Crossref journal-article
Springer Science and Business Media LLC
Scientific Data (297)
Abstract

AbstractWe present a new open repository for chemical reactions on catalytic surfaces, available at https://www.catalysis-hub.org. The featured database for surface reactions contains more than 100,000 chemisorption and reaction energies obtained from electronic structure calculations, and is continuously being updated with new datasets. In addition to providing quantum-mechanical results for a broad range of reactions and surfaces from different publications, the database features a systematic, large-scale study of chemical adsorption and hydrogenation on bimetallic alloy surfaces. The database contains reaction specific information, such as the surface composition and reaction energy for each reaction, as well as the surface geometries and calculational parameters, essential for data reproducibility. By providing direct access via the web-interface as well as a Python API, we seek to accelerate the discovery of catalytic materials for sustainable energy applications by enabling researchers to efficiently use the data as a basis for new calculations and model generation.

Bibliography

Winther, K. T., Hoffmann, M. J., Boes, J. R., Mamun, O., Bajdich, M., & Bligaard, T. (2019). Catalysis-Hub.org, an open electronic structure database for surface reactions. Scientific Data, 6(1).

Authors 6
  1. Kirsten T. Winther (first)
  2. Max J. Hoffmann (additional)
  3. Jacob R. Boes (additional)
  4. Osman Mamun (additional)
  5. Michal Bajdich (additional)
  6. Thomas Bligaard (additional)
References 52 Referenced 236
  1. Haunschild, R., Barth, A. & Marx, W. Evolution of DFT studies in view of a scientometric perspective. Journal of Cheminformatics 8, 52 (2016). (10.1186/s13321-016-0166-y) / Journal of Cheminformatics by R Haunschild (2016)
  2. Medford, A. J., Kunz, M. R., Ewing, S. M., Borders, T. & Fushimi, R. Extracting knowledge from data through catalysis informatics. ACS Catalysis 8, 7403–7429 (2018). (10.1021/acscatal.8b01708) / ACS Catalysis by AJ Medford (2018)
  3. Bo, C., Maseras, F. & López, N. The role of computational results databases in accelerating the discovery of catalysts. Nature Catalysis 1, 809 (2018). (10.1038/s41929-018-0176-4) / Nature Catalysis by C Bo (2018)
  4. Wilkinson, M. D. et al. The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data 3, 160018 (2016). (10.1038/sdata.2016.18) / Scientific Data by MD Wilkinson (2016)
  5. Jain, A. et al. The materials project: a materials genome approach to accelerating materials innovation. APL Materials 1, 011002 (2013). (10.1063/1.4812323) / APL Materials by A Jain (2013)
  6. Kirklin, S. et al. The Open Quantum Materials Database (OQMD): Assessing the accuracy of DFT formation energies. npj Computational Materials 1, 15010 (2015). (10.1038/npjcompumats.2015.10) / npj Computational Materials by S Kirklin (2015)
  7. Draxl, C. & Scheffler, M. NOMAD: The FAIR concept for big data-driven materials science. MRS Bulletin 43, 676–682 (2018). (10.1557/mrs.2018.208) / MRS Bulletin by C Draxl (2018)
  8. Curtarolo, S. et al. AFLOW: An Automatic Framework for High-Throughput Materials Discovery. Computational Materials Science 58, 218–226 (2012). (10.1016/j.commatsci.2012.02.005) / Computational Materials Science by S Curtarolo (2012)
  9. Álvarez-Moreno, M. et al. Managing the computational chemistry big data problem: the ioChem-BD platform. Journal of Chemical Information and Modeling 55, 95–103 (2014). (10.1021/ci500593j) / Journal of Chemical Information and Modeling by M Álvarez-Moreno (2014)
