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Micale D, Bracconi M, Maestri M. Increasing Computational Efficiency of CFD Simulations of Reactive Flows at Catalyst Surfaces through Dynamic Load Balancing. ACS ENGINEERING AU 2024; 4:312-324. [PMID: 38911942 PMCID: PMC11191586 DOI: 10.1021/acsengineeringau.3c00066] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Revised: 12/27/2023] [Accepted: 12/28/2023] [Indexed: 06/25/2024]
Abstract
We propose a numerical strategy based on dynamic load balancing (DLB) aimed at enhancing the computational efficiency of multiscale CFD simulation of reactive flows at catalyst surfaces. Our approach employs DLB combined with a hybrid parallelization technique, integrating both MPI and OpenMP protocols. This results in an optimized distribution of the computational load associated with the chemistry solution across processors, thereby minimizing computational overheads. Through assessments conducted on fixed and fluidized bed reactor simulations, we demonstrated a remarkable improvement of the parallel efficiency from 19 to 87% and from 19 to 91% for the fixed and fluidized bed, respectively. Owing to this improved parallel efficiency, we observe a significant computational speed-up of 1.9 and 2.1 in the fixed and fluidized bed reactor simulations, respectively, compared to simulations without DLB. All in all, the proposed approach is able to improve the computational efficiency of multiscale CFD simulations paving the way for a more efficient exploitation of high-performance computing resources and expanding the current boundaries of feasible simulations.
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Affiliation(s)
- Daniele Micale
- Laboratory of Catalysis and
Catalytic Processes, Dipartimento di Energia, Politecnico di Milano, via La Masa 34, 20156 Milano, Italy
| | - Mauro Bracconi
- Laboratory of Catalysis and
Catalytic Processes, Dipartimento di Energia, Politecnico di Milano, via La Masa 34, 20156 Milano, Italy
| | - Matteo Maestri
- Laboratory of Catalysis and
Catalytic Processes, Dipartimento di Energia, Politecnico di Milano, via La Masa 34, 20156 Milano, Italy
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2
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Sabadell-Rendón A, Kaźmierczak K, Morandi S, Euzenat F, Curulla-Ferré D, López N. Automated MUltiscale simulation environment. DIGITAL DISCOVERY 2023; 2:1721-1732. [PMID: 38054103 PMCID: PMC10694852 DOI: 10.1039/d3dd00163f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/23/2023] [Accepted: 11/05/2023] [Indexed: 12/07/2023]
Abstract
Multiscale techniques integrating detailed atomistic information on materials and reactions to predict the performance of heterogeneous catalytic full-scale reactors have been suggested but lack seamless implementation. The largest challenges in the multiscale modeling of reactors can be grouped into two main categories: catalytic complexity and the difference between time and length scales of chemical and transport phenomena. Here we introduce the Automated MUltiscale Simulation Environment AMUSE, a workflow that starts from Density Functional Theory (DFT) data, automates the analysis of the reaction networks through graph theory, prepares it for microkinetic modeling, and subsequently integrates the results into a standard open-source Computational Fluid Dynamics (CFD) code. We demonstrate the capabilities of AMUSE by applying it to the unimolecular iso-propanol dehydrogenation reaction and then, increasing the complexity, to the pre-commercial Pd/In2O3 catalyst employed for the CO2 hydrogenation to methanol. The results show that AMUSE allows the computational investigation of heterogeneous catalytic reactions in a comprehensive way, providing essential information for catalyst design from the atomistic to the reactor scale level.
