Materials Data on NaNi4(PO4)3 by Materials Project

doi:10.17188/1652300

Title: Materials Data on NaNi4(PO4)3 by Materials Project

Dataset
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Abstract

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:: The Materials Project

Publication Date:: 2019-08-31

Other Number(s):: mp-21966

DOE Contract Number:: AC02-05CH11231; EDCBEE

Research Org.:: Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). LBNL Materials Project

Sponsoring Org.:: USDOE Office of Science (SC), Basic Energy Sciences (BES)

Collaborations:: MIT; UC Berkeley; Duke; U Louvain

Subject:: 36 MATERIALS SCIENCE

Keywords:: crystal structure; NaNi4(PO4)3; Na-Ni-O-P

OSTI Identifier:: 1652300

DOI:: https://doi.org/10.17188/1652300

Citation Formats


                    The Materials Project. Materials Data on NaNi4(PO4)3 by Materials Project.  United States: N. p., 2019. 
        Web.  doi:10.17188/1652300.

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                    The Materials Project. Materials Data on NaNi4(PO4)3 by Materials Project.  United States.  doi:https://doi.org/10.17188/1652300

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                    The Materials Project. 2019.  
"Materials Data on NaNi4(PO4)3 by Materials Project".  United States.  doi:https://doi.org/10.17188/1652300.  https://www.osti.gov/servlets/purl/1652300. Pub date:Sat Aug 31 00:00:00 EDT 2019

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@article{osti_1652300,

  title        = {Materials Data on NaNi4(PO4)3 by Materials Project},

  author       = {The Materials Project},

  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          = {10.17188/1652300},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {2019},

  month        = {8}

}

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Dataset:

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DOI: https://doi.org/10.17188/1652300

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