Prediction of superconductivity for oxides based on structural parameters and artificial neural network method

J Mater Sci Technol ›› 2000, Vol. 16 ›› Issue (04): 435-438.

• Research Articles • Previous Articles Next Articles

Prediction of superconductivity for oxides based on structural parameters and artificial neural network method

Xueye WANG, Huang SONG, Guanzhou QIU, Dianzuo WANG

Department of Chemistry, Xiangtan University, Xiangtan 411105, China...

Received:1999-05-28 Revised:1999-08-04 Online:2000-07-28 Published:2009-10-10
Contact: Xueye WANG

Abstract

Abstract: Superconductive properties for oxides were predicted by artificial neural network (ANN) method with structural and chemical parameters as inputs. The predicted properties include superconductivity for oxides, distributed ranges of the superconductive transition temperature (T-c) for complex oxides, and T-c values for cuprate superconductors. The calculated results indicated that the adjusted ANN can be used to predict superconductive properties for unknown oxides.

Key words:

Xueye WANG, Huang SONG, Guanzhou QIU, Dianzuo WANG. Prediction of superconductivity for oxides based on structural parameters and artificial neural network method[J]. J Mater Sci Technol, 2000, 16(04): 435-438.

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Prediction of superconductivity for oxides based on structural parameters and artificial neural network method

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