登录注册
Quick Links : Mindat手册The Rock H. Currier Digital LibraryMindat Newsletter [Free Download]
主页关于 MindatMindat手册Mindat的历史版权Who We Are联系我们于 Mindat.org刊登广告
捐赠给 MindatCorporate Sponsorship赞助板页已赞助的板页在 Mindat刊登 广告的广告商于 Mindat.org刊登广告
Learning CenterWhat is a mineral?The most common minerals on earthInformation for EducatorsMindat ArticlesThe ElementsThe Rock H. Currier Digital LibraryGeologic Time
搜索矿物的性质搜索矿物的化学Mineral Visual ExplorerAdvanced Locality Search随意显示任何一 种矿物Random Locality使用minID搜索邻近产地Search Articles搜索词汇表更多搜索选项
搜索:
矿物名称:
地区产地名称:
关键字:
 
Mindat手册添加新照片Rate Photos产区编辑报告Coordinate Completion Report添加词汇表项目
Mining Companies统计会员列表Mineral MuseumsClubs & Organizations矿物展及活动The Mindat目录表设备设置The Mineral QuizTime Machine
照片搜索Photo GalleriesSearch by ColorPhoto Colour Explorer今天最新的照片昨天最新的照片用户照片相集过去每日精选照片相集Photography

Xu, Liu, Wencong, Lu, Chunrong, Peng, Qiang, Su, Jin, Guo (2009) Two semi-empirical approaches for the prediction of oxide ionic conductivities in ABO3 perovskites. Computational Materials Science, 46 (4). 860-868 doi:10.1016/j.commatsci.2009.04.047

Advanced
   -   Only viewable:
Reference TypeJournal (article/letter/editorial)
TitleTwo semi-empirical approaches for the prediction of oxide ionic conductivities in ABO3 perovskites
JournalComputational Materials Science
AuthorsXu, LiuAuthor
Wencong, LuAuthor
Chunrong, PengAuthor
Qiang, SuAuthor
Jin, GuoAuthor
Year2009 (October)Volume46
Issue4
PublisherElsevier BV
DOIdoi:10.1016/j.commatsci.2009.04.047Search in ResearchGate
Generate Citation Formats
Mindat Ref. ID9505648Long-form Identifiermindat:1:5:9505648:9
GUID0
Full ReferenceXu, Liu, Wencong, Lu, Chunrong, Peng, Qiang, Su, Jin, Guo (2009) Two semi-empirical approaches for the prediction of oxide ionic conductivities in ABO3 perovskites. Computational Materials Science, 46 (4). 860-868 doi:10.1016/j.commatsci.2009.04.047
Plain TextXu, Liu, Wencong, Lu, Chunrong, Peng, Qiang, Su, Jin, Guo (2009) Two semi-empirical approaches for the prediction of oxide ionic conductivities in ABO3 perovskites. Computational Materials Science, 46 (4). 860-868 doi:10.1016/j.commatsci.2009.04.047
In(2009, October) Computational Materials Science Vol. 46 (4) Elsevier BV

See Also

These are possibly similar items as determined by title/reference text matching only.

Chang, Dongping, Xu, Pengcheng, Ji, Xiaobo, Li, Minjie, Lu, Wencong (2023) Application of Online Computational Platform of Materials Data Mining (OCPMDM) in Search for ABO3 Perovskites with Multi-Properties. Science of Advanced Materials, 15 (8) 1014-1025 doi:10.1166/sam.2023.4525
Yang, Xue, Li, Long, Tao, Qiuling, Lu, Wencong, Li, Minjie (2021) Rapid discovery of narrow bandgap oxide double perovskites using machine learning. Computational Materials Science, 196. 110528pp. doi:10.1016/j.commatsci.2021.110528
Zhang, Yun, Xu, Xiaojie (2022) Modeling oxygen ionic conductivities of ABO3 Perovskites through machine learning. Chemical Physics, 558. 111511pp. doi:10.1016/j.chemphys.2022.111511
Xu, Pengcheng, Lu, Tian, Ji, Xiaobo, Li, Minjie, Lu, Wencong (2023) Machine Learning Combined with Weighted Voting Regression and Proactive Searching Progress to Discover ABO3-δ Perovskites with High Oxide Ionic Conductivity. The Journal of Physical Chemistry C, 127 (34) 17096-17108 doi:10.1021/acs.jpcc.3c02893
Gong, Chen, Liu, Jian, Dai, Siqi, Hao, Hua, Liu, Hanxing (2024) Machine learning assisted prediction of the phonon cutoff frequency of ABO3 perovskite materials. Computational Materials Science, 239. 112943 doi:10.1016/j.commatsci.2024.112943
Javed, Syed Gibran, Khan, Asifullah, Majid, Abdul, Mirza, Anwar M., Bashir, J. (2007) Lattice constant prediction of orthorhombic ABO3 perovskites using support vector machines. Computational Materials Science, 39 (3). 627-634 doi:10.1016/j.commatsci.2006.08.015
Eglitis, R.I, Kotomin, E.A, Borstel, G (2004) Computer modelling of point defects in ABO3 perovskites and MgO. Computational Materials Science, 30 (3). 376-382 doi:10.1016/j.commatsci.2004.02.030
Lu, Yizhou; Uberuaga, Blas Pedro; Choudhury, Samrat (2026) Machine learning guided prediction of solute segregation at coherent and semi-coherent metal/oxide interfaces. Computational Materials Science, 264. doi:10.1016/j.commatsci.2025.114480
Soontrapa, C., Chen, Y. (2009) Optimization approach in variable-charge potential for metal/metal oxide systems. Computational Materials Science, 46 (4). 887-892 doi:10.1016/j.commatsci.2009.04.027
Olsson, Pär A.T. (2009) Semi-empirical atomistic study of point defect properties in BCC transition metals. Computational Materials Science, 47 (1). 135-145 doi:10.1016/j.commatsci.2009.06.025
Akrom, Muhamad, Rustad, Supriadi, Dipojono, Hermawan Kresno, Maezono, Ryo, Kasai, Hideaki (2025) Quantum machine learning for ABO3 perovskite structure prediction. Computational Materials Science, 250. doi:10.1016/j.commatsci.2025.113694
 
and/or  
版权所有© mindat.org1993年至2026年，除了规定的地方。 Mindat.org全赖于全球数千个以上成员和支持者们的参与。
To cite: Ralph, J., Von Bargen, D., Martynov, P., Zhang, J., Que, X., Prabhu, A., Morrison, S. M., Li, W., Chen, W., & Ma, X. (2025). Mindat.org: The open access mineralogy database to accelerate data-intensive geoscience research. American Mineralogist, 110(6), 833–844. doi:10.2138/am-2024-9486.
隐私政策 - 条款和条款细则 - 联络我们 - Report a bug/vulnerability Current server date and time: 2026.6.6 10:56:36
Go to top of page