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Ostace A, Chen YY, Parker R, Mebane DS, Okoli CO, Lee A, Tong A, Fan LS, Biegler LT, Burgard AP, Miller DC, Bhattacharyya D. Kinetic model development and Bayesian uncertainty quantification for the complete reduction of Fe-based oxygen carriers with CH4, CO, and H2 for chemical looping combustion. Chem Eng Sci 2022. [DOI: 10.1016/j.ces.2022.117512] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
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2
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Pineda M, Stamatakis M. Kinetic Monte Carlo simulations for heterogeneous catalysis: Fundamentals, current status, and challenges. J Chem Phys 2022; 156:120902. [DOI: 10.1063/5.0083251] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
Kinetic Monte Carlo (KMC) simulations in combination with first-principles (1p)-based calculations are rapidly becoming the gold-standard computational framework for bridging the gap between the wide range of length scales and time scales over which heterogeneous catalysis unfolds. 1p-KMC simulations provide accurate insights into reactions over surfaces, a vital step toward the rational design of novel catalysts. In this Perspective, we briefly outline basic principles, computational challenges, successful applications, as well as future directions and opportunities of this promising and ever more popular kinetic modeling approach.
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Affiliation(s)
- M. Pineda
- Thomas Young Centre and Department of Chemical Engineering, University College London, Roberts Building, Torrington Place, London WC1E 7JE, United Kingdom
| | - M. Stamatakis
- Thomas Young Centre and Department of Chemical Engineering, University College London, Roberts Building, Torrington Place, London WC1E 7JE, United Kingdom
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3
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Calvo F, Gómez JM, Alvarez O, Ricardez-Sandoval L. Trends and perspectives on emulsified product design. Curr Opin Chem Eng 2022. [DOI: 10.1016/j.coche.2021.100745] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
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4
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Chaffart D, Shi S, Ma C, Lv C, Ricardez-Sandoval LA. A Moving Front Kinetic Monte Carlo Algorithm for Moving Interface Systems. J Phys Chem B 2022; 126:2040-2059. [PMID: 35196012 DOI: 10.1021/acs.jpcb.1c10389] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
This work presents the development of a new kinetic Monte Carlo algorithm, referred to as Moving Front kinetic Monte Carlo (MFkMC), for simulating processes subject to moving interfaces. This framework is designed to capture the movement of transiently varying interfaces in a kinetic-like manner so that its movement can be described using Monte Carlo sampling. The MFkMC algorithm accomplishes this task by evaluating the behavior of the interfacial molecules and assigning kinetic Monte Carlo-style rate equations that describe the transition probability that a molecule would advance into the neighboring phase, displacing an interfacial molecule from the opposing phase and thus changing the interface. Due to its kinetic Monte Carlo structure, the MFkMC algorithm can additionally account for other important interfacial phenomena, such as interfacial surface reactions. The proposed algorithm was tested via applications to three different simple interfacial case studies. These studies validate the MFkMC algorithm and demonstrate its capabilities to accurately and efficiently simulate a variety of different moving interface systems.
