2020/04/30 by E. Aprà, E. J. Bylaska, W. A. de Jong +114 · 1 citation
Chemistry · Materials Science · Physics and Astronomy · #Advanced Chemical Physics Studies #Advanced Physical and Chemical Molecular Interactions #Complex system #Computational complexity theory #Computational model #Electronic structure #Electronic systems #Machine Learning in Materials Science #Power (physics) #Scaling #physics.chem-ph #physics.comp-ph
paper · pdf · doi:10.1063/5.0004997
published as J. Chem. Phys., 152, 184102 (2020) · This article appeared in volume 152, issue 18, page 184102 of the Journal of Chemical Physics. It can be found at https://doi.org/10.1063/5.0004997
openalex created_date 2020/05/01 · openalex publication_date 2020/05/11 · arxiv created 2020/05/26 · arxiv updated 2020/05/27 · openalex updated_date 2026/08/06
Specialized computational chemistry packages have permanently reshaped the landscape of chemical and materials science by providing tools to support and guide experimental efforts and for the prediction of atomistic and electronic properties. In this regard, electronic structure packages have played a special role by using first-principle-driven methodologies to model complex chemical and materials processes. Over the past few decades, the rapid development of computing technologies and the tremendous increase in computational power have offered a unique chance to study complex transformations using sophisticated and predictive many-body techniques that describe correlated behavior of electrons in molecular and condensed phase systems at different levels of theory. In enabling these simulations, novel parallel algorithms have been able to take advantage of computational resources to address the polynomial scaling of electronic structure methods. In this paper, we briefly review the NWChem computational chemistry suite, including its history, design principles, parallel tools, current capabilities, outreach, and outlook.