Abstract
Inelastic neutron scattering (INS) is a powerful tool to study the vibrational dynamics in a material. The analysis and interpretation of the INS spectra, however, are often nontrivial. Unlike diffraction, for which one can quickly calculate the scattering pattern from the structure, the calculation of INS spectra from the structure involves multiple steps requiring significant experience and computational resources. To overcome this barrier, a database of INS spectra consisting of commonly seen materials will be a valuable reference, and it will also lay the foundation of advanced data-driven analysis and interpretation of INS spectra. Here we report such a database compiled for over 20,000 organic molecules and over 10,000 inorganic crystals. The INS spectra are obtained from a streamlined workflow, and the synthetic INS spectra are also verified by available experimental data. The database is expected to greatly facilitate INS data analysis, and it can also enable the utilization of advanced analytics such as data mining and machine learning. Notice: This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan).
Original language | English |
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Article number | 54 |
Journal | Scientific Data |
Volume | 10 |
Issue number | 1 |
DOIs | |
State | Published - Dec 2023 |
Funding
A portion of this research used resources at the Spallation Neutron Source, a DOE Office of Science User Facility operated by the Oak Ridge National Laboratory (ORNL). The computing resources for INS simulations were made available through the VirtuES and the ICE-MAN projects, funded by Laboratory Directed Research and Development (LDRD) Program and Compute and Data Environment for Science (CADES) at ORNL. The research is also sponsored by the Artificial Intelligence Initiative as part of the LDRD program of ORNL, managed by UT-Battelle, LLC, for the US Department of Energy under contract DE-AC05-00OR22725. A portion of this research used resources at the Spallation Neutron Source, a DOE Office of Science User Facility operated by the Oak Ridge National Laboratory (ORNL). The computing resources for INS simulations were made available through the VirtuES and the ICE-MAN projects, funded by Laboratory Directed Research and Development (LDRD) Program and Compute and Data Environment for Science (CADES) at ORNL. The research is also sponsored by the Artificial Intelligence Initiative as part of the LDRD program of ORNL, managed by UT-Battelle, LLC, for the US Department of Energy under contract DE-AC05-00OR22725.
Funders | Funder number |
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Artificial Intelligence Initiative | |
CADES | |
Data Environment for Science | |
U.S. Department of Energy | DE-AC05-00OR22725 |
Office of Science | |
Oak Ridge National Laboratory | |
Laboratory Directed Research and Development |