Development, characterization, and modeling of a high-performance Ru/B2CA catalyst for ammonia synthesis

Canan Karakaya; Jake Huang; Christopher Cadigan; Adam Welch; Jonathan Kintner; Joseph Beach; Huayang Zhu; Ryan O'Hayre; Robert J. Kee

doi:10.1016/j.ces.2021.116902

Development, characterization, and modeling of a high-performance Ru/B2CA catalyst for ammonia synthesis

Canan Karakaya, Jake Huang, Christopher Cadigan, Adam Welch, Jonathan Kintner, Joseph Beach, Huayang Zhu, Ryan O'Hayre, Robert J. Kee

Chemical Process Scale Up

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10 Scopus citations

Abstract

This paper documents the development and performance of a nano-phase Ru catalyst on a (BaO)_x(CaO)_y(Al₂O₃)_z support. Extensive screening of the support's ternary composition shows the best stoichiometry is (BaO)₂(CaO)(Al₂O₃), denoted B2CA. The paper first describes catalyst preparation and characterization. The paper reports a detailed 12-step reaction mechanism that represents ammonia synthesis over wide ranges of temperature, pressure, space velocity, and feed composition. The mechanism is developed and validated using results of packed-bed experiments. The elementary reaction pathways consider surface adsorbates, including catalyst-poisoning behaviors. The rate expressions include important coverage-dependent activation barriers. Machine learning models assist interpretation of the catalyst-support interactions. The detailed chemistry is much more predictive than is possible with global representations (N₂+3H₂⇌2NH₃). The validated models can be applied to assist optimizing reactor design and operating conditions.

Original language	English
Article number	116902
Journal	Chemical Engineering Science
Volume	247
DOIs	https://doi.org/10.1016/j.ces.2021.116902
State	Published - Jan 16 2022

Funding

This work was supported by the Advanced Research Projects Agency-Energy (ARPA-E) through the REFUEL program (Award No. DE-AR0000808) and OPEN program (Award No. DE-AR0000685).

Keywords

Ammonia synthesis
Heterogeneous catalysis
Machine learning
Microkinetics
Packed-bed reactor
Ru/B2CA

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10.1016/j.ces.2021.116902

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title = "Development, characterization, and modeling of a high-performance Ru/B2CA catalyst for ammonia synthesis",

abstract = "This paper documents the development and performance of a nano-phase Ru catalyst on a (BaO)x(CaO)y(Al2O3)z support. Extensive screening of the support's ternary composition shows the best stoichiometry is (BaO)2(CaO)(Al2O3), denoted B2CA. The paper first describes catalyst preparation and characterization. The paper reports a detailed 12-step reaction mechanism that represents ammonia synthesis over wide ranges of temperature, pressure, space velocity, and feed composition. The mechanism is developed and validated using results of packed-bed experiments. The elementary reaction pathways consider surface adsorbates, including catalyst-poisoning behaviors. The rate expressions include important coverage-dependent activation barriers. Machine learning models assist interpretation of the catalyst-support interactions. The detailed chemistry is much more predictive than is possible with global representations (N2+3H2⇌2NH3). The validated models can be applied to assist optimizing reactor design and operating conditions.",

keywords = "Ammonia synthesis, Heterogeneous catalysis, Machine learning, Microkinetics, Packed-bed reactor, Ru/B2CA",

author = "Canan Karakaya and Jake Huang and Christopher Cadigan and Adam Welch and Jonathan Kintner and Joseph Beach and Huayang Zhu and Ryan O'Hayre and Kee, {Robert J.}",

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AU - Karakaya, Canan

AU - Huang, Jake

AU - Cadigan, Christopher

AU - Welch, Adam

AU - Kintner, Jonathan

AU - Beach, Joseph

AU - Zhu, Huayang

AU - O'Hayre, Ryan

AU - Kee, Robert J.

PY - 2022/1/16

Y1 - 2022/1/16

N2 - This paper documents the development and performance of a nano-phase Ru catalyst on a (BaO)x(CaO)y(Al2O3)z support. Extensive screening of the support's ternary composition shows the best stoichiometry is (BaO)2(CaO)(Al2O3), denoted B2CA. The paper first describes catalyst preparation and characterization. The paper reports a detailed 12-step reaction mechanism that represents ammonia synthesis over wide ranges of temperature, pressure, space velocity, and feed composition. The mechanism is developed and validated using results of packed-bed experiments. The elementary reaction pathways consider surface adsorbates, including catalyst-poisoning behaviors. The rate expressions include important coverage-dependent activation barriers. Machine learning models assist interpretation of the catalyst-support interactions. The detailed chemistry is much more predictive than is possible with global representations (N2+3H2⇌2NH3). The validated models can be applied to assist optimizing reactor design and operating conditions.

AB - This paper documents the development and performance of a nano-phase Ru catalyst on a (BaO)x(CaO)y(Al2O3)z support. Extensive screening of the support's ternary composition shows the best stoichiometry is (BaO)2(CaO)(Al2O3), denoted B2CA. The paper first describes catalyst preparation and characterization. The paper reports a detailed 12-step reaction mechanism that represents ammonia synthesis over wide ranges of temperature, pressure, space velocity, and feed composition. The mechanism is developed and validated using results of packed-bed experiments. The elementary reaction pathways consider surface adsorbates, including catalyst-poisoning behaviors. The rate expressions include important coverage-dependent activation barriers. Machine learning models assist interpretation of the catalyst-support interactions. The detailed chemistry is much more predictive than is possible with global representations (N2+3H2⇌2NH3). The validated models can be applied to assist optimizing reactor design and operating conditions.

KW - Ammonia synthesis

KW - Heterogeneous catalysis

KW - Machine learning

KW - Microkinetics

KW - Packed-bed reactor

KW - Ru/B2CA

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DO - 10.1016/j.ces.2021.116902

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SN - 0009-2509

VL - 247

JO - Chemical Engineering Science

JF - Chemical Engineering Science

M1 - 116902

ER -

Development, characterization, and modeling of a high-performance Ru/B2CA catalyst for ammonia synthesis

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