  10. Landis, D. D. et al. The computational materials repository. Computing in Science & Engineering 14, 51 (2012). (10.1109/MCSE.2012.16) / Computing in Science & Engineering by DD Landis (2012)
  11. Haastrup, S. et al. The computational 2D materials database: High-throughput modeling and discovery of atomically thin crystals. 2D Materials 5, 042002 (2018). (10.1088/2053-1583/aacfc1) / 2D Materials by S Haastrup (2018)
  12. Schmidt, P. S. & Thygesen, K. S. Benchmark database of transition metal surface and adsorption energies from many-body perturbation theory. The Journal of Physical Chemistry C 122, 4381–4390 (2018). (10.1021/acs.jpcc.7b12258) / The Journal of Physical Chemistry C by PS Schmidt (2018)
  13. Hummelshøj, J. S., Abild-Pedersen, F., Studt, F., Bligaard, T. & Nørskov, J. K. CatApp: a web application for surface chemistry and heterogeneous catalysis. Angewandte Chemie International Edition 51, 272–274 (2012). (10.1002/anie.201107947) / Angewandte Chemie International Edition by JS Hummelshøj (2012)
  14. Boes, J. R., Mamun, O., Winther, K. & Bligaard, T. Graph theory approach to high-throughput surface adsorption structure generation. The Journal of Physical Chemistry A 123, 2281–2285 (2019). (10.1021/acs.jpca.9b00311) / The Journal of Physical Chemistry A by JR Boes (2019)
  15. Hansen, M. H. et al. An Atomistic Machine Learning Package for Surface Science and Catalysis Preprint at, https://arxiv.org/abs/1904.00904 (2019).
  16. Jennings, P. et al. CatLearn. Zenodo, https://doi.org/10.5281/zenodo.2601873 (2019). (10.5281/zenodo.2601873) by P. Jennings (2019)
  17. Subramani, V. & Gangwal, S. K. A review of recent literature to search for an efficient catalytic process for the conversion of syngas to ethanol. Energy & Fuels 22, 814–839 (2008). (10.1021/ef700411x) / Energy & Fuels by V Subramani (2008)
  18. Schumann, J. et al. Selectivity of synthesis gas conversion to C2+ oxygenates on fcc(111) transition-metal surfaces. ACS Catalysis 8, 3447–3453 (2018). (10.1021/acscatal.8b00201) / ACS Catalysis by J Schumann (2018)
  19. Debe, M. K. Electrocatalyst approaches and challenges for automotive fuel cells. Nature 486, 43 (2012). (10.1038/nature11115) / Nature by MK Debe (2012)
  20. Back, S., Kulkarni, A. R. & Siahrostami, S. Single metal atoms anchored in two-dimensional materials: Bifunctional catalysts for fuel cell applications. Chem Cat Chem 10, 3034–3039 (2018). (10.1002/cctc.201800447) / ChemCatChem by S Back (2018)
  21. Lu, Z. et al. Identifying the Active Surfaces of Electrochemically Tuned LiCoO2 for Oxygen Evolution Reaction. Journal of the American Chemical Society 139, 6270–6276 (2017). (10.1021/jacs.7b02622) / Journal of the American Chemical Society by Z Lu (2017)
  22. Nørskov, J. K., Bligaard, T., Rossmeisl, J. & Christensen, C. H. Towards the computational design of solid catalysts. Nature Chemistry 1, 37 (2009). (10.1038/nchem.121) / Nature Chemistry by JK Nørskov (2009)
  23. Chen, L. D. et al. Understanding the apparent fractional charge of protons in the aqueous electrochemical double layer. Nature Communications 9, 3202 (2018). (10.1038/s41467-018-05511-y) / Nature Communications by LD Chen (2018)
  24. Patel, A. M. et al. Theoretical approaches to describing the oxygen reduction reaction activity of single atom catalysts. The Journal of Physical Chemistry C 122, 29307–29318 (2019). (10.1021/acs.jpcc.8b09430) / The Journal of Physical Chemistry C by AM Patel (2019)
  25. Mamun, O., Winther, K. T., Boes, J. R. & Bligaard, T. High-throughput calculations of catalytic properties of bimetallic alloy surfaces. Scientific Data 6, 80 (2019). (10.1038/s41597-019-0080-z)
