Crystal structure prediction via particle-swarm optimization

Abstract

We have developed a powerful method for crystal structure prediction from "scratch" through particle swarm optimization (PSO) algorithm within the evolutionary scheme.PSO technique is dramatically different with the genetic algorithm and has apparently avoided the use of evolution operators (e.g., crossover and mutation). The approach is based on a highly efficient global minimization of free energy surfaces merging total-energy calculations via PSO technique and requires only chemical compositions for a given compound to predict stable or metastable structures at given external conditions (e.g., pressure). A particularly devised geometrical structure factor method which allows the elimination of similar structures during structure evolution was implemented to enhance the structure search efficiency. The application of designed variable unit cell size technique has greatly reduced the computational cost. Moreover, the symmetry constraint imposed in the structure generation enables the realization of diverse structures, leads to significantly reduced search space and optimization variables, and thus fastens the global structural convergence. The PSO algorithm has been successfully applied to the prediction of many known systems (e.g., elemental, binary and ternary compounds) with various chemical bonding environments (e.g., metallic, ionic, and covalent bonding). The remarkable success rate demonstrates the reliability of this methodology and illustrates the great promise of PSO as a major technique on crystal structure determination. 11 R. Martonak, A. Laio, and M. Parrinello, Physical review letters 90, 75503 (2003).

Sn(II)-Containing Phosphates as Optoelectronic Materials

“…As mentioned, we performed structure prediction calculations for SnP 2 O 6 . These were done based on first principles DFT calculations combined with the particle swarm optimization algorithm as implemented in the CALYPSO code [36,37]. We also particularly calculated the optical absorption spectra of the compounds when doped [38][39][40].…”

Tailoring Li adsorption on graphene

“…In the PPSO method, we fix the coordinates of the C atoms in the graphene, while allowing the coordinates of Li atoms to evolve using the PSO algorithm [16]. First, 20 different Li adsorption patterns were randomly generated and then relaxed using the DFT calculations.…”

“…clusters [16]. By only using chemical component information, these authors have been successful in determining stable configurations of O 4 , Li, and ice under high pressure [17][18][19].…”

Emergence of a few distinct structures from a single formal structure type during high-throughput screening for stable compounds: The case of RbCuS and RbCuSe

“…Several global optimization methods are currently widely used to search for the lowest energy structure of a solid by exploring in an unbiased fashion the Born-Oppenheimer surface of a solid calculated by DFT. These computational appraoches include evolutionary algorithms [30][31][32][33][34] , particle swarm optimization, 35 methods based on molecular dynamics, such as simulated annealing 36 , minima hopping, 37 and metadynamics 38 . Also a search approach based on the local energy minimization of randomly generated structures 39 has been successfully applied to numerous materials.…”