Title: Biomass HDO Catalysts Innovation from Atomistic Activity Predictors - data
Citation
Morteo-Flores F, Engel J, Roldan A (2020). Biomass HDO Catalysts Innovation from Atomistic Activity Predictors - data. Cardiff University. https://doi.org/10.17035/d.2020.0104938086
Access Rights: Data is provided under a Creative Commons Attribution (CC BY 4.0) licence
Access Method: https://doi.org/10.17035/d.2020.0104938086 will take you to the repository page for this dataset, where you will be able to download the data or find further access information, as appropriate.
Dataset Details
Publisher: Cardiff University
Date (year) of data becoming publicly available: 2020
Coverage start date: 01/04/2020
Coverage end date: 03/04/2020
Data format: xlsx
Software Required: The .xlsx file can be viewed with Microsoft Excel or free programs such as OpenOffice or LibreOffice
Estimated total storage size of dataset: Less than 100 megabytes
Number of Files In Dataset: 1
DOI : 10.17035/d.2020.0104938086
DOI URL: http://doi.org/10.17035/d.2020.0104938086
This dataset was produced un course of a density functional theory (DFT) study exploring the relationship between twelve transition metals (TMs) properties, as catalysts, and their affinity for hydrogen and oxygen, as key species in the valorisation of biomass. The Excel file (.xlsx) contains the hydrogen and oxygen adsorption energies (in eV), and different transition properties such as surface energy (in J m-2), work function, d-band width, centre (in Å) Research results based upon these data are published at https://doi.org/10.1098/rsta.2020.0056
Description
Keywords
Green Chemistry
Related Projects
- Computational modelling of the formation and stability of supported particles of catalytic importance (01/01/2016 - 02/01/2018)
