Geometrical and optical benchmarking of copper guanidine-quinoline complexes: Insights from TD-DFT and many-body perturbation theory†

A. Jesser, M. Rohrmüller, W.G. Schmidt, S. Herres-Pawlis, Journal of Computational Chemistry 35 (2013) 1–17.

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Journal Article | Published | English
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Journal of Computational Chemistry
Volume
35
Issue
1-2
Page
1-17
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Jesser A, Rohrmüller M, Schmidt WG, Herres-Pawlis S. Geometrical and optical benchmarking of copper guanidine-quinoline complexes: Insights from TD-DFT and many-body perturbation theory†. Journal of Computational Chemistry. 2013;35(1-2):1-17. doi:10.1002/jcc.23449
Jesser, A., Rohrmüller, M., Schmidt, W. G., & Herres-Pawlis, S. (2013). Geometrical and optical benchmarking of copper guanidine-quinoline complexes: Insights from TD-DFT and many-body perturbation theory†. Journal of Computational Chemistry, 35(1–2), 1–17. https://doi.org/10.1002/jcc.23449
@article{Jesser_Rohrmüller_Schmidt_Herres-Pawlis_2013, title={Geometrical and optical benchmarking of copper guanidine-quinoline complexes: Insights from TD-DFT and many-body perturbation theory†}, volume={35}, DOI={10.1002/jcc.23449}, number={1–2}, journal={Journal of Computational Chemistry}, author={Jesser, Anton and Rohrmüller, Martin and Schmidt, Wolf Gero and Herres-Pawlis, Sonja}, year={2013}, pages={1–17} }
Jesser, Anton, Martin Rohrmüller, Wolf Gero Schmidt, and Sonja Herres-Pawlis. “Geometrical and Optical Benchmarking of Copper Guanidine-Quinoline Complexes: Insights from TD-DFT and Many-Body Perturbation Theory†.” Journal of Computational Chemistry 35, no. 1–2 (2013): 1–17. https://doi.org/10.1002/jcc.23449.
A. Jesser, M. Rohrmüller, W. G. Schmidt, and S. Herres-Pawlis, “Geometrical and optical benchmarking of copper guanidine-quinoline complexes: Insights from TD-DFT and many-body perturbation theory†,” Journal of Computational Chemistry, vol. 35, no. 1–2, pp. 1–17, 2013.
Jesser, Anton, et al. “Geometrical and Optical Benchmarking of Copper Guanidine-Quinoline Complexes: Insights from TD-DFT and Many-Body Perturbation Theory†.” Journal of Computational Chemistry, vol. 35, no. 1–2, 2013, pp. 1–17, doi:10.1002/jcc.23449.

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