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Affiliation(s)
- Donovan Chaffart
- Department of Chemical Engineering, University of Waterloo, Waterloo N2L 3G1, Canada
| | - Songlin Shi
- Department of Engineering Mechanics, Tsinghua University, Beijing 100084, China
| | - Chen Ma
- Department of Engineering Mechanics, Tsinghua University, Beijing 100084, China
| | - Cunjing Lv
- Department of Engineering Mechanics, Tsinghua University, Beijing 100084, China
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5
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Jung J, Choi HK, Son SH, Kwon JSI, Lee JH. Multiscale modeling of fiber deformation: Application to a batch pulp digester for model predictive control of fiber strength. Comput Chem Eng 2022. [DOI: 10.1016/j.compchemeng.2021.107640] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
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6
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Chaffart D, Ricardez-Sandoval LA. A three dimensional kinetic Monte Carlo defect-free crystal dissolution model for biological systems, with application to uncertainty analysis and robust optimization. Comput Chem Eng 2022. [DOI: 10.1016/j.compchemeng.2021.107586] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
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7
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Chen W, Cohen M, Yu K, Wang HL, Zheng W, Vlachos DG. Experimental data-driven reaction network identification and uncertainty quantification of CO2-assisted ethane dehydrogenation over Ga2O3/Al2O3. Chem Eng Sci 2021. [DOI: 10.1016/j.ces.2021.116534] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
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8
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Calvo F, Gómez JM, Ricardez-Sandoval L, Alvarez O. Integrated design of emulsified cosmetic products: A review. Chem Eng Res Des 2020. [DOI: 10.1016/j.cherd.2020.07.014] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
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9
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Kimaev G, Ricardez-Sandoval LA. Artificial Neural Networks for dynamic optimization of stochastic multiscale systems subject to uncertainty. Chem Eng Res Des 2020. [DOI: 10.1016/j.cherd.2020.06.017] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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10
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Kimaev G, Chaffart D, Ricardez‐Sandoval LA. Multilevel Monte Carlo applied for uncertainty quantification in stochastic multiscale systems. AIChE J 2020. [DOI: 10.1002/aic.16262] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Affiliation(s)
- Grigoriy Kimaev
- Deparment of Chemical EngineeringUniversity of Waterloo Waterloo Ontario Canada
| | - Donovan Chaffart
- Deparment of Chemical EngineeringUniversity of Waterloo Waterloo Ontario Canada
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11
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Zhang M, Zijlstra B, Filot IAW, Li F, Wang H, Li J, Hensen EJM. A theoretical study of the reverse water‐gas shift reaction on Ni(111) and Ni(311) surfaces. CAN J CHEM ENG 2019. [DOI: 10.1002/cjce.23655] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Affiliation(s)
- Min Zhang
- Hebei Provincial Key Laboratory of Green Chemical Technology and High Efficient Energy Saving, School of Chemical Engineering and TechnologyHebei University of Technology Tianjin China
- Laboratory of Inorganic Materials and Catalysis, Schuit Institute of Catalysis, Department of Chemical Engineering and ChemistryEindhoven University of Technology Eindhoven The Netherlands
| | - Bart Zijlstra
- Laboratory of Inorganic Materials and Catalysis, Schuit Institute of Catalysis, Department of Chemical Engineering and ChemistryEindhoven University of Technology Eindhoven The Netherlands
| | - Ivo A. W. Filot
- Laboratory of Inorganic Materials and Catalysis, Schuit Institute of Catalysis, Department of Chemical Engineering and ChemistryEindhoven University of Technology Eindhoven The Netherlands
| | - Fang Li
- Hebei Provincial Key Laboratory of Green Chemical Technology and High Efficient Energy Saving, School of Chemical Engineering and TechnologyHebei University of Technology Tianjin China
| | - Haiou Wang
- Hebei Provincial Key Laboratory of Green Chemical Technology and High Efficient Energy Saving, School of Chemical Engineering and TechnologyHebei University of Technology Tianjin China
| | - Jingde Li
- Hebei Provincial Key Laboratory of Green Chemical Technology and High Efficient Energy Saving, School of Chemical Engineering and TechnologyHebei University of Technology Tianjin China
| | - Emiel J. M. Hensen
- Laboratory of Inorganic Materials and Catalysis, Schuit Institute of Catalysis, Department of Chemical Engineering and ChemistryEindhoven University of Technology Eindhoven The Netherlands
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12
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Kimaev G, Ricardez-Sandoval LA. Nonlinear model predictive control of a multiscale thin film deposition process using artificial neural networks. Chem Eng Sci 2019. [DOI: 10.1016/j.ces.2019.07.044] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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13
