the interlayer shear resistance, acting as an atomic-scale "glue" that mitigates delamination and structural failure—a key degradation mechanism. We uncover dynamic stabilization mechanisms and quantify the energy barriers that retard lateral sliding, which are crucial inputs for physics-of-failure models. We combine ab initio density functional theory (DFT) and machine-learned-force-field Molecular Dynamics (MLFF-MD) for this study. Leveraging MLFFs allows us to extend our simulations to larger length- and time-scales and hence capture long-term dopant dynamics and degradation evolution. MLFF-MD has the advantage of combining a bigger scope with near-DFT accuracy, enhancing predictive capabilities for materials design.

This work provides mechanistic insight into transition metal intercalation for 2D material's stabilization and offers a physics-informed computational framework for assessing material longevity and reliability. Such predictive capabilities are critical for proactive Prognostics and Health Management (PHM), enabling the rational design of robust 2D heterostructures, guiding synthesis strategies, and informing maintenance protocols for advanced electronic and spintronic devices.