The Electrolyte Genome project: A big data approach in battery materials discovery

Computational Materials Science

Volumn 103, Issue , 2015, Pages 56-67

  Qu, Xiaohui ^a   Jain, Anubhav ^a   Rajput, Nav Nidhi ^a   Cheng, Lei ^b   Zhang, Yong ^c   Ong, Shyue Ping ^d   Brafman, Miriam ^a   Maginn, Edward ^c   Curtiss, Larry A ^b   Persson, Kristin A ^a  

^a LAWRENCE BERKELEY NATIONAL LABORATORY   (United States)

^b ARGONNE NATIONAL LABORATORY   (United States)

^c University of Notre Dame   (United States)

^d UNIVERSITY OF CALIFORNIA SAN DIEGO   (United States)

Author keywords

Battery; DFT; Dissociation constants; Electrolyte; Electron affinity; High throughput; Ionization potential; IP EA

Indexed keywords

AUTOMATION; COMPUTATIONAL GEOMETRY; DESIGN FOR TESTABILITY; DISSOCIATION; ELECTRIC BATTERIES; ELECTROLYTES; ELECTRON AFFINITY; FUNCTIONAL GROUPS; INFORMATION MANAGEMENT; IONIZATION; IONIZATION POTENTIAL; MOLECULES; QUANTUM THEORY; REDOX REACTIONS; THROUGHPUT;

BATTERY; DFT; DISSOCIATION CONSTANT; HIGH THROUGHPUT; IP/EA;

BIG DATA;

EID: 84961287781     PISSN: 09270256     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.commatsci.2015.02.050     Document Type: Article

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