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Urrea-Quintero JH, Ochoa S, Hernández H. A reduced-order multiscale model of a free-radical semibatch emulsion polymerization process. Comput Chem Eng 2019. [DOI: 10.1016/j.compchemeng.2019.04.029] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
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14
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Matera S, Schneider WF, Heyden A, Savara A. Progress in Accurate Chemical Kinetic Modeling, Simulations, and Parameter Estimation for Heterogeneous Catalysis. ACS Catal 2019. [DOI: 10.1021/acscatal.9b01234] [Citation(s) in RCA: 94] [Impact Index Per Article: 18.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Sebastian Matera
- Fachbereich Mathematik and Informatik, Freie Universität, 14195 Berlin, Germany
| | - William F. Schneider
- Department of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, Indiana 46556, United States
| | - Andreas Heyden
- Department of Chemical Engineering, University of South Carolina, Columbia, South Carolina 29208, United States
| | - Aditya Savara
- Chemical Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37830, United States
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15
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Sivaramakrishnan K, Puliyanda A, Tefera DT, Ganesh A, Thirumalaivasan S, Prasad V. A Perspective on the Impact of Process Systems Engineering on Reaction Engineering. Ind Eng Chem Res 2019. [DOI: 10.1021/acs.iecr.9b00280] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
Affiliation(s)
- Kaushik Sivaramakrishnan
- Department of Chemical and Materials Engineering, University of Alberta, Edmonton, AB T6G 2R3, Canada
| | - Anjana Puliyanda
- Department of Chemical and Materials Engineering, University of Alberta, Edmonton, AB T6G 2R3, Canada
| | - Dereje Tamiru Tefera
- Department of Chemical and Materials Engineering, University of Alberta, Edmonton, AB T6G 2R3, Canada
| | - Ajay Ganesh
- Department of Chemical and Materials Engineering, University of Alberta, Edmonton, AB T6G 2R3, Canada
| | - Sushmitha Thirumalaivasan
- Department of Chemical and Materials Engineering, University of Alberta, Edmonton, AB T6G 2R3, Canada
| | - Vinay Prasad
- Department of Chemical and Materials Engineering, University of Alberta, Edmonton, AB T6G 2R3, Canada
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16
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Cerrillo-Briones IM, Ricardez-Sandoval LA. Robust optimization of a post-combustion CO2 capture absorber column under process uncertainty. Chem Eng Res Des 2019. [DOI: 10.1016/j.cherd.2019.02.020] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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17
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Optimization and control of a thin film growth process: A hybrid first principles/artificial neural network based multiscale modelling approach. Comput Chem Eng 2018. [DOI: 10.1016/j.compchemeng.2018.08.029] [Citation(s) in RCA: 57] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
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18
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Lee D, Mohr A, Kwon JSI, Wu HJ. Kinetic Monte Carlo modeling of multivalent binding of CTB proteins with GM1 receptors. Comput Chem Eng 2018. [DOI: 10.1016/j.compchemeng.2018.08.011] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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19
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Kimaev G, Ricardez‐Sandoval LA. Multilevel Monte Carlo applied to chemical engineering systems subject to uncertainty. AIChE J 2017. [DOI: 10.1002/aic.16045] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Affiliation(s)
- Grigoriy Kimaev
- Dept. of Chemical EngineeringUniversity of WaterlooWaterloo Ontario Canada N2L 3G1
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20
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Ahmadian Behrooz H. Robust synthesis of the pressure-swing distillation process under azeotropic feed composition disturbance—Study of the tetrahydrofuran/methanol system. Comput Chem Eng 2017. [DOI: 10.1016/j.compchemeng.2017.04.022] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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21
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Chaffart D, Ricardez-Sandoval LA. Robust optimization of a multiscale heterogeneous catalytic reactor system with spatially-varying uncertainty descriptions using polynomial chaos expansions. CAN J CHEM ENG 2017. [DOI: 10.1002/cjce.22912] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Affiliation(s)
- Donovan Chaffart
- Department of Chemical Engineering; University of Waterloo; Waterloo ON N2L 3G1 Canada
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22
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Kimaev G, Ricardez-Sandoval LA. A comparison of efficient uncertainty quantification techniques for stochastic multiscale systems. AIChE J 2017. [DOI: 10.1002/aic.15702] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Affiliation(s)
- Grigoriy Kimaev
- Dept. of Chemical Engineering; University of Waterloo; Waterloo ON Canada N2L 3G1
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