  26. Mamun, O., Winther, K. T., Boes, J. R. & Bligaard, T. High-throughput calculations of catalytic properties of bimetallic alloy surfaces. Materials Cloud Archive, https://doi.org/10.24435/materialscloud:2019.0015/v1 (2019). (10.24435/materialscloud:2019.0015/v1) by O Mamun (2019)
  27. Pettifor, D. G. A chemical scale for crystal-structure maps. Solid State Communications 51, 31–34 (1984). (10.1016/0038-1098(84)90765-8) / Solid State Communications by DG Pettifor (1984)
  28. Glawe, H., Sanna, A., Gross, E. & Marques, M. A. The optimal one dimensional periodic table: a modified Pettifor chemical scale from data mining. New Journal of Physics 18, 093011 (2016). (10.1088/1367-2630/18/9/093011) / New Journal of Physics by H Glawe (2016)
  29. Giannozzi, P. et al. Advanced capabilities for materials modelling with QUANTUM ESPRESSO. Journal of Physics: Condensed Matter 29, 465901 (2017). / Journal of Physics: Condensed Matter by P Giannozzi (2017)
  30. Kresse, G. & Furthmüller, J. Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set. Computational Materials Science 6, 15–50 (1996). (10.1016/0927-0256(96)00008-0) / Computational Materials Science by G Kresse (1996)
  31. Kresse, G. & Furthmüller, J. Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set. Physical Review B 54, 11169 (1996). (10.1103/PhysRevB.54.11169) / Physical Review B by G Kresse (1996)
  32. Enkovaara, J. E. et al. Electronic structure calculations with GPAW: a real-space implementation of the projector augmented-wave method. Journal of Physics: Condensed Matter 22, 253202 (2010). / Journal of Physics: Condensed Matter by JE Enkovaara (2010)
  33. Wellendorff, J. et al. Density functionals for surface science: Exchange-correlation model development with bayesian error estimation. Physical Review B 85, 235149 (2012). (10.1103/PhysRevB.85.235149) / Physical Review B by J Wellendorff (2012)
  34. Wellendorff, J. et al. A benchmark database for adsorption bond energies to transition metal surfaces and comparison to selected dft functionals. Surface Science 640, 36–44 (2015). (10.1016/j.susc.2015.03.023) / Surface Science by J Wellendorff (2015)
  35. Mallikarjun Sharada, S., Bligaard, T., Luntz, A. C., Kroes, G.-J. & Nørskov, J. K. Sbh10: A benchmark database of barrier heights on transition metal surfaces. The Journal of Physical Chemistry C 121, 19807–19815 (2017). (10.1021/acs.jpcc.7b05677) / The Journal of Physical Chemistry C by S Mallikarjun Sharada (2017)
  36. Hammer, B., Hansen, L. B. & Nørskov, J. K. Improved adsorption energetics within density-functional theory using revised Perdew-Burke-Ernzerhof functionals. Physical Review B 59, 7413 (1999). (10.1103/PhysRevB.59.7413) / Physical Review B by B Hammer (1999)
  37. Perdew, J. P., Burke, K. & Ernzerhof, M. Generalized gradient approximation made simple. Physical Review Letters 77, 3865 (1996). (10.1103/PhysRevLett.77.3865) / Physical Review Letters by JP Perdew (1996)
  38. Liechtenstein, A., Anisimov, V. & Zaanen, J. Density-functional theory and strong interactions: Orbital ordering in Mott-Hubbard insulators. Physical Review B 52, R5467 (1995). (10.1103/PhysRevB.52.R5467) / Physical Review B by A Liechtenstein (1995)
  39. Winther, K. T. et al. CatHub: A Python API for the Surface Reactions Database on Catalysis-Hub.org. Zenodo, https://doi.org/10.5281/zenodo.2600391 (2019). (10.5281/zenodo.2600391) by K.T. Winther (2019)
  40. Larsen, A. H. et al. The atomic simulation environment—a Python library for working with atoms. Journal of Physics: Condensed Matter 29, 273002 (2017). / Journal of Physics: Condensed Matter by AH Larsen (2017)
  41. Nørskov, J. K. et al. Universality in heterogeneous catalysis. Journal of Catalysis 209, 275–278 (2002). (10.1006/jcat.2002.3615) / Journal of Catalysis by JK Nørskov (2002)
