TY - JOUR AU - Kiran Mathew AU - Joseph H Montoya AU - Alireza Faghaninia AU - Shyam S Dwaraknath AU - Muratahan Aykol AU - Hanmei Tang AU - Iek-heng Chu AU - Tess Smidt AU - Brandon Bocklund AU - Matthew Horton AU - John Dagdelen AU - Brandon Wood AU - Zi-Kui Liu AU - Jeffrey B Neaton AU - Shyue Ping Ong AU - Kristin A Persson AU - Anubhav Jain AB -
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.
BT - Computational Materials Science DA - 08/2017 DO - 10.1016/j.commatsci.2017.07.030 LA - eng N2 -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.
PY - 2017 SP - 140 EP - 152 ST - Computational Materials Science T2 - Computational Materials Science TI - Atomate: A high-level interface to generate, execute, and analyze computational materials science workflows VL - 139 SN - 09270256 ER -