Electrode evaluation framework comprised density functional theory and thermal runaway models for the lithium-ion batteries

Lithium-ion batteries (LIBs) faces issues related to hotspots and thermal runaway when subjected to extreme conditions, necessitating the study of thermally induced failure modes to enhance both performance and safety. This research introduces a multi-scale framework that combines density functional theory (DFT) with empirical electrochemical modeling to assess the thermal behavior of LiFePO₄ and LiMnO₂ electrodes. DFT simulations were utilized to refine electrode properties such as dielectric constants, bond strengths, energy states, and structural stability. These are then transformed into temperature-dependent parameters for analyzing thermal runaway. Further, the atomistic descriptors were integrated into a lumped-parameter electrochemical–thermal model to account for heat generation, ionic transport, and decomposition pathways. A diagnostic protocol employing the finite volume method was used to evaluate electrode stability under thermal stress. By connecting electronic structure with continuum-scale thermal behavior, the framework allows for mechanistic prediction of instability, offering greater accuracy than traditional empirically fitted models. The innovation of this work is on embedding DFT-derived redox potentials, thermodynamic data, diffusion barriers, and thermal conductivities directly into macroscopic heat generation terms, thus creating a physics-based link between atomic-scale insights and system-level cooling performance. Beyond LIBs, this approach can be applied to the design of advanced thermal management systems, electrode/electrolyte screening, failure risk prediction, optimization of charging strategies, and extension to emerging chemistries like sodium-ion, solid-state, and metal–air batteries. Overall, this study presents a comprehensive strategy for advancing safe, efficient, and scalable energy storage technologies.