Advances in DFT-Based Computational Tribology: A Review

The rapid advancement of micro/nano-electromechanical systems (MEMS/NEMS) and precision manufacturing has fundamentally challenged traditional friction theories at the nanoscale. Classical continuum models fail to capture energy dissipation mechanisms at the atomic level, which are influenced by interfacial phenomena such as electron transfer, charge redistribution, and energy level realignment. Density functional theory (DFT), renowned for its accurate description of ground-state properties in many-electron systems, has emerged as a key tool for uncovering quantized friction mechanisms. By quantifying potential energy surface (PES) fluctuations, the evolution of interfacial charge density, and dynamic electronic band structures, DFT establishes a universal correlation between frictional dissipation and electronic behavior, transcending the limitations of conventional models in explaining stick–slip motion, superlubricity, and non-Amonton effects. Research breakthroughs in the application of DFT include characterizing frictional chemical potentials, designing heterojunction-based superlubricity, elucidating strain/load modulation mechanisms, and resolving electronic energy dissipation pathways. However, these advances remain scattered across interdisciplinary studies. This article systematically summarizes methodological innovations and cutting-edge applications of DFT in computational tribology, with the aim of constructing a unified framework for carrying out the “electronic structure–energy dissipation–frictional response” predictions. It provides a state of the art of using DFT to help design high-performance lubricants and actively control interfacial friction.