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Title: Materials Data on CaP4(HO6)2 (SG:14) by Materials Project

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations
Authors:
Publication Date:
Report Number(s):
mp-697657
DOE Contract Number:
AC02-05CH11231; EDCBEE
Product Type:
Dataset
Research Org(s):
LBNL Materials Project; Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Collaborations:
MIT; UC Berkeley; Duke; U Louvain
Sponsoring Org:
USDOE Office of Science (SC), Basic Energy Sciences (BES) (SC-22)
Resource Relation:
Related Information: https://materialsproject.org/citing
Subject:
36 MATERIALS SCIENCE; crystal structure; Ca1 H2 O12 P4; Ca-H-O-P; ICSD-82359; electronic bandstructure
OSTI Identifier:
1285173

Kristin Persson. Materials Data on CaP4(HO6)2 (SG:14) by Materials Project. United States: N. p., Web. doi:10.17188/1285173.
Kristin Persson. Materials Data on CaP4(HO6)2 (SG:14) by Materials Project. United States. doi:10.17188/1285173.
Kristin Persson. 2014. "Materials Data on CaP4(HO6)2 (SG:14) by Materials Project". United States. doi:10.17188/1285173. https://www.osti.gov/servlets/purl/1285173.
@misc{osti_1285173,
title = {Materials Data on CaP4(HO6)2 (SG:14) by Materials Project},
author = {Kristin Persson},
abstractNote = {Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations},
doi = {10.17188/1285173},
year = {2014},
month = {10} }
  1. Harnessing the power of supercomputing and state of the art electronic structure methods, the Materials Project provides open web-based access to computed information on known and predicted materials as well as powerful analysis tools to inspire and design novel materials. Experimental research can be targeted to the most promising compounds from computational data sets. Supercomputing clusters at national laboratories provide the infrastructure that enables computations, data, and algorithms to run at unparalleled speed. Researchers are be able to data-mine scientific trends in materials properties. By providing materials researchers with the information they need to design better, the Materials Project aimsmore » to accelerate innovation in materials research. « less
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