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Affiliation(s)
- Albert Sabadell-Rendón
- Institute of Chemical Research of Catalonia (ICIQ-CERCA), The Barcelona Institute of Science and Technology, (BIST) Av. Paisos Catalans 16 Tarragona 43007 Spain
| | - Kamila Kaźmierczak
- TotalEnergies, TotalEnergies One Tech Belgium Zone industrielle C, 7181 Feluy Belgium
| | - Santiago Morandi
- Institute of Chemical Research of Catalonia (ICIQ-CERCA), The Barcelona Institute of Science and Technology, (BIST) Av. Paisos Catalans 16 Tarragona 43007 Spain
- Department of Physical and Inorganic Chemistry, Universitat Rovira i Virgili Campus Sescelades, N4 Block, C. Marcel·lí Domingo 1 Tarragona 43007 Spain
| | - Florian Euzenat
- TotalEnergies Research and Technology Gonfreville, Route Industrielle, Carrefour 4, Port 4864 76700 Rogerville France
| | - Daniel Curulla-Ferré
- TotalEnergies, TotalEnergies One Tech Belgium Zone industrielle C, 7181 Feluy Belgium
| | - Núria López
- Institute of Chemical Research of Catalonia (ICIQ-CERCA), The Barcelona Institute of Science and Technology, (BIST) Av. Paisos Catalans 16 Tarragona 43007 Spain
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3
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Kreitz B, Lott P, Studt F, Medford AJ, Deutschmann O, Goldsmith CF. Automated Generation of Microkinetics for Heterogeneously Catalyzed Reactions Considering Correlated Uncertainties. Angew Chem Int Ed Engl 2023; 62:e202306514. [PMID: 37505449 DOI: 10.1002/anie.202306514] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Revised: 07/06/2023] [Accepted: 07/26/2023] [Indexed: 07/29/2023]
Abstract
The study presents an ab-initio based framework for the automated construction of microkinetic mechanisms considering correlated uncertainties in all energetic parameters and estimation routines. 2000 unique microkinetic models were generated within the uncertainty space of the BEEF-vdW functional for the oxidation reactions of representative exhaust gas emissions from stoichiometric combustion engines over Pt(111) and compared to experiments through multiscale modeling. The ensemble of simulations stresses the importance of considering uncertainties. Within this set of first-principles-based models, it is possible to identify a microkinetic mechanism that agrees with experimental data. This mechanism can be traced back to a single exchange-correlation functional, and it suggests that Pt(111) could be the active site for the oxidation of light hydrocarbons. The study provides a universal framework for the automated construction of reaction mechanisms with correlated uncertainty quantification, enabling a DFT-constrained microkinetic model optimization for other heterogeneously catalyzed systems.
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Affiliation(s)
- Bjarne Kreitz
- School of Engineering, Brown University, 184 Hope Street, Providence, RI, 02912, USA
- Institute for Chemical Technology and Polymer Chemistry, Karlsruhe Institute of Technology, Engesserstr. 20, 76128, Karlsruhe, Germany
| | - Patrick Lott
- Institute for Chemical Technology and Polymer Chemistry, Karlsruhe Institute of Technology, Engesserstr. 20, 76128, Karlsruhe, Germany
| | - Felix Studt
- Institute for Chemical Technology and Polymer Chemistry, Karlsruhe Institute of Technology, Engesserstr. 20, 76128, Karlsruhe, Germany
- Institute of Catalysis Research and Technology, Karlsruhe Institute of Technology, 76344, Eggenstein-Leopoldshafen, Germany
| | - Andrew J Medford
- School of Chemical and Biomolecular Engineering, Atlanta, GA, 30318, USA
| | - Olaf Deutschmann
- Institute for Chemical Technology and Polymer Chemistry, Karlsruhe Institute of Technology, Engesserstr. 20, 76128, Karlsruhe, Germany
| | - C Franklin Goldsmith
- School of Engineering, Brown University, 184 Hope Street, Providence, RI, 02912, USA
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Rajan A, Pushkar AP, Dharmalingam BC, Varghese JJ. Iterative multiscale and multi-physics computations for operando catalyst nanostructure elucidation and kinetic modeling. iScience 2023; 26:107029. [PMID: 37360694 PMCID: PMC10285649 DOI: 10.1016/j.isci.2023.107029] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/28/2023] Open
Abstract
Modern heterogeneous catalysis has benefitted immensely from computational predictions of catalyst structure and its evolution under reaction conditions, first-principles mechanistic investigations, and detailed kinetic modeling, which are rungs on a multiscale workflow. Establishing connections across these rungs and integration with experiments have been challenging. Here, operando catalyst structure prediction techniques using density functional theory simulations and ab initio thermodynamics calculations, molecular dynamics, and machine learning techniques are presented. Surface structure characterization by computational spectroscopic and machine learning techniques is then discussed. Hierarchical approaches in kinetic parameter estimation involving semi-empirical, data-driven, and first-principles calculations and detailed kinetic modeling via mean-field microkinetic modeling and kinetic Monte Carlo simulations are discussed along with methods and the need for uncertainty quantification. With these as the background, this article proposes a bottom-up hierarchical and closed loop modeling framework incorporating consistency checks and iterative refinements at each level and across levels.
