A Database of Ionic Transport Characteristics for Over 29 000 Inorganic Compounds. (25th June 2020)

• Record Type: Journal Article
• Authors: Zhang, Liwen; He, Bing; Zhao, Qian; Zou, Zheyi; Chi, Shuting; Mi, Penghui; Ye, Anjiang; Li, Yajie; Wang, Da; Avdeev, Maxim; Adams, Stefan; Shi, Siqi
• Is Part Of: Advanced functional materials. Volume 30:Number 35(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-06-25
• Subjects: bond valence site energy -- cation and anion conductors -- databases -- geometric analysis -- transport characteristics; Materials -- Periodicals; Chemical vapor deposition -- Periodicals; 620.11
• DOI: 10.1002/adfm.202003087
• Languages: English
• ISSNs: 1616-301X

Abstract

Abstract: Transport characteristics of ionic conductors play a key role in the performance of electrochemical devices such as solid‐state batteries, solid‐oxide fuel cells, and sensors. Despite the significance of the transport characteristics, they have been experimentally measured only for a very small fraction of all inorganic compounds, which limits the technological progress. To address this deficiency, a database containing crystal structure information, ion migration channel connectivity information, and 3D channel maps for over 29 000 inorganic compounds is presented. The database currently contains ionic transport characteristics for all potential cation and anion conductors, including Li +, Na +, K +, Ag +, Cu (2)+, Mg 2+, Zn 2+, Ca 2+, Al 3+, F −, and O 2−, and this number is growing steadily. The methods used to characterize materials in the database are a combination of structure geometric analysis based on Voronoi decomposition and bond valence site energy (BVSE) calculations, which yield interstitial sites, transport channels, and BVSE activation energy. The computational details are illustrated on several typical compounds. This database is created to accelerate the screening of fast ionic conductors and to accumulate descriptors for machine learning, providing a foundation for large‐scale research on ion migration in inorganic materials. Abstract : An ionic transport characteristic database for ≈29 000 Li‐, Na‐, K‐, Ag‐, Cu‐, Mg‐, Zn‐, Ca‐, Al‐, O‐, and F‐containing inorganic compounds using a combination of geometric analysis and bond valence site energy calculations is created. This database provides a useful resource for the screening of fast ionic conductors, paving the way for the large‐scale research on ion migration in inorganic materials.