Two semi-empirical approaches for the prediction of oxide ionic conductivities in ABO3 perovskites

Computational Materials Science

Volumn 46, Issue 4, 2009, Pages 860-868

  Xu, Liu ^a,b   Wencong, Lu ^b   Chunrong, Peng ^b   Qiang, Su ^a   Jin, Guo ^c  

^a SHANGHAI UNIVERSITY   (China)

^b Department of Chemistry   (China)

^c GUANGXI UNIVERSITY   (China)

Author keywords

CASTEP; Conductivity; Electronic structure; Perovskites; Support vector regression

Indexed keywords

ATOMIC PROPERTIES; BACK-PROPAGATION ARTIFICIAL NEURAL NETWORK; CASTEP; CONDUCTIVITY; ELECTRICAL CONDUCTIVITY; FIRST-PRINCIPLES CALCULATION; GENERALIZATION ABILITY; MACHINE-LEARNING; OXIDE IONIC CONDUCTIVITY; OXIDE-ION CONDUCTIVITY; PARTIAL LEAST SQUARES; PEROVSKITE TYPE OXIDES; PLS MODELS; SEMI-EMPIRICAL APPROACH; SUPPORT VECTOR REGRESSION; SUPPORT VECTOR REGRESSIONS; THREE MACHINE LEARNING METHODS;

ALGEBRA; ELECTRIC PROPERTIES; ELECTRONIC PROPERTIES; ELECTRONIC STRUCTURE; IONIC CONDUCTIVITY; IONS; NEURAL NETWORKS; OXIDE MINERALS; PEROVSKITE; REGRESSION ANALYSIS; ROBOT LEARNING;

BACKPROPAGATION;

EID: 70249138290     PISSN: 09270256     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.commatsci.2009.04.047     Document Type: Article

References (57)

