4.5 Article

Atomic Simulation Recipes-A Python framework and library for automated workflows

期刊

COMPUTATIONAL MATERIALS SCIENCE
卷 199, 期 -, 页码 -

出版社

ELSEVIER
DOI: 10.1016/j.commatsci.2021.110731

关键词

High-throughput; Database; Data provenance; Workflow; Python; Materials computation; Density functional theory

资金

  1. European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program [773122, 951786]

向作者/读者索取更多资源

ASR is an open-source Python framework designed for atomistic materials simulations in a high-throughput manner, with Recipes as the core concept and ASE for interface functionality. Users can freely combine Recipes to build advanced workflows, and utilize a command-line interface for running Recipes and inspecting results.
The Atomic Simulation Recipes (ASR) is an open source Python framework for working with atomistic materials simulations in an efficient and sustainable way that is ideally suited for high-throughput projects. Central to ASR is the concept of a Recipe: a high-level Python script that performs a well defined simulation task robustly and accurately while keeping track of the data provenance. The ASR leverages the functionality of the Atomic Simulation Environment (ASE) to interface with external simulation codes and attain a high abstraction level. We provide a library of Recipes for common simulation tasks employing density functional theory and many-body perturbation schemes. These Recipes utilize the GPAW electronic structure code, but may be adapted to other simulation codes with an ASE interface. Being independent objects with automatic data provenance control, Recipes can be freely combined through Python scripting giving maximal freedom for users to build advanced workflows. ASR also implements a command line interface that can be used to run Recipes and inspect results. The ASR Migration module helps users maintain their data while the Database and App modules makes it possible to create local databases and present them as customized web pages.

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