Atomate: A high-level interface to generate, execute, and analyze computational materials science workflows. We introduce atomate, an open-source Python framework for computational materials science simulation, analysis, and design with an emphasis on automation and extensibility. Built on top of open source Python packages already in use by the materials community such as pymatgen, FireWorks, and custodian, atomate provides well-tested workflow templates to compute various materials properties such as electronic bandstructure, elastic properties, and piezoelectric, dielectric, and ferroelectric properties. Atomate also enables the computational characterization of materials by providing workflows that calculate X-ray absorption (XAS), Electron energy loss (EELS) and Raman spectra. One of the major features of atomate is that it provides both fully functional workflows as well as reusable components that enable one to compose complex materials science workflows that use a diverse set of computational tools. Additionally, atomate creates output databases that organize the results from individual calculations and contains a builder framework that creates summary reports for each computed material based on multiple simulations.
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References in zbMATH (referenced in 3 articles )
Showing results 1 to 3 of 3.
- Morten Gjerding, Thorbjørn Skovhus, Asbjørn Rasmussen, Fabian Bertoldo, Ask Hjorth Larsen, Jens Jørgen Mortensen, Kristian Sommer Thygesen: Atomic Simulation Recipes - a Python framework and library for automated workflows (2021) arXiv
- He Ma, Wennie Wang, Siyoung Kim, Man-Hin Cheng, Marco Govoni, Giulia Galli: PyCDFT: A Python package for constrained density functional theory (2020) arXiv
- Brian C. Ferrari: AutoGAMESS: A Python package for automation of GAMESS(US) Raman calculations (2019) not zbMATH