1. Ishihara T., Matsuda H., and Takita Y. Journal of American Chemical Society 116 (1994) 3801-3803
2. Huang K., Tichy R.S., and Goodenough J.B. Journal of the American Ceramic Society 81 10 (1998) 2565-2575
3. Huang K., Tichy R.S., and Goodenough J.B. Journal of the American Ceramic Society 81 10 (1998) 2576-2580
4. Huang K., Tichy R.S., and Goodenough J.B. Journal of the American Ceramic Society 81 10 (1998) 2581-2585
5. Saiful Islam M. Journal of Material Chemistry 10 (2000) 1027-1038
6. Kuwabara A., and Tanaka I. Journal of Physical Chemistry B 108 (2004) 9168-9172
7. Pornprasertsuk R., Ramanarayanan P., Musgrave C.B., and Prinz F.B. Journal of Applied Physics 98 (2005) 103513
8. Cherry M., Islam M.S., and Catlow C.R.A. Journal of Solid State Chemistry 118 (1995) 125-132
9. Piskunov S., Heifets E., Eglitis R.I., and Borstel G. Computational Materials Science 29 (2004) 165-178
10. Pramananda Perumal T., Sridhar V., Murthy K.P.N., Easwarakumar K.S., and Ramasamy S. Computational Materials Science 38 (2007) 865-872
11. Eglitis R.I., Kotomin E.A., Borstel G., Kapphan S.E., and Vikhnin V.S. Computational Materials Science 27 (2003) 81-86
12. Kuzmanovski I., and Aleksovska S. Chemometrics and Intelligent Laboratory Systems 67 (2003) 167-174
13. Björketun M.E., Sundell P.G., Wahnström G., and Engberg D. Solid State Ionics 176 (2005) 3035-3040
14. Iles N., Kellou A., Driss Khodja K., Amrani B., Lemoigno F., Bourbie D., and Aourag H. Computational Materials Science 39 (2007) 896-902
15. Javed S.G., Khan A., Majid A., Mirza A.M., and Bashir J. Computational Materials Science 39 (2007) 627-634
16. Wold S., Sjöström M., and Eriksson L. Laboratory Information Management 58 (2001) 109-130
17. Chen N.-y., Lu W.-c., Chen R.-l., Li C.-h., and Qin P. Laboratory Information Management 45 (1999) 329-333
18. Zhang Z., and Friedrich K. Composites Science and Technology 63 (2003) 2029-2044
19. Verikas A., and Bacauskiene M. Laboratory Information Management 67 (2003) 187-191
20. Vapnik V. Statistical Learning Theory (1998), John Wiley and Johns, New York
21. A.J. Smola, B. Schölkopf, A Tutorial on Support Vector Regression, NeuroCOLT Technical Report NC-TR-98-030, Royal Holloway College, University of London, UK, 1998. Available from: .
22. Chen N.-y., Lu W.-c., Yang J., and Li G.-z. Support Vector Machine in Chemistry (2004), World Scientific Publishing Company, Singapore
23. Madsen G.K.H., and Singh D.J. Computer Physics Communications 175 (2006) 67-71
24. Cook R.L., and Sammells A.F. Solid State Ionics 45 (1991) 311-321
25. Sammells A.F., Cook R.L., White J.H., Osborne J.J., and MacDuff R.C. Solid State Ionics 52 (1992) 111-123
26. Pauling L. Nature of Chemical Bond (1960), Cornell University Press
27. Pauling L. Proceedings of Royal Society A (1927) 114-191
28. Fajans K., and Joos G. Zeitschrift fur Physik 23 (1924) 20
29. Yu-biao F., Shao-yin Z., Hong-tao S., Yuan L., and Yan-yun Z. Journal of Dal ian Institute of Light Industry 19 (2000) 98-101 (in Chinese)
30. Jones R.O., and Gunnarsson O. Reviews of Modern Physics 61 (1989) 689
31. Kohn W., and Sham L.J. Physical Review A 140 (1965) 1133
32. Segall M.D., Lindan P.L.D., Probert M.J., Pickard C.J., Hasnip P.J., Clark S.J., and Payne M.C. Journal of Physics: Condensed Matter 14 11 (2002) 2717-2743
33. Pagnier T., Charrier-Cougoulic I., Ritter C., and Lucazeau G. The European Physical Journal Applied Physics 9 (2000) 1-9
34. Ruggiero A., and Ferro R. Classe di Scienze Fisiche, Matematiche 17 (1954) 48-50
35. Liu X., and Liebermann R.C. Physics and Chemistry of Minerals (Germany) 20 (1993) 171-175
36. Brous J., Fankuchen I., and Banks E. Acta Crystallographica 6 (1953) 67-70 (1,1948-23,1967)
37. Lerch M. Journal of Physics and Chemistry of Solids 62 (2001) 445-455
38. Hayashi H., Inaba H., Matsuyama M., Lan N.G., Dokiya M., and Tagawa H. Solid State Ionics 122 (1999) 1-15
39. Verikas A., and Bacauskiene M. Chemometrics and Intelligence Laboratory Systems 67 (2003) 187-191
40. Wen-cong L., Nian-yi C., Chen-zhou Y., and Guo-zheng L.I. Computers and Applied Chemistry 19 6 (2002) 697-702 (in Chinese)
41. Furutani H., Honda M., and Yamada T. Chemistry of Materials 11 (1999) 2081-2088
42. Ishihara T., Ishikawa S., Yu C., Akbay T., and Hosoi K. Physical Chemistry Chemical Physics 5 (2003) 2257-2263
43. Ishihara T., Ishikawa S., Hosoi K., Nishiguchi H., and Takita Y. Solid State Ionics 175 (2004) 319-322
44. Shibayama, Nishiguchi H., and Takita Y. Journal of Materials Science 36 (2001) 1125-1131
45. Hashimoto, Kishimoto H., and Iwahara H. Solid State Ionics 139 (2001) 179-187
46. Lybye D., and Bonanos N. Solid State Ionics 125 (1999) 339-344
47. Lybye D., Poulsen F.W., and Mogensen M. Solid State Ionics 128 (2000) 91-103
48. George H. John, Ron Kohavi, Karl Pfleger, in: Machine Learning: Proceedings of the Eleventh International Conference, Morgan Kaufmann Publishers, San Francisco, CA, 1994, pp. 121-129.
49. Amendolia S.R., Cossu G., Ganadu M.L., Golosio B., Masala G.L., and Mura G.M. Chemometrics Intelligent Laboratory Systtems 69 (2003) 13-20
50. Mj. Kearns, D. Ron, in: Proceedings of the Tenth Annual ACM Workshop on Computational Learning Theory, Nashville, Tennessee, 1997 July 6-9. ACM Press, New York, 1997, pp. 152-162.
51. S.B. Holden, PAC-like Upper Bounds for the Sample Complexity of Leave-one-out Cross Validation, Paper Presented at Ninth Annual ACM Workshop on Computational Learning Theory, June 28, Desenzano del Garda, Italy, 1996.
52. Saghi-Szabo G., Cohen R.E., and Krakauer H. Physical Review B 59 (1999) 12771-12776
53. Inbar I., and Cohen R.E. Physical Review B 53 (1996) 1193-1204
54. Mori S., Chen C.H., and Cheong S.W. Nature 392 (1998) 473-476
55. Stevenson J.W., Armstrong T.R., Carneim R.D., Pederson L.R., and Weber W.J. Journal of the Electrochemical Society 143 (1996) 2722-2729
56. Satpathy S., Popovic Z.S., and Vukajlovic F.R. Physical Review 76 (1996) 960-963
57. Mizokawa T., and Fujimori A. Physical Review 54 (1996) 5368-5380