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NLRMatDB is a computational materials database with the specific focus on materials for renewable energy applications including, but not limited to, photovoltaic materials, materials for photo-electrochemical water splitting, thermoelectrics, etc. The main goal of NLRMatDB is to enable and facilitate the access and exchange of computational data between different research groups following the guidelines outlined in the Presidential Materials Genome Initiative (http://www.mgi.gov).

NLRMatDB is a growing collection of computed properties of stoichiometric and fully ordered materials, including:

Future developments of NLRMatDB are planned to include: defect formation energies, surface energies, ionization potentials and electron affinities, ect. Methods that are used in calculations are provided in the publications listed below. The primary engine for the first-principles calculations is the VASP code (http://www.vasp.at). The management of the high-throughput calculations is supported by the pylada environment (https://github.com/pylada/pylada-light), an NLR developed comprehensive python framework for preparing, running, monitoring, analyzing, and archiving high throughput first principles calculations.

Maintenance and development of the NLR MatDB and the web interface: Peter Graf, Harry Sorensen, and Stephen Sullivan.

List of contributors (in alphabetical order): Ann Deml, Stephan Lany, Haowei Peng, Vladan Stevanovic, Jun Yan, Pawel Zawadzki.

How to cite:

If you are using the data from NLRMatDB please acknowledge by citing the following work.

Acknowledgments:

Support for data contributions to the NLRMatDB

NLR computational materials team NLR Energy Sciences