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Chemical Bond Parameters in Sr_3MRhO_6(M=Rare earth)
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作者 Zhi Jian WU, Si Yuan ZhANG (Laboratory of rare earth chemistry and physics, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun 130022) 《Chinese Chemical Letters》 SCIE CAS CSCD 2000年第8期747-748,共2页
Chemical bond parameters, that is, bond covalency, bond valence, macroscopic linear susceptibility, and oxidation states of elements in Sr3MRhO6(M-Sm, Eu, Tb, Dy, Ho, Er, Yb) have been calculated. The results indicat... Chemical bond parameters, that is, bond covalency, bond valence, macroscopic linear susceptibility, and oxidation states of elements in Sr3MRhO6(M-Sm, Eu, Tb, Dy, Ho, Er, Yb) have been calculated. The results indicate that the bond covalency of M-O decreases sharply with the decrease of ionic radius of M3+ from Sm to Yb, while no obvious trend has been found for Rh-O and Sr-O bonds. The global instability index indicates that the crystal structures of Sr3MrhO6(M=Sm, Eu, Tb, Dy, Ho) have strained bonds. 展开更多
关键词 chemical bond parameters Sr3MRhO6.
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Study of Properties of Intermetallic Compounds of Rare Earth Metals by Artificial Neural Networks
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作者 严六明 詹千宝 +1 位作者 钦佩 陈念贻 《Journal of Rare Earths》 SCIE EI CAS CSCD 1994年第2期102-107,共6页
The results of an expert system of lanthanide intermetallic compounds using artificial neural networks and chemical bond parameter method were reported. Two pattern recognition neural models, one for prediction of the... The results of an expert system of lanthanide intermetallic compounds using artificial neural networks and chemical bond parameter method were reported. Two pattern recognition neural models, one for prediction of the occurrence of 1 : 1 lanthanide intermetallic compounds with CsClstructure and the other for prediction of congruent or incongruent melting types, were developed. Four regression neural models were also developed for prediction of melting point of these compounds. In order to get rid of overfitting, cross-vahdation method was used for the neural models. And satisfactory results were obtained in all of the neural models in this paper. 展开更多
关键词 Artificial neural network chemical bond parameter Rare earths Intermetallic compound Expert system
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