1
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Yokaichiya T, Ikeda T, Muraoka K, Nakayama A. On-the-fly kinetic Monte Carlo simulations with neural network potentials for surface diffusion and reaction. J Chem Phys 2024; 160:204108. [PMID: 38785283 DOI: 10.1063/5.0199240] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2024] [Accepted: 05/05/2024] [Indexed: 05/25/2024] Open
Abstract
We develop an adaptive scheme in the kinetic Monte Carlo simulations, where the adsorption and activation energies of all elementary steps, including the effects of other adsorbates, are evaluated "on-the-fly" by employing the neural network potentials. The configurations and energies evaluated during the simulations are stored for reuse when the same configurations are sampled in a later step. The present scheme is applied to hydrogen adsorption and diffusion on the Pd(111) and Pt(111) surfaces and the CO oxidation reaction on the Pt(111) surface. The effects of interactions between adsorbates, i.e., adsorbate-adsorbate lateral interactions, are examined in detail by comparing the simulations without considering lateral interactions. This study demonstrates the importance of lateral interactions in surface diffusion and reactions and the potential of our scheme for applications in a wide variety of heterogeneous catalytic reactions.
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Affiliation(s)
- Tomoko Yokaichiya
- Department of Chemical System Engineering, The University of Tokyo, Tokyo 113-8656, Japan
| | - Tatsushi Ikeda
- Department of Chemical System Engineering, The University of Tokyo, Tokyo 113-8656, Japan
| | - Koki Muraoka
- Department of Chemical System Engineering, The University of Tokyo, Tokyo 113-8656, Japan
| | - Akira Nakayama
- Department of Chemical System Engineering, The University of Tokyo, Tokyo 113-8656, Japan
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2
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Li XY, Ou P, Duan X, Ying L, Meng J, Zhu B, Gao Y. Dynamic Active Sites In Situ Formed in Metal Nanoparticle Reshaping under Reaction Conditions. JACS AU 2024; 4:1892-1900. [PMID: 38818067 PMCID: PMC11134379 DOI: 10.1021/jacsau.4c00088] [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: 01/30/2024] [Revised: 04/11/2024] [Accepted: 04/12/2024] [Indexed: 06/01/2024]
Abstract
Understanding the nonequilibrium transformation of nanocatalysts under reaction conditions is important because metastable atomic structures may be created during the process, which offers unique activities in reactions. Although reshaping of metal nanoparticles (NPs) under reaction conditions has been widely recognized, the dynamic reshaping process has been less studied at the atomic scale. Here, we develop an atomistic kinetic Monte Carlo model to simulate the complete reshaping process of Pt nanoparticles in a CO environment and reveal the in situ formation of atomic clusters on the NP surface, a new type of active site beyond conventional understanding, boosting the reactivities in the CO oxidation reaction. Interestingly, highly active peninsula and inactive island clusters both form on the (111) facets and interchange in varying states of dynamic equilibrium, which influences the catalytic activities significantly. This study provides new fundamental knowledge of nanocatalysis and new guidance for the rational design of nanocatalysts.
