Structure and activity relationship for CO and O2 adsorption over gold nanoparticles using density functional theory and artificial neural networks

Journal of Chemical Physics

Volumn 132, Issue 17, 2010, Pages

  Davran Candan, Tuǧba ^a   Günay, M Erdem ^a   Yildirim, Ramazan ^a  

^a BOGAZICI UNIVERSITY   (Turkey)

Author keywords

[No Author keywords available]

Indexed keywords

ADSORPTION ENERGIES; ADSORPTION SITE; ARTIFICIAL NEURAL NETWORK; ARTIFICIAL NEURAL NETWORK MODELS; CATALYTIC SYSTEM; CATIONIC CLUSTER; CO OXIDATION; COORDINATION NUMBER; DESCRIPTORS; GOLD NANOPARTICLES; HIGHEST OCCUPIED MOLECULAR ORBITAL; LOWEST UNOCCUPIED MOLECULAR ORBITAL GAP; NEURAL NETWORK MODEL; UNPAIRED ELECTRONS;

ADSORPTION; BINDING ENERGY; DENSITY FUNCTIONAL THEORY; DYES; ELECTRON AFFINITY; GOLD COMPOUNDS; IONIZATION POTENTIAL; MOLECULAR MODELING; MOLECULAR ORBITALS; NANOPARTICLES; NEURAL NETWORKS; STRUCTURAL OPTIMIZATION;

STRUCTURAL PROPERTIES;

EID: 78049371866     PISSN: 00219606     EISSN: None     Source Type: Journal    
DOI: 10.1063/1.3369007     Document Type: Article

References (55)

