Michelle A. Nolen^1,2, Sean A. Tacey¹, Martha A. Arellano-Treviño¹, Kurt M. Van Allsburg¹, Carrie A. Farberow^1*

1 Catalytic Carbon Transformation & Scale-Up Center, National Renewable Energy Laboratory, Golden, CO 80401, United States

2 Department of Chemical and Biological Engineering, Colorado School of Mines, Golden, CO 80401, United States

* Corresponding authors emails: carrie.farberow@nrel.gov

DOI10.24435/materialscloud:kr-m2 [version v2]

Publication date: Aug 27, 2024

How to cite this record

Michelle A. Nolen, Sean A. Tacey, Martha A. Arellano-Treviño, Kurt M. Van Allsburg, Carrie A. Farberow, High-throughput dataset of impurity adsorption on common catalysts in biomass upgrading applications, Materials Cloud Archive 2024.129 (2024), https://doi.org/10.24435/materialscloud:kr-m2

Description

An extensive dataset consisting of adsorption energies of pernicious impurities present in biomass upgrading processes on common catalysts and support materials has been generated. This work aims to inform catalyst and process development for the conversion of biomass-derived feedstocks to fuels and chemicals. A high-throughput workflow was developed to execute density functional theory calculations for a diverse set of atomic (Al, B, Ca, Cl, Fe, K, Mg, Mn, N, Na, P, S, Si, Zn) and molecular (COS, H₂S, HCl, HCN, K₂O, KCl, NH₃) species on 35 unique surfaces for transition-metal (Ag, Au, Co, Cu, Fe, Ir, Ni, Pd, Pt, Re, Rh, Ru) and metal-oxide (Al₂O₃, MgO, anatase-TiO₂, rutile-TiO₂, ZnO, ZrO₂) catalysts and supports. Approximately 3,000 unique adsorption geometries were obtained. The data record includes structure and calculation output files for each unique adsorbate geometry on each surface.

Materials Cloud sections using this data

Files

File name	Size	Description
Ag_100.tgz MD5md5:49fffe9b6ddf38ea95b42b432511174c	74.6 MiB	CONTCARs and OUTCARS
Ag_111.tgz MD5md5:a03cb90c00e3f190a8edb0059617cd25	276.4 MiB	CONTCARs and OUTCARs
Ag_211.tgz MD5md5:73bda9a539764d36e222789bda826c29	467.4 MiB	CONTCARs and OUTCARs
Al2O3_0001.tgz MD5md5:3fccdd1c59ef085ebee62e578394be5c	381.5 MiB	CONTCARs and OUTCARs
aTiO2_101.tgz MD5md5:515ae2763eee5d24f28c97f58b898716	832.6 MiB	CONTCARs and OUTCARs
Au_100.tgz MD5md5:b792688981ef601420a69b231a1408f1	75.6 MiB	CONTCARs and OUTCARs
Au_111.tgz MD5md5:9b4b1048e74d2e9eecdc086d85ad657b	197.1 MiB	CONTCARs and OUTCARs
Au_211.tgz MD5md5:ef63a0a958eabb01745878774611662a	434.2 MiB	CONTCARs and OUTCARs
Co_0001.tgz MD5md5:335576d6283db15e85d1de2679f6636e	164.1 MiB	CONTCARs and OUTCARs
Cu_100.tgz MD5md5:b6c41ccbec5f392034261517ba6c90a2	54.8 MiB	CONTCARs and OUTCARs
Cu_111.tgz MD5md5:061b51cfd339bffd6c87574d18c882d6	160.8 MiB	CONTCARs and OUTCARs
Cu_211.tgz MD5md5:722f91c5aaf82bb8f81b748f0d91d037	282.8 MiB	CONTCARs and OUTCARs
Fe_110.tgz MD5md5:073a2fa63e2f5e70fcbd8a0c037c6954	96.3 MiB	CONTCARs and OUTCARs
Ir_100.tgz MD5md5:101d3a3c9d42daf13e9c2105679a15bf	51.5 MiB	CONTCARs and OUTCARs
Ir_111.tgz MD5md5:220815375d2ff488f73f2d868e44b0eb	156.6 MiB	CONTCARs and OUTCARs
Ir_211.tgz MD5md5:b2718777dbbf65c8986a410f24418874	175.6 MiB	CONTCARs and OUTCARs
MgO_100.tgz MD5md5:8ab8a985d41b4ba93fe2f907620c87ba	52.9 MiB	CONTCARs and OUTCARs
Ni_100.tgz MD5md5:bac3ac1abdbacb509289566667b64e27	84.6 MiB	CONTCARs and OUTCARs
Ni_111.tgz MD5md5:b865f02398846875ce759a96709ca410	193.6 MiB	CONTCARs and OUTCARs
Ni_211.tgz MD5md5:b0f79edc1348b57eb29b73e05eeed473	233.6 MiB	CONTCARs and OUTCARs
Pd_100.tgz MD5md5:4ca36108c165696b59c45f7df8036cf7	69.2 MiB	CONTCARs and OUTCARs
Pd_111.tgz MD5md5:8c5505ebcf3e05a290b5b1be9960beb1	226.6 MiB	CONTCARs and OUTCARs
Pt_211.tgz MD5md5:a925c7040ceed070022e0965a7f4f483	236.9 MiB	CONTCARs and OUTCARs
Pt_100.tgz MD5md5:de9da3cd3220b926621b855b566204d2	54.2 MiB	CONTCARs and OUTCARs
Pt_111.tgz MD5md5:e8e29112db258216c06e2e2140df5260	183.3 MiB	CONTCARs and OUTCARs
Pd_211.tgz MD5md5:b12a4d51ef1d2c2635bea6a0db3371d0	271.0 MiB	CONTCARs and OUTCARs
Re_0001.tgz MD5md5:1f9279388abfa4c797aaf0cc2054f36a	193.8 MiB	CONTCARs and OUTCARs
Rh_100.tgz MD5md5:16359087430617b903b99ee1523cf236	51.5 MiB	CONTCARs and OUTCARs
Rh_111.tgz MD5md5:aebbaf1d7eb1a3d9eddbd3d9e6bce27a	168.9 MiB	CONTCARs and OUTCARs
Rh_211.tgz MD5md5:ddeb0d02206175f5b678f44eb8db69d9	197.2 MiB	CONTCARs and OUTCARs
rTiO2_110.tgz MD5md5:b25cc3c05a5ea33c09585f6bbee25852	834.7 MiB	CONTCARs and OUTCARs
Ru_0001.tgz MD5md5:5fe11cee3054d34438944066355e5049	136.5 MiB	CONTCARs and OUTCARs
ZnO_1010.tgz MD5md5:a4696b00525b0c91139c57a7bbe064f8	229.8 MiB	CONTCARs and OUTCARs
ZnO_1120.tgz MD5md5:9dc77595a608a9648030158ae53fb7f0	418.4 MiB	CONTCARs and OUTCARs
ZrO2_111.tgz MD5md5:3fc501522ce0c85c050d9b9b52c0471f	2.8 GiB	CONTCARs and OUTCARs
README.txt MD5md5:1533bd3e64a097d4f823606f7d141635	1.4 KiB	Guide to directory organization.
CPD impurity adsorption dataset.json MD5md5:825b87bf860dfadedda966d7f0c73658	6.9 MiB	JSON file containing the parsed dataset ‘High-throughput dataset of impurity adsorption on common catalysts in biomass upgrading applications’ in the Catalyst Property Database (https://cpd.chemcatbio.org/search_database) data structure

License

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

Keywords

density-functional theory high-throughput VASP