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High-throughput computation of Raman spectra from first principles

Mohammad Bagheri1*, Hannu-Pekka Komsa1*

1 Microelectronics Research Unit, Faculty of Information Technology and Electrical Engineering, University of Oulu, Oulu, FIN-90014, Finland

* Corresponding authors emails: mohammad.bagheri@oulu.fi, hannu-pekka.komsa@oulu.fi
DOI10.24435/materialscloud:ze-58 [version v1]

Publication date: Aug 21, 2022

How to cite this record

Mohammad Bagheri, Hannu-Pekka Komsa, High-throughput computation of Raman spectra from first principles, Materials Cloud Archive 2022.104 (2022), doi: 10.24435/materialscloud:ze-58.


Raman spectroscopy is a widely-used non-destructive material characterization method, which provides information about the vibrational modes of the material and therefore of its atomic structure and chemical composition. Raman spectra can be simulated using atomistic first-principles methods but these are computationally demanding and thus the existing databases of computational Raman spectra are fairly small. We developed an optimized workflow to efficiently calculate the Raman tensors, from which the Raman spectra can be straightforwardly simulated. The workflow was benchmarked and validated by comparison to experiments and previous computational methods for select technologically relevant material systems. Using the workflow, we performed high-throughput calculations for a large set of materials (5099) belonging to many different material classes, and collected the results to a database.

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File name Size Description
145.7 MiB JSON file containing calculated Raman tensors, vibrational information and selected material properties for 5099 materials


Files and data are licensed under the terms of the following license: Creative Commons Attribution 4.0 International.
Metadata, except for email addresses, are licensed under the Creative Commons Attribution Share-Alike 4.0 International license.

External references

M. Bagheri, H.-P. Komsa, In preparation


Raman tensors density-functional theory high-throughput

Version history:

2022.104 (version v1) [This version] Aug 21, 2022 DOI10.24435/materialscloud:ze-58