1. S. M. Senkan, Angew. Chem., Int. Ed. 1433-7851 40, 312 (2001). 10.1002/1521-3773(20010119)40:2<312::AID-ANIE312>3.0.CO;2-I (Pubitemid 32114870)
2. M. Neurock, Applications: Catalysis. In WTEC Panel Report on Applications of Molecular and Materials Modeling (International Technology Research Institute, Maryland, 2002).
3. M. Haruta, Catal. Surv. Jpn. 1384-6574 1, 61 (1997). 10.1023/A: 1019068728295
4. M. Haruta, Catal. Today 0920-5861 36, 153 (1997). 10.1016/S0920-5861(96) 00208-8
5. W. T. Wallace and R. L. Whetten, J. Am. Chem. Soc. 0002-7863 124, 7499 (2002). 10.1021/ja0175439 (Pubitemid 34670457)
6. A. Sanchez, S. Abbet, U. Heiz, W. D. Schneider, H. Häkkinen, R. N. Barnett, and U. Landman, J. Phys. Chem. A 1089-5639 103, 9573 (1999). 10.1021/jp9935992
7. Y. Iizuka, T. Tode, T. Takao, K. Yatsu, T. Takeuchi, S. Tsubota, and M. Haruta, J. Catal. 0021-9517 187, 50 (1999). 10.1006/jcat.1999.2604
8. M. Valden, X. Lai, and D. W. Goodman, Science 0036-8075 281, 1647 (1998). 10.1126/science.281.5383.1647 (Pubitemid 28435574)
9. M. Haruta, T. Kobayashi, H. Sano, and N. Yamada, Chem. Lett. 0366-7022 16, 405 (1987). 10.1246/cl.1987.405
10. C. Rossignol, S. Arrii, F. Morfin, L. Piccolo, V. Caps, and J. L. Rousset, J. Catal. 0021-9517 230, 476 (2005). 10.1016/j.jcat.2005.01.011
11. R. J. H. Grisel, C. J. Weststrate, A. Goossens, M. W. J. Craj́, A. M. van der Kraan, and B. E. Nieuwenhuys, Catal. Today 0920-5861 72, 123 (2002). 10.1016/S0920-5861(01)00486-2 (Pubitemid 34222290)
12. X. Wu, L. Senapati, S. K. Nayak, A. Selloni, and M. Hajaligol, J. Chem. Phys. 0021-9606 117, 4010 (2002). 10.1063/1.1483067 (Pubitemid 34992686)
13. D. W. Yuan and Z. Zeng, J. Chem. Phys. 0021-9606 120, 6574 (2004). 10.1063/1.1667466
14. G. Mills, M. S. Gordon, and H. Metiu, Chem. Phys. Lett. 0009-2614 359, 493 (2002). 10.1016/S0009-2614(02)00746-7
15. B. Yoon, H. Häkkinen, and U. Landman, J. Phys. Chem. A 1089-5639 107, 4066 (2003). 10.1021/jp027596s
16. T. Davran-Candan, E. A. Aksoylu, and R. Yildirim, J. Mol. Catal. A: Chem. 1381-1169 306, 118 (2009). 10.1016/j.molcata.2009.02.034
17. L. M. Molina and B. Hammer, Phys. Rev. Lett. 0031-9007 90, 206102 (2003). 10.1103/PhysRevLett.90.206102
18. L. M. Molina and B. Hammer, Phys. Rev. B 0163-1829 69, 155424 (2004). 10.1103/PhysRevB.69.155424
19. L. M. Molina, M. D. Rasmussen, and B. Hammer, J. Chem. Phys. 0021-9606 120, 7673 (2004). 10.1063/1.1687337
20. A. Franceschetti, S. J. Pennycook, and S. T. Pantelides, Chem. Phys. Lett. 0009-2614 374, 471 (2003). 10.1016/S0009-2614(03)00725-5 (Pubitemid 36742425)
21. B. Hvolbæk, T. V. W. Janssens, B. S. Clausen, H. Falsig, C. H. Christensen, and J. K. Norskov, Nanotoday 1748-0132 2, 14 (2007). 10.1016/S1748-0132(07)70113-5 (Pubitemid 47074465)
22. N. Lopez and J. K. Norskov, J. Am. Chem. Soc. 0002-7863 124, 11262 (2002). 10.1021/ja026998a
23. L. Xiao, B. Tollberg, X. Hu, and L. Wang, J. Chem. Phys. 0021-9606 124, 114309 (2006). 10.1063/1.2179419
24. H. Häkkinen, B. Yoon, U. Landman, X. Li, H. J. Zhai, and L. S. Wang, J. Phys. Chem. A 1089-5639 107, 6168 (2003). 10.1021/jp035437i
25. J. Wang, G. Wang, and J. Zhao, Phys. Rev. B 0163-1829 66, 035418 (2002). 10.1103/PhysRevB.66.035418
26. P. K. Jain, Struct. Chem. 1040-0400 16, 421 (2005). 10.1007/s11224-005- 6350-8 (Pubitemid 41278442)
27. D. T. Larose, Discovering Knowledge in Data (Wiley, New Jersey, 2005).
28. R. Callan, The Essence of Neural Networks (Prentice Hall, Hertfordshire, 1999).
29. M. E. Günay and R. Yildirim, Chem. Eng. J. 0300-9467 140, 324 (2008). 10.1016/j.cej.2007.09.047 (Pubitemid 351713579)
