全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...
-  2018 


DOI: 10.3866/PKU.WHXB201701083

Full-Text   Cite this paper   Add to My Lib

Abstract:

Dye-sensitized solar cells (DSSCs) are one of the most promising renewable energy technologies. Charge transfer and charge transport are pivotal processes in DSSCs, which govern solar energy capture and conversion. These processes can be probed using modern electronic structure methods. Because of the heterogeneity and complexity of the local environment of a chromophore in DSSCs (such as solvatochromism and chromophore aggregation), a part of the solvation environment should be treated explicitly during the calculation. However, because of the high computational cost and unfavorable scaling with the number of electrons of high-level quantum mechanical methods, approaches to explicitly treat the local environment need careful consideration. Two problems must be tackled to reduce computational cost. First, the number of configurations representing the solvent distribution should be limited as much as possible. Second, the size of the explicit region should be kept relatively small. The purpose of this study is to develop efficient computational approaches to select representative configurations and to limit the explicit solvent region to reduce the computational cost for later (higher-level) quantum mechanical calculations. For this purpose, an ensemble of solvent configurations around a 1-methyl-8-oxyquinolinium betaine (QB) dye molecule was generated using Monte Carlo simulations and molecular mechanics force fields. Then, a fitness function was developed using data from inexpensive electronic structure calculations to reduce the number of configurations. Specific solvent molecules were also selected for explicit treatment based on a distance criterion, and those not selected were treated as background charges. The configurations and solvent molecules selected proved to be good representatives of the entire ensemble; thus, expensive electronic structure calculations need to be performed only on this subset of the system, which significantly reduces the computational cost.
Dye-sensitized solar cells (DSSCs) are one of the most promising renewable energy technologies. Charge transfer and charge transport are pivotal processes in DSSCs, which govern solar energy capture and conversion. These processes can be probed using modern electronic structure methods. Because of the heterogeneity and complexity of the local environment of a chromophore in DSSCs (such as solvatochromism and chromophore aggregation), a part of the solvation environment should be treated explicitly during the calculation. However, because of the high computational cost and

