Understanding Solar Cell Materials Using Spectroscopy and Computational Chemistry
There are a wide variety of materials that have utility in solar cells; these include polymers, small molecules and perovskite structures. It is possible to use computational modelling to improve these materials.1 This is particularly effective when used with spectroscopic analysis because the computational modelling has systematic errors that need calibrated with experiment. For example effective modelling of Raman spectra in donor acceptor systems shows systematic errors depending on the percentage of Hartree-Fock exchange (%HF) used by a functional.2,3 The ability of various density functionals to predict electronic absorption and Raman spectra of oligothiophenes is assessed. A linear relationship between the %HF used and the predicted excitation energy is found. This allows for tuning of hybrid functionals which can accurately predict the bandgap of a given oligomer size. The optimal %HF for the oligomers is found to increase hyperbolically with the number of thiophene units. Range-separated hybrid functionals are found to give consistent result across the range of oligomers whereas hybrid functionals with fixed %HF give differing results based on the oligomer length. The relationship between %HF and calculated Raman frequencies and cross-sections is more complex. Functionals with low %HF give more accurate frequencies but vastly overestimated cross-sections. An understanding of these relationships provides for more insightful use of computational methods as design tools.
References:
1. L. Zhao, P. Wagner, H. van der Salm, T. M. Clarke, K. C. Gordon, S. Mori and A. J. Mozer, J. Phys. Chem. C, 2015, 119, 5350-5363.
2. J. E. Barnsley, G. E. Shillito, C. B. Larsen, H. van der Salm, L. E. Wang, N. T. Lucas and K. C. Gordon, J. Phys. Chem. A, 2016, 120, 1853-1866.
3. M. E. Reish, S. Nam, W. Lee, H. Y. Woo and K. C. Gordon, J. Phys. Chem. C, 2012, 116, 21255-21266.