High-Throughput Dataset of Impurity Adsorption on Common Catalysts in Biomass Upgrading Applications: Article No. 1049

Michelle Nolen; Sean Tacey; Martha Arellano-Trevino; Kurt Van Allsburg; Carrie Farberow

doi:10.1038/s41597-024-03872-2

High-Throughput Dataset of Impurity Adsorption on Common Catalysts in Biomass Upgrading Applications: Article No. 1049

Michelle Nolen, Sean Tacey, Martha Arellano-Trevino, Kurt Van Allsburg, Carrie Farberow

Catalytic Carbon Transformation and Scale-Up Center

Research output: Contribution to journal › Article › peer-review

Abstract

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 and corresponding adsorption energies were obtained.

Original language	American English
Number of pages	9
Journal	Scientific Data
Volume	11
DOIs	https://doi.org/10.1038/s41597-024-03872-2
State	Published - 2024

NREL Publication Number

NREL/JA-5100-89792

Keywords

biomass conversion
catalyst
computational chemistry
density functional theory
impurity

Access to Document

10.1038/s41597-024-03872-2

https://www.nrel.gov/docs/fy25osti/89792.pdf

Cite this

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title = "High-Throughput Dataset of Impurity Adsorption on Common Catalysts in Biomass Upgrading Applications: Article No. 1049",

abstract = "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 and corresponding adsorption energies were obtained.",

keywords = "biomass conversion, catalyst, computational chemistry, density functional theory, impurity",

author = "Michelle Nolen and Sean Tacey and Martha Arellano-Trevino and {Van Allsburg}, Kurt and Carrie Farberow",

year = "2024",

doi = "10.1038/s41597-024-03872-2",

language = "American English",

volume = "11",

journal = "Scientific Data",

issn = "2052-4463",

publisher = "Nature Research",

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T1 - High-Throughput Dataset of Impurity Adsorption on Common Catalysts in Biomass Upgrading Applications

T2 - Article No. 1049

AU - Nolen, Michelle

AU - Tacey, Sean

AU - Arellano-Trevino, Martha

AU - Van Allsburg, Kurt

AU - Farberow, Carrie

PY - 2024

Y1 - 2024

N2 - 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 and corresponding adsorption energies were obtained.

AB - 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 and corresponding adsorption energies were obtained.

KW - biomass conversion

KW - catalyst

KW - computational chemistry

KW - density functional theory

KW - impurity

U2 - 10.1038/s41597-024-03872-2

DO - 10.1038/s41597-024-03872-2

M3 - Article

SN - 2052-4463

VL - 11

JO - Scientific Data

JF - Scientific Data

ER -

High-Throughput Dataset of Impurity Adsorption on Common Catalysts in Biomass Upgrading Applications: Article No. 1049

Abstract

NREL Publication Number

Keywords

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