References

[1]  1 Ladomenou K. ; Kitsopoulos T. N. ; Sharma G. D. ; Coutsolelos A. G. RSC Adv. 2014, 4, 21379. doi: 10.1039/c4ra00985a
[2]  2 Green M. A. ; Emery K. ; Hishikawa Y. ; Warta W. ; Dunlop E. D. Prog. Photovolt Res. Appl. 2015, 23, 1. doi: 10.1002/pip.2637
[3]  3 Graetzel M. Nature 2001, 414, 338. doi: 10.1038/35104607
[4]  6 Deing K. C. ; Mayerh ffer U. ; Würthner F. ; Meerholz K. Phys. Chem. Chem. Phys. 2012, 14, 8328. doi: 10.1039/c2cp40789b
[5]  8 Pastore M. ; De Angelis F. ACS Nano 2010, 4, 556. doi: 10.1021/nn901518s
[6]  15 Coutinho K. ; De Oliveira M. J. ; Canuto S. Int. J. Quantum Chem. 1998, 66, 249. doi: 10.1002/(SICI)1097-461X(1998)66:3<249::AID-QUA6>3.0.CO;2-V
[7]  16 Jaramillo P. ; Pérez P. ; Fuentealba P. ; Canuto S. ; Coutinho K. J. Phys. Chem. B 2009, 113, 4314. doi: 10.1021/jp808210y
[8]  17 Barreto R. C. ; Coutinho K. ; Georg H. C. ; Canuto S. Phys. Chem. Chem. Phys. 2009, 11, 1388. doi: 10.1039/b816912h
[9]  18 Aidas K. ; Kongsted J. ; Osted A. ; Mikkelsen K. V. ; Christiansen O. J. Phys. Chem. A 2005, 109, 8001. doi: 10.1021/jp0527094
[10]  22 Murugan N. A. J. Phys. Chem. B 2011, 115, 1056. doi: 10.1021/jp1049342
[11]  24 Allen M. P. ; Tildesley D. J. Computer Simulation of Liquids Oxford, UK: Oxford University Press, 1987.
[12]  25 Ewald P. Ann. Phys. 1921, 64, 253. doi: 10.1002/andp.19213690304
[13]  26 Maitland G. C. ; Rigby M. ; Smith E. B. ; Wakeham A. Intermolecular Forces: Their Origin and Determination Oxford, UK: Pergamon Press, 1987.
[14]  29 Marenich A.V ; Olson R. M. ; Kelly C. P. ; Cramer C. J. ; Truhlar D. G. J. Chem. Theory Comput 2007, 3, 2011. doi: 10.1021/ct7001418
[15]  30 Frisch M. J. ; Trucks G. W. ; Schlegel H. B. ; Scuseria G. E. ; Robb M. A. ; Cheeseman J. R. ; Scalmani G. ; Barone V. ; Mennucci B. ; Petersson G. A. ; et al Gaussian 09, Revision D.01 Wallingford, CT, USA: Gaussian Inc, 2013.
[16]  32 Marenich A. V. ; Jerome S. V. ; Cramer C. J. ; Truhlar D. G. J. Chem. Theor. Comput. 2012, 8, 527. doi: 10.1021/ct200866d
[17]  33 Martin M. G. ; Siepmann J. I. J. Phys. Chem. B 1998, 102, 2569. doi: 10.1021/jp972543+
[18]  34 Wick C. D. ; Stubbs J. M. ; Rai N. ; Siepmann J. I. J. Phys. Chem. B 2005, 109, 18974. doi: 10.1021/jp0504827
[19]  37 Zerner M. C. ; Loew G. H. ; Kirchner R. F. ; Mueller-Westerhoff U. T. J. Am. Chem. Soc. 1980, 102, 589. doi: 10.1021/ja00522a025
[20]  40 Lin Y. L. ; Gao J. J. Chem. Theory Comput. 2007, 3, 1484. doi: 10.1021/ct700058c
[21]  4 O'Regan B. ; Graetzel M. Nature 1991, 353, 737. doi: 10.1038/353737a0
[22]  5 Gong J. ; Liang J. ; Sumathy K. Renew. Sust. Energ. Rev. 2012, 16, 5848. doi: 10.1016/j.rser.2012.04.044
[23]  7 Luo L. ; Lin C. -J. ; Tsai C. -Y. ; Wu H. -P. ; Li L. -L. ; Lo C. -F. ; Lin C. -Y. ; Diau E. W. -G. Phys. Chem. Chem. Phys. 2010, 12, 1064. doi: 10.1039/b919962d
[24]  9 El Seoud O. A. Pure Appl. Chem. 2007, 79, 1135. doi: 10.1351/pac200779061135
[25]  10 Tada E. B. ; Novaki L. P. ; El Seoud O. A. J. Phys. Org. Chem. 2000, 13, 679. doi: 10.1002/1099-1395(200011)13:11<679::AID-POC299>3.0.CO;2-R
[26]  21 Marenich A. V. ; Cramer C. J. ; Truhlar D. G. J. Phys. Chem. B 2015, 119, 958. doi: 10.1021/jp506293w
[27]  23 Wood W. W. ; Parker F. R. J. Chem. Phys. 1957, 27, 720. doi: 10.1063/1.1743822
[28]  28 Zhang L. ; Siepmann J. I. Theor. Chem. Acc. 2006, 115, 391. doi: 10.1007/s00214-005-0073-1
[29]  31 Marenich A. V. ; Cramer C. J. ; Truhlar D. G. CM5PAC Minneapolis, MN, USA: Uniersity of Minnesota, 2011.
[30]  36 Thompson M. A. ; Zerner M. C. J. Am. Chem. Soc. 1991, 113, 8210. doi: 10.1021/ja00022a003
[31]  39 Voityuk A. A. ; Kummer A. D. ; Michel-Beyerle M. -E. ; R?sch N. Chem. Phys. 2001, 269, 83. doi: 10.1016/S0301-0104(01)00334-2
[32]  11 Gao J. ; Zhang J. Z. H. ; Houk K. N. Accounts Chem. Res. 2014, 47, 2711. doi: 10.1021/ar500293u
[33]  12 Li S. ; Li W. ; Ma J. Accounts Chem. Res. 2014, 47, 2712. doi: 10.1021/ar500038z
[34]  13 Wang B. ; Yang K. R. ; Xu X. ; Isegawa M. ; Leverentz H. R. ; Truhlar D. G. Accounts Chem. Res. 2014, 47, 2731. doi: 10.1021/ar500068a
[35]  14 He X. ; Zhu T. ; Wang X. ; Liu J. ; Zhang J. Z. H. Accounts Chem. Res. 2014, 47, 2748. doi: 10.1021/ar500077t
[36]  19 Christopher C. Essentials of Computational Chemistry: Theories and Models Chichester, UK: John Wiley & Sons, 2013.
[37]  20 Masunov A. ; Tretiak S. ; Hong J. W. ; Liu B. ; Bazan G. C. J. Chem. Phys. 2005, 122, 224505. doi: 10.1063/1.1878732
[38]  27 Rai N. ; Siepmann J. I. J. Phys. Chem. B 2013, 117, 273. doi: 10.1021/jp307328x
[39]  35 Jorgensen W. L. ; Chandrasekhar J. ; Madura J. D. ; Impey R. W. ; Klein M. L. J. Chem. Phys. 1983, 79, 926. doi: 10.1063/1.445869
[40]  38 Hollas J. M. Modern Spectroscopy Chichester, UK: John Wiley & Sons, 2004.

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133