32 research outputs found
Computational analysis of gas-solid interactions in materials for energy storage and conversion
Designing mixed metal halide ammines for ammonia storage using density functional theory and genetic algorithms
New superior ammonia storage materials are suggested from computational screening. Global optimum of 27â000 mixtures identified testing only âź1.5% of the candidates, proving the success of the genetic algorithm.</p
Designing New Materials for Ammonia Storage Using Density Functional Theory and Genetic Algorithms
Decoupling Strain and Ligand Effects in Ternary Nanoparticles for Improved ORR Electrocatalysis
Ternary PtâAuâM (M = 3d transition metal) nanoparticles show reduced OH adsorption energies and improved activity for the oxygen reduction reaction (ORR) compared to pure Pt nanoparticles, as obtained by density functional theory.</p
A DFT-based genetic algorithm search for AuCu nanoalloy electrocatalysts for CO2 reduction
The global minimum for a 309-atom icosahedral AuâCu nanoalloy is identified, with potential application for electrochemical production of CO.</p
Genetic algorithms for computational materials discovery accelerated by machine learning
Abstract Materials discovery is increasingly being impelled by machine learning methods that rely on pre-existing datasets. Where datasets are lacking, unbiased data generation can be achieved with genetic algorithms. Here a machine learning model is trained on-the-fly as a computationally inexpensive energy predictor before analyzing how to augment convergence in genetic algorithm-based approaches by using the model as a surrogate. This leads to a machine learning accelerated genetic algorithm combining robust qualities of the genetic algorithm with rapid machine learning. The approach is used to search for stable, compositionally variant, geometrically similar nanoparticle alloys to illustrate its capability for accelerated materials discovery, e.g., nanoalloy catalysts. The machine learning accelerated approach, in this case, yields a 50-fold reduction in the number of required energy calculations compared to a traditional âbrute forceâ genetic algorithm. This makes searching through the space of all homotops and compositions of a binary alloy particle in a given structure feasible, using density functional theory calculations