Cite the OMDB

The OMDB is an academic project, and its development has been published in a number of peer-reviewed papers. If you use the OMDB, its search facilities, servers, data collections, or machine learning tools in your own research, please cite the following paper:

Borysov SS, Geilhufe RM, Balatsky AV, Organic materials database: An open-access online database for data mining, PLoS ONE 12(2), e0171501 (2017), doi: 10.1371/journal.pone.0171501

If you use our magnetic structure dataset, we ask you to cite:

J. Hellsvik, R. Díaz Pérez, R. M. Geilhufe, M. Månsson, A. V. Balatsky, Spin Wave Excitations of Metal Organic Materials, arXiv: 1907.01817 (2019) arXiv: 1907.01817

For downloading the OMDB-GAP1 dataset and for the application of our tool for the machine learning prediction of band gaps, we ask you to cite:

B. Olsthoorn, R. M. Geilhufe, S. S. Borysov, A. V. Balatsky, Band Gap Prediction for Large Organic Crystal Structures with Machine Learning, Advanced Quantum Technologies, 1900023 (2019), doi: 10.1002/qute.201900023

For the application of our band structure pattern matching tools, please refer to:

S. S. Borysov, B. Olsthoorn, M. B. Gedik, R. M. Geilhufe, A. V. Balatsky, Online search tool for graphical patterns in electronic band structures, npj Computational Materials 4, 46 (2018), doi: 10.1038/s41524-018-0104-9

For the application of our density of states similarity search tool, please refer to:

R. M. Geilhufe, S. S. Borysov, D. Kalpakchi, A.V. Balatsky, Towards novel organic high-Tc superconductors: Data mining using density of states similarity search, Physical Review Materials 2:2, 024802 (2018), doi: 10.1103/PhysRevMaterials.2.024802