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Strong Structure Band Gap Relation in Semiconductors: Implications for Computational Band Gap Prediction

Published online by Cambridge University Press:  29 August 2014

David H. Foster  and
Guenter Schneider
David H. Foster
Affiliation:
Department of Physics, Oregon State University, 301 Weniger Hall, Oregon State University, Corvallis, OR 97331-6507, U.S.A.
Guenter Schneider
Affiliation:
Department of Physics, Oregon State University, 301 Weniger Hall, Oregon State University, Corvallis, OR 97331-6507, U.S.A.
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Abstract

Structure prediction for novel materials requires computationally inexpensive lattice relaxation methods. Prediction of the band gap and excited state properties depends on the accuracy of the relaxations and the sensitivity of the band edges to structural parameters. We examine the relaxation performance of common relaxation methods for several members of the type IB3-V-VI4 copper chalcogenide semiconductors, which have become of recent interest for potential photovoltaic and thermoelectric applications. These materials are members of a larger family of materials, composed of type IB and type VI elements and additional elements acting as cations, which contains structures as complex as Cu12Sb4S13 (tetrahedrite) and may benefit from materials prediction studies. Examining Cu3PS4, Cu3PSe4, Cu3AsS4, and Cu3AsSe4, we find that relaxation induced structural errors cause subsequently calculated band gap values Eg to deviate by as much as 0.6 eV from values obtained using experimentally determined structures. Using the HSE06 hybrid functional we find that the complex V/VI* anti-bonding character of the conduction band minimum creates a band gap sensitivity of order 10 eV/Å to the mean V-VI distance 〈V-VI〉. A weaker correlation between Eg and 〈IB-VI〉 exists due to the Cu-d/Ch-p* character of the valence band maximum (Ch = S, Se). Type IB-III-VI2 materials are known to have similar properties and we include CuInSe2, CuAlS2, and CuAlSe2. Regarding structural relaxation accuracy, we find that GGA+U and meta-GGA functional MS2 typically perform better than GGA (PBE) or PBEsol, but not as well as the much more expensive HSE functional.

Keywords

semiconductingsimulationelectronic structure
Type
Articles
Information
MRS Online Proceedings Library (OPL) , Volume 1704: Symposium QQ – Computationally Enabled Discoveries in Synthesis, Structure and Properties of Nanoscale Materials , 2014 , mrss14-1704-qq09-03
Copyright
Copyright © Materials Research Society 2014 

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References

REFERENCES

Chan, M. K. Y. and Ceder, G., Phys. Rev. Lett., 105, 196403 (2010).10.1103/PhysRevLett.105.196403CrossRefGoogle Scholar
Yu, L. and Zunger, A., Phys. Rev. Lett. 108, 068701 (2012).10.1103/PhysRevLett.108.068701CrossRefGoogle Scholar
Setywan, W. and Curtarolo, S., Comput. Mat. Sci. 49, 299 (2010).10.1016/j.commatsci.2010.05.010CrossRefGoogle Scholar
Jaffe, J. A. and Zunger, Alex, Phys. Rev. B 29, 1882 (1984).10.1103/PhysRevB.29.1882CrossRefGoogle Scholar
Vidal, J., Botti, S., Olsson, P., Guillemoles, J-F., and Reining, L, Phys. Rev. Lett. 104, 056401 (2010).10.1103/PhysRevLett.104.056401CrossRefGoogle Scholar
Zhang, Y., Yuan, X., Sun, X., Shih, B-C., Zhang, P, and Zhang, W., Phys. Rev. B 84, 075127 (2011).10.1103/PhysRevB.84.075127CrossRefGoogle Scholar
Foster, D. H., Jieratum, V., Kykyneshi, R., Keszler, D. A., and Schneider, G., Appl. Phys. Lett. 99 181903 (2011).10.1063/1.3656760CrossRefGoogle Scholar
Do, D., Ozolins, V., Mahanti, S. D., Lee, M-S., Zhang, Y, and Wolverton, C., J. Phys.: Condens. Matter 24, 415502 (2012).Google Scholar
Do, D. and Mahanti, S. D., arXiv:1306.0503v3 (2013).Google Scholar
Heyd, J., Scuseria, G. E., and Ernzerhof, M., J. Chem. Phys. 118, 8207 (2003); ibid. 124, 219906(2006).10.1063/1.1564060CrossRefGoogle Scholar
Kokenyesi, Robert (private communication).Google Scholar
Perdew, J. P., Burke, K., and Ernzerhof, M., Phys. Rev. Lett. 77, 3865.10.1103/PhysRevLett.77.3865CrossRefGoogle Scholar
Perdew, J. P., Ruzsinszky, A., Csonka, G. I., Vydrov, O. A., Scuseria, G. E., Constantin, L. A., Zhou, X., and Burke, K., Phys. Rev. Lett. 100, 136406 (2008).10.1103/PhysRevLett.100.136406CrossRefGoogle Scholar
Persson, C., Zhao, Y. J., Lany, S., and Zunger, A., Phys. Rev. B 72, 035211 (2005).10.1103/PhysRevB.72.035211CrossRefGoogle Scholar
Sun, J., Xiao, B., Fang, Y., Haunschild, R., Hao, P., Ruzsinszky, A., Csonka, G. I., Scuseria, G. E., and Perdew, J. P., Phys. Rev. Lett. 111, 106401 (2013).10.1103/PhysRevLett.111.106401CrossRefGoogle Scholar
Bloechl, P. E., Phys. Rev. B 50, 17953 (1994).10.1103/PhysRevB.50.17953CrossRefGoogle Scholar
Kresse, G. and Joubert, D., Phys. Rev. B 59, 1758 (1999).10.1103/PhysRevB.59.1758CrossRefGoogle Scholar
Pfitzner, A. and Reiser, S., Z. Kristallogr. 217, 51–54 (2002).Google Scholar
Ma, H-W., Guo, G-C., Zhou, G-W., Wang, M-S., Lin, S-H., Dong, Z-C., and Huang, J-S., Chinese J. Struct. Chem. 21, 288–291 (2002).Google Scholar
Berger, L. I. and Prochukhan, V. D., “Ternary Diamond-like Semiconductors”, Consultants Bureau, 1969.Google Scholar
Gaines, R. V., Am. Mineral. 42, 766 (1957).Google Scholar
Pfitzner, A. and Bernert, T., Z. Kristallogr. 219, 20 (2004).Google Scholar
Rabadanov, M. Kh. and Verlin, I. A., Inorgan. Mat. 34, 14 (1998).Google Scholar
Bondar (Bodnar), I. V., Karoza, A. G., and Smirnova, G. F., Inorgan. Mat. 21, 964 (1985).Google Scholar
Spiess, H. W., Haeberln, V., Brandt, G., Rauber, A., and Schneider, J., Phys. Status Solidi B 62, 183 (1974).10.1002/pssb.2220620118CrossRefGoogle Scholar