Genetic Algorithms and Machine Learning for Predicting Surface Composition, Structure, and Chemistry: A Historical Perspective and Assessment

TL;DR: The Global Optimization with First-principles Energy Expressions (GOFEE) method as discussed by the authors is an efficient method for identifying low energy structures in computationally expensive energy landscapes such as the ones described by density functional theory, van der Waals-enabled DFT, or even methods beyond DFT.

TL;DR: In this article, the enthalpies of adsorption in zeolites were computed using machine learning techniques with thermodynamic perturbation theory using correlated approximations.

TL;DR: The Atomistic Global Optimization X (AGOX) framework as discussed by the authors provides a modular way of expressing global optimization algorithms, and modern programming practices are used to enable that modularity in the freely available AGOX Python package.

TL;DR: In this article, a genetic algorithm was used to determine the global energy minimum structures of vanadium oxide oligomers and a monolayer on the CeO₂(111) surface.

TL;DR: Scikit-learn is a Python module integrating a wide range of state-of-the-art machine learning algorithms for medium-scale supervised and unsupervised problems, focusing on bringing machine learning to non-specialists using a general-purpose high-level language.

TL;DR: In this paper, the Hartree and Hartree-Fock equations are applied to a uniform electron gas, where the exchange and correlation portions of the chemical potential of the gas are used as additional effective potentials.

TL;DR: This book brings together the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields.

TL;DR: In this article, the ground state of an interacting electron gas in an external potential was investigated and it was proved that there exists a universal functional of the density, called F[n(mathrm{r})], independent of the potential of the electron gas.