Computational materials science is a key approach for discovering and designing new materials, enabling predictions of stability, structural transitions, and electronic properties prior to synthesis. In this talk, we discuss the theoretical prediction and experimental realization of new materials from 2D metallic monolayers, such as goldene, as well as new classes of entangled diamond-like carbon allotropes (diamondiynes). These materials showed unique properties with applications in nanoelectronics, optoelectronics, and advanced mechanical systems.

Carlos Maciel O. Bastos holds a B.Sc. in Physics from UFSCar, and both an M.Sc. and a Ph.D. from IFSC-USP. His expertise covers a range of computational techniques, from effective methods like k.p and tight-binding, ab initio methods as density functional theory (DFT), and molecular dynamics (MD). He is a developer of the WANTIBEXOS and STB-Suite packages, as well as the SIESTA-MLIP interface to training force fields using machine learning. His primary research interests include semiconductor materials, two-dimensional (2D) materials, materials for solar cell applications, carbon allotropes, among others.