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Affiliation(s)
- Ajin Rajan
- Department of Chemical Engineering, Indian Institute of Technology Madras, Chennai, Tamil Nadu 600036, India
| | - Anoop P. Pushkar
- Department of Chemical Engineering, Indian Institute of Technology Madras, Chennai, Tamil Nadu 600036, India
| | - Balaji C. Dharmalingam
- Department of Chemical Engineering, Indian Institute of Technology Madras, Chennai, Tamil Nadu 600036, India
| | - Jithin John Varghese
- Department of Chemical Engineering, Indian Institute of Technology Madras, Chennai, Tamil Nadu 600036, India
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Kreitz B, Abeywardane K, Goldsmith CF. Linking Experimental and Ab Initio Thermochemistry of Adsorbates with a Generalized Thermochemical Hierarchy. J Chem Theory Comput 2023. [PMID: 37354113 DOI: 10.1021/acs.jctc.3c00112] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/26/2023]
Abstract
Enthalpies of formation of adsorbates are crucial parameters in the microkinetic modeling of heterogeneously catalyzed reactions since they quantify the stability of intermediates on the catalyst surface. This quantity is often computed using density functional theory (DFT), as more accurate methods are computationally still too expensive, which means that the derived enthalpies have a large uncertainty. In this study, we propose a new error cancellation method to compute the enthalpies of formation of adsorbates from DFT more accurately through a generalized connectivity-based hierarchy. The enthalpy of formation is determined through a hypothetical reaction that preserves atomistic and bonding environments. The method is applied to a data set of 60 adsorbates on Pt(111) with up to 4 heavy (non-hydrogen) atoms. Enthalpies of formation of the fragments required for the bond balancing reactions are based on experimental heats of adsorption for Pt(111). The comparison of enthalpies of formation derived from different DFT functionals using the isodesmic reactions shows that the effect of the functional is significantly reduced due to the error cancellation. Thus, the proposed methodology creates an interconnected thermochemical network of adsorbates that combines experimental with ab initio thermochemistry in a single and more accurate thermophysical database.
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Affiliation(s)
- Bjarne Kreitz
- School of Engineering, Brown University, Providence, Rhode Island 02912, United States
| | - Kento Abeywardane
- School of Engineering, Brown University, Providence, Rhode Island 02912, United States
| | - C Franklin Goldsmith
- School of Engineering, Brown University, Providence, Rhode Island 02912, United States
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Exploring catalytic reaction networks with machine learning. Nat Catal 2023. [DOI: 10.1038/s41929-022-00896-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
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7
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The future of computational fluid dynamics (CFD) simulation in the chemical process industries. Chem Eng Res Des 2022. [DOI: 10.1016/j.cherd.2022.09.021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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Kreitz B, Lott P, Bae J, Blöndal K, Angeli S, Ulissi ZW, Studt F, Goldsmith CF, Deutschmann O. Detailed Microkinetics for the Oxidation of Exhaust Gas Emissions through Automated Mechanism Generation. ACS Catal 2022. [DOI: 10.1021/acscatal.2c03378] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Bjarne Kreitz
- School of Engineering, Brown University, Providence, Rhode Island 02912, United States
- Institute for Chemical Technology and Polymer Chemistry, Karlsruhe Institute of Technology, 76131 Karlsruhe, Germany
| | - Patrick Lott
- Institute for Chemical Technology and Polymer Chemistry, Karlsruhe Institute of Technology, 76131 Karlsruhe, Germany
| | - Jongyoon Bae
- School of Engineering, Brown University, Providence, Rhode Island 02912, United States
| | - Katrín Blöndal
- School of Engineering, Brown University, Providence, Rhode Island 02912, United States
| | - Sofia Angeli
- Institute for Chemical Technology and Polymer Chemistry, Karlsruhe Institute of Technology, 76131 Karlsruhe, Germany
| | - Zachary W. Ulissi
- Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, United States
| | - Felix Studt
- Institute for Chemical Technology and Polymer Chemistry, Karlsruhe Institute of Technology, 76131 Karlsruhe, Germany
- Institute of Catalysis Research and Technology, Karlsruhe Institute of Technology, 76344 Eggenstein-Leopoldshafen, Germany
| | - C. Franklin Goldsmith
- School of Engineering, Brown University, Providence, Rhode Island 02912, United States
| | - Olaf Deutschmann
- Institute for Chemical Technology and Polymer Chemistry, Karlsruhe Institute of Technology, 76131 Karlsruhe, Germany
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