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Title: Sequential-Optimization-Based Framework for Robust Modeling and Design of Heterogeneous Catalytic Systems

Abstract

Here, we present a general optimization-based framework for (i) ab initio and experimental data driven mechanistic modeling and (ii) optimal catalyst design of heterogeneous catalytic systems. Both cases are formulated as a nonlinear optimization problem that is subject to a mean-field microkinetic model and thermodynamic consistency requirements as constraints, for which we seek sparse solutions through a ridge (L 2 regularization) penalty. The solution procedure involves an iterative sequence of forward simulation of the differential algebraic equations pertaining to the microkinetic model using a numerical tool capable of handling stiff systems, sensitivity calculations using linear algebra, and gradient-based nonlinear optimization. A multistart approach is used to explore the solution space, and a hierarchical clustering procedure is implemented for statistically classifying potentially competing solutions. An example of methanol synthesis through hydrogenation of CO and CO 2 on a Cu-based catalyst is used to illustrate the framework. The framework is fast, is robust, and can be used to comprehensively explore the model solution and design space of any heterogeneous catalytic system.

Authors:
 [1]; ORCiD logo [1]; ORCiD logo [1]
  1. Univ. of Wisconsin-Madison, Madison, WI (United States)
Publication Date:
Research Org.:
Univ. of Wisconsin-Madison, Madison, WI (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Basic Energy Sciences (BES) (SC-22)
OSTI Identifier:
1408149
Alternate Identifier(s):
OSTI ID: 1421604
Grant/Contract Number:
FG02-05ER15731
Resource Type:
Journal Article: Published Article
Journal Name:
Journal of Physical Chemistry. C
Additional Journal Information:
Journal Volume: 121; Journal Issue: 46; Journal ID: ISSN 1932-7447
Publisher:
American Chemical Society
Country of Publication:
United States
Language:
English
Subject:
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY

Citation Formats

Rangarajan, Srinivas, Maravelias, Christos T., and Mavrikakis, Manos. Sequential-Optimization-Based Framework for Robust Modeling and Design of Heterogeneous Catalytic Systems. United States: N. p., 2017. Web. doi:10.1021/acs.jpcc.7b08089.
Rangarajan, Srinivas, Maravelias, Christos T., & Mavrikakis, Manos. Sequential-Optimization-Based Framework for Robust Modeling and Design of Heterogeneous Catalytic Systems. United States. doi:10.1021/acs.jpcc.7b08089.
Rangarajan, Srinivas, Maravelias, Christos T., and Mavrikakis, Manos. Thu . "Sequential-Optimization-Based Framework for Robust Modeling and Design of Heterogeneous Catalytic Systems". United States. doi:10.1021/acs.jpcc.7b08089.
@article{osti_1408149,
title = {Sequential-Optimization-Based Framework for Robust Modeling and Design of Heterogeneous Catalytic Systems},
author = {Rangarajan, Srinivas and Maravelias, Christos T. and Mavrikakis, Manos},
abstractNote = {Here, we present a general optimization-based framework for (i) ab initio and experimental data driven mechanistic modeling and (ii) optimal catalyst design of heterogeneous catalytic systems. Both cases are formulated as a nonlinear optimization problem that is subject to a mean-field microkinetic model and thermodynamic consistency requirements as constraints, for which we seek sparse solutions through a ridge (L2 regularization) penalty. The solution procedure involves an iterative sequence of forward simulation of the differential algebraic equations pertaining to the microkinetic model using a numerical tool capable of handling stiff systems, sensitivity calculations using linear algebra, and gradient-based nonlinear optimization. A multistart approach is used to explore the solution space, and a hierarchical clustering procedure is implemented for statistically classifying potentially competing solutions. An example of methanol synthesis through hydrogenation of CO and CO2 on a Cu-based catalyst is used to illustrate the framework. The framework is fast, is robust, and can be used to comprehensively explore the model solution and design space of any heterogeneous catalytic system.},
doi = {10.1021/acs.jpcc.7b08089},
journal = {Journal of Physical Chemistry. C},
number = 46,
volume = 121,
place = {United States},
year = {Thu Nov 09 00:00:00 EST 2017},
month = {Thu Nov 09 00:00:00 EST 2017}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record at 10.1021/acs.jpcc.7b08089

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Cited by: 1 work
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