  42. Garrido Torres, J. A., Jennings, P. C., Hansen, M. H., Boes, J. R. & Bligaard, T. Low-Scaling Algorithm for Nudged Elastic Band Calculations Using a Surrogate Machine Learning Model. Physical Review Letters 122, 156001 (2019). (10.1103/PhysRevLett.122.156001)
  43. Medford, A. J. et al. Catmap: a software package for descriptor-based microkinetic mapping of catalytic trends. Catalysis Letters 145, 794–807 (2015). (10.1007/s10562-015-1495-6) / Catalysis Letters by AJ Medford (2015)
  44. Decker, S. et al. The semantic web: The roles of XML and RDF. IEEE Internet computing 4, 63–73 (2000). (10.1109/4236.877487) / IEEE Internet computing by S Decker (2000)
  45. Wang, B., Dobosh, P. A., Chalk, S., Sopek, M. & Ostlund, N. S. Computational chemistry data management platform based on the semantic web. The Journal of Physical Chemistry A 121, 298–307 (2016). (10.1021/acs.jpca.6b10489) / The Journal of Physical Chemistry A by B Wang (2016)
  46. Hall, S. R. & McMahon, B. International tables for crystallography, definition and exchange of crystallographic data, vol. 8 (Springer Science & Business Media, 2005). (10.1107/97809553602060000107)
  47. Hall, S. R. & McMahon, B. The implementation and evolution of STAR/CIF ontologies: interoperability and preservation of structured data. Data Science Journal 15 (2016). (10.5334/dsj-2016-003)
  48. Heller, S. R., McNaught, A., Pletnev, I., Stein, S. & Tchekhovskoi, D. Inchi, the IUPAC international chemical identifier. Journal of Cheminformatics 7, 23 (2015). (10.1186/s13321-015-0068-4) / Journal of Cheminformatics by SR Heller (2015)
  49. Grethe, G., Blanke, G., Kraut, H. & Goodman, J. M. International chemical identifier for reactions (RINCHI). Journal of Cheminformatics 10, 22, https://doi.org/10.1186/s13321-018-0277-8 (2018). (10.1186/s13321-018-0277-8) / Journal of Cheminformatics by G Grethe (2018)
  50. Hoffmann, M. et al. CatalysisHubFrontend: A React frontent for Catalysis-Hub.org. Zenodo, https://doi.org/10.5281/zenodo.2605378 (2019). (10.5281/zenodo.2605378) by M. Hoffmann (2019)
  51. Burger, M. C. Chemdoodle web components: HTML5 toolkit for chemical graphics, interfaces, and informatics. Journal of Cheminformatics 7, 35 (2015). (10.1186/s13321-015-0085-3) / Journal of Cheminformatics by MC Burger (2015)
  52. Hoffmann, M. et al. CatalysisHubBackend: A Python backend for the Catalysis-Hub.org platform. Zenodo, https://doi.org/10.5281/zenodo.2600445 (2019). (10.5281/zenodo.2600445) by M. Hoffmann (2019)
Dates
Type When
Created 6 years, 3 months ago (May 28, 2019, 6:04 a.m.)
Deposited 2 years, 8 months ago (Dec. 16, 2022, 11:18 p.m.)
Indexed 2 days, 2 hours ago (Aug. 27, 2025, 12:07 p.m.)
Issued 6 years, 3 months ago (May 28, 2019)
Published 6 years, 3 months ago (May 28, 2019)
Published Online 6 years, 3 months ago (May 28, 2019)
Funders 1
  1. DOE | SC | Basic Energy Sciences 10.13039/100006151 Basic Energy Sciences

    Region: Americas

    gov (National government)

    Labels6
    1. Office of Basic Energy Sciences
    2. DOE Office of Basic Energy Sciences
    3. US Department of Energy's Basic Energy Sciences
    4. DOE Basic Energy Sciences
    5. Department of Energy Basic Energy Sciences Program
    6. BES
    Awards1
    1. DE-AC02-76SF00515

@article{Winther_2019, title={Catalysis-Hub.org, an open electronic structure database for surface reactions}, volume={6}, ISSN={2052-4463}, url={http://dx.doi.org/10.1038/s41597-019-0081-y}, DOI={10.1038/s41597-019-0081-y}, number={1}, journal={Scientific Data}, publisher={Springer Science and Business Media LLC}, author={Winther, Kirsten T. and Hoffmann, Max J. and Boes, Jacob R. and Mamun, Osman and Bajdich, Michal and Bligaard, Thomas}, year={2019}, month=may }