I will present the results of ab initio and machine learning molecular dynamics simulations that show how slippery layered materials can be synthesized at the tribological interface thanks to tribochemical reactions. In particular, I will show that selenide layers can be formed by sprinkling Se nanopowders onto sliding contacts [1] and graphene can be obtained by the tribologically-induced polymerization of aromatic molecules [2]. Finally, I will discuss the potentiality of machine-learning interaction potentials to design self-assembled monolayers as friction modifiers [3].

[1] P.G. Grützmacher, M. Cutini, E. Marquis, M. Rodríguez Ripoll, H. Riedl, P. Kutrowatz, S. Bug, C.J. Hsu, J. Bernardi, C. Gachot, A. Erdemir, and M.C. Righi, Advanced Materials 35, 2302076 (2023)

[2] Y. Long, A. Pacini, M. Ferrario, N. Van Tran, S. Peeters, B. Thiebaut, S. Loehlé, J.M. Martin, M.C. Righi, and M.I. De Barros Bouchet, Carbon 228, 119365 (2024).

[3] H.T.T. Ta, M. Ferrario, S. Loehlé, and M.C. Righi, Computational Materials Today, 1 1000005 (2024)

These results are part of the ”Advancing Solid Interface and Lubricants by First Principles Material Design (SLIDE)” project that has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program (Grant agreement No. 865633).