Review of ICME Discovering Advanced Solid Lubricants

Author of the article:LI Peixuan 1 , WANG William Yi 1,2 , SUI Xudong 3

Author's Workplace：1. State Key Laboratory of Solidification Processing, Northwestern Polytechnical University, Xi'an 710072, China; 2. Innovation Center NPU Chongqing, Chongqing 401135, China; 3. State Key Laboratory of Solid Lubrication, Lanzhou Institute of Chemical Physics, Chinese Academy of Science, Lanzhou 730000, China

Key Words：integrated computational materials engineering; solid lubricant; first-principles calculations; molecular dynamics; machine learning; high throughput

Abstract： Tribology research is a synthetic subject involving mathematics, atomic and molecular physics, materials science
and many other fields. Integrated computational materials engineering (ICME), which integrates computational materials
science, design and manufacture into a whole system, is beneficial for solving complex tribological problems and
accelerating the development of advanced solid lubricants and optimization of preparation process. In this review, beginning
with the theory-driven paradigm, both the Prandtl-Tomlinson and Frenkel-Kontorova models are introduced. Applying these
theories, the latest progress in the authors' team on two-dimensional lubricants by utilizing atomic scale simulations is
summarized. From the perspective of data-driven machine learning, the logical methods and advantages of artificial
intelligence in materials tribological performance are presented by analysing the cases of lubricity and wear-resistance
properties. Based on the frames of developing materials paradigms, the applications of ICME in tribology are discussed,
paving a path for developing advanced and engineering lubricants.