Fast inertial relaxation engine in the CRYSTAL code

In the framework of ab initio simulations, search for energy minimum atomic structures is first step to perform in studying properties a system. One most used and efficient optimization algorithms quasi-Newton line-search scheme based on Broyden–Fletcher–Goldfarb–Shanno (Bfgs) Hessian updating formula. However, recent studies [Bitzek et al., Phys. Rev. Lett. 97, 170201 (2006) Guénolé Comput. Mater. Sci. 175, 109584 (2020)] suggested that minimization methods molecular dynamics concepts, such as Fast Inertial Relaxation Engine (Fire) algorithm, often exhibit better performance accuracy finding local minima than schemes. present work, implementation Fire, Crystal quantum mechanical simulation package [Dovesi Wiley Interdiscip. Rev.: Mol. 8, e1360 (2018)], has been described. Its efficiency comparison with Bfgs have assessed using Hartree–Fock density functional theory Perdew–Burke–Ernzerhof hybrid functionals model potential surface. Fire shows good convergence behavior all considered systems, well reproducing obtained by approach. As regards computational cost, requires more iterations converge respect Bfgs, but each iteration faster one. The overall improves size system increased so this method seems be very promising systems without symmetry (space group P1) large number atoms.