30. M. E. Günay and R. Yildirim, Appl. Catal., A 0926-860X 377, 174 (2010). 10.1016/j.apcata.2010.01.033
31. A. Corma, J. M. Serra, P. Serna, S. Valero, E. Argente, and V. Botti, J. Catal. 0021-9517 229, 513 (2005). 10.1016/j.jcat.2004.11.024
32. T. Hattori and S. Kito, Catal. Today 0920-5861 23, 347 (1995). 10.1016/0920-5861(94)00148-U
33. M. Holeňa and M. Baerns, Catal. Today 0920-5861 81, 485 (2003). 10.1016/S0920-5861(03)00147-0
34. U. Rodemerck, M. Baerns, M. Holeňa, and D. Wolf, Appl. Surf. Sci. 0169-4332 223, 168 (2004). 10.1016/S0169-4332(03)00919-X
35. R. M. Balabin and E. I. Lomakina, Neural network approach to quantum-chemistry data: Accurate prediction of density functional theory energies .Journal of Chemical Physics(2009),131(7), DOI: 10.1063/1.3206326, Article number 074104.
36. H. Häkkinen and U. Landman, Phys. Rev. B 0163-1829 62, R2287 (2000). 10.1103/PhysRevB.62.R2287
37. J. Zhao, J. Yang, and J. G. Hou, Phys. Rev. B 0163-1829 67, 085404 (2003). 10.1103/PhysRevB.67.085404
38. E. M. Fernández, J. M. Soler, I. L. Garzon, and L. C. Balbás, Phys. Rev. B 0163-1829 70, 165403 (2004). 10.1103/PhysRevB.70. 165403 (Pubitemid 40100495)
39. See supplementary material at http://dx.doi.org/10.1063/1.3369007 E-JCPSA6-132-047012 material for optimum geometries of clusters, structural properties and adsorption energies; statistical measures for testing the success of neural networks; k -fold cross validation analysis for testing the generalization ability of networks; procedure to find the optimum network; change in root mean square error technique for relative significances of variables; multicolinearity analysis for the input and structural properties.
40. D. T. Larose, Data Mining Methods and Models (Wiley, New Jersey, 2006).
41. M. J. Frisch, G. W. Trucks, H. B. Schlegel, GAUSSIAN 03, Revision B.05, Gaussian, Inc., Wallingford, CT, 2004.
42. R. Dennington II, T. Keith, J. Millam, K. Eppinnett, W. L. Hovell, and R. Gilliland, GAUSSVIEW, Version 3.09, Semichem, Inc., Shawnee Mission, KS, 2003.
43. A. D. Becke, J. Chem. Phys. 0021-9606 98, 5648 (1993). 10.1063/1.464913
44. P. J. Hay and W. R. Wadt, J. Chem. Phys. 0021-9606 82, 270 (1985). 10.1063/1.448799
45. A. Prestianni, A. Martorana, I. Ciofini, F. Labat, and C. Adamo, J. Phys. Chem. C 1932-7447 112, 18061 (2008). 10.1021/jp8062959
46. M. Okumura, Y. Kitagawa, M. Haruta, and K. Yamaguchi, Chem. Phys. Lett. 0009-2614 346, 163 (2001). 10.1016/S0009-2614(01)00957-5 (Pubitemid 33396330)
47. D. P. Mandic and J. A. Chambers, Recurrent Neural Networks for Prediction (Wiley, London, 2001). 10.1002/047084535X
48. A. H. Sung, Expert Sys. Applic. 0957-4174 15, 405 (1998). 10.1016/S0957-4174(98)00041-4
49. H. J. Zhai and L. S. Wang, J. Chem. Phys. 0021-9606 122, 051101 (2005). 10.1063/1.1850091 (Pubitemid 41047525)
50. Q. Sun, P. Jena, Y. D. Kim, M. Fischer, and G. Ganteför, J. Chem. Phys. 0021-9606 120, 6510 (2004). 10.1063/1.1666009
51. B. E. Salisbury, W. T. Wallace, and R. L. Whetten, Chem. Phys. 0301-0104 262, 131 (2000). 10.1016/S0301-0104(00)00272-X
52. X. Ding, Z. Li, J. Yang, J. G. Hou, and Q. Zhu, J. Chem. Phys. 0021-9606 120, 9594 (2004). 10.1063/1.1665323
53. G. Mills, M. S. Gordon, and H. Metiu, J. Chem. Phys. 0021-9606 118, 4198 (2003). 10.1063/1.1542879
54. D. M. Cox, R. Brickman, K. Creegan, and A. Kaldor, Z. Phys. D: At., Mol. Clusters 0178-7683 19, 353 (1991). 10.1007/BF01448327
55. D. M. Cox, R. O. Brickman, and K. Creegan, Mater. Res. Soc. Symp. Proc. 0272-9172 206, 34 (1991).