[en] Vibrational spectroscopy is an indispensable analytical tool that provides structural fingerprints for molecules, solids, and interfaces thereof. This study introduces THeSeuSS (THz Spectra Simulations Software)—an automated computational platform that efficiently simulates IR and Raman spectra for both periodic and non-periodic systems. Using DFT, DFTB and machine-learning force field, THeSeuSS offers robust capabilities for detailed vibrational spectra simulations. Our extensive evaluations and benchmarks demonstrate that THeSeuSS accurately reproduces both previously calculated and experimental spectra, enabling precise comparisons and interpretations of vibrational characteristics in various test cases, including H2O and glycine molecules in the gas phase, as well as solid ammonia and solid ibuprofen. Designed with a user-friendly interface and seamless integration with existing computational chemistry tools, THeSeuSS enhances the accessibility and applicability of advanced spectroscopic simulations, supporting research and development in chemical, pharmaceutical, and material sciences.
Disciplines :
Chemistry
Author, co-author :
BOZIKI, Ariadni ; University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS)
Mebenga, Frédéric Ngono; Janssen Research and Development, Pharmaceutical and Material Sciences (PM&S), Janssen Pharmaceutical Companies of Johnson & Johnson, Beerse, Belgium
Fernandes, Philippe; Janssen Research and Development, Pharmaceutical and Material Sciences (PM&S), Janssen Pharmaceutical Companies of Johnson & Johnson, Beerse, Belgium
TKATCHENKO, Alexandre ; University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Physics and Materials Science (DPHYMS)
External co-authors :
yes
Language :
English
Title :
A Journey With THeSeuSS: Automated Python Tool for Modeling IR and Raman Vibrational Spectra of Molecules and Solids
Janssen Pharmaceutica European Research Council Fonds National de la Recherche Luxembourg
Funding text :
This work was supported by the Janssen Pharmaceutica, THESIS3, European Research Council, MACHINE\u2010DRUG, and Fonds National de la Recherche Luxembourg, BroadApp. Funding:Funding: This work was supported by the Janssen Pharmaceutica, THESIS3, European Research Council, MACHINE-DRUG, and Fonds National de la Recherche Luxembourg, BroadApp. The authors extend their gratitude to Dr. Olympia Giannou for her insightful discussions regarding coding queries. Special thanks are also due to Dr. Matteo Barborini for his valuable insights into the code and to Dr. Georgios Kafanas for his guidance on parallelization techniques using slurm. The authors are also grateful to Kyunghoon Han for his assistance with mathematical formulations. Lastly, heartfelt thanks are extended to Dr. Benjamin Hourahine and Dr. Mariana Rossi for their invaluable discussions on the intricacies of the DFTB+ and FHI-aims codes, respectively. The calculations presented in this paper were carried out using the HPC facilities of the University of Luxembourg (see hpc.uni.lu) [137], and the Luxembourg national supercomputer MeluXina. A.B. and A.T. gratefully acknowledge the HPC and LuxProvide teams for their expert support.
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