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Affiliation(s)
- Xiao-Yan Li
- Shanghai
Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800, China
- Department
of Chemistry, Northwestern University, Evanston, Illinois 60208, United States
| | - Pengfei Ou
- Department
of Chemistry, Northwestern University, Evanston, Illinois 60208, United States
| | - Xinyi Duan
- Shanghai
Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800, China
| | - Lei Ying
- Shanghai
Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800, China
| | - Jun Meng
- Shanghai
Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800, China
| | - Beien Zhu
- Photon
Science Research Center for Carbon Dioxide, Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai 201210, China
| | - Yi Gao
- Photon
Science Research Center for Carbon Dioxide, Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai 201210, China
- Key
Laboratory of Low-Carbon Conversion Science & Engineering, Shanghai Advanced Research Institute, Chinese Academy
of Sciences, Shanghai 201210, China
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3
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Wang Y, Liang J, Liu S, Wang Q, Zhang Y, Tian Y, Ke Z, Su Q, Pang S. Selective Adsorbent Design with Multifunctional Surfaces: Innovating Solutions for Heterogeneous Catalysis in Water. LANGMUIR : THE ACS JOURNAL OF SURFACES AND COLLOIDS 2024; 40:9265-9279. [PMID: 38636094 DOI: 10.1021/acs.langmuir.4c00702] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/20/2024]
Abstract
Heterogeneous catalytic systems with water as the solvent often have the disadvantage of cross-contamination, while concerns about the purification and workup of the aqueous phase after reactions are rare in the lab or industry. In this context, designing and developing the functional selective solid adsorbent and revealing the adsorption mechanism can provide a new strategy and guidelines for constructing supported heterogeneous catalysts to address these issues. Herein, we report the stable composite adsorbent (Fe/ATP@PPy: magnetic Fe3O4/attapulgite with the polypyrrole shell) that features an integrated multifunctional surface, which can effectively tune the selective adsorption processes for Cu2+, Co2+, and Ni2+ ions and nitrobenzene via the cooperative chemisorption/physisorption in an aqueous system. The adsorption experiments showed that Fe/ATP@PPy displayed significantly higher adsorption selectivity for Ni2+ than Cu2+ and Co2+ ions, especially which exhibited an approximate 100.00% removal for both Ni2+ ions and nitrobenzene in the mixture system with a low concentration. Furthermore, combined tracking adsorption of Ni2+ ions and X-ray photoelectron spectroscopy characterization confirmed that the effective adsorption occurs via ion transfer coordination; the pathway was further validated at the molecular level through theoretical modeling. In addition, the selective adsorption mechanism was proposed based on the adsorption experiment, characterization, and the corresponding density functional theory calculation.
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Affiliation(s)
- Yanbin Wang
- Key Laboratory of Environment-Friendly Composite Materials of the State Ethnic Affairs Commission, Gansu Provincial Biomass Function Composites Engineering Research Center, Key Laboratory for Utility of Environment-Friendly Composite Materials and Biomass in University of Gansu Province, Chemical Engineering Institute, Northwest Minzu University, Lanzhou, Gansu 730030, P. R. China
| | - Junxi Liang
- Key Laboratory of Environment-Friendly Composite Materials of the State Ethnic Affairs Commission, Gansu Provincial Biomass Function Composites Engineering Research Center, Key Laboratory for Utility of Environment-Friendly Composite Materials and Biomass in University of Gansu Province, Chemical Engineering Institute, Northwest Minzu University, Lanzhou, Gansu 730030, P. R. China
| | - Shimin Liu
- State Key Laboratory for Oxo Synthesis and Selective Oxidation, Lanzhou Institute of Chemical Physics, Chinese Academy of Sciences, Lanzhou, Gansu 730000, P. R. China
| | - Qing Wang
- Key Laboratory of Environment-Friendly Composite Materials of the State Ethnic Affairs Commission, Gansu Provincial Biomass Function Composites Engineering Research Center, Key Laboratory for Utility of Environment-Friendly Composite Materials and Biomass in University of Gansu Province, Chemical Engineering Institute, Northwest Minzu University, Lanzhou, Gansu 730030, P. R. China
| | - Yujing Zhang
- Key Laboratory of Eco-functional Polymer Materials of the Ministry of Education, Key Laboratory of Polymer Materials of Gansu Province, College of Chemistry and Chemical Engineering, Northwest Normal University, Lanzhou, Gansu 730070, P. R. China
| | - Yu Tian
- Key Laboratory of Environment-Friendly Composite Materials of the State Ethnic Affairs Commission, Gansu Provincial Biomass Function Composites Engineering Research Center, Key Laboratory for Utility of Environment-Friendly Composite Materials and Biomass in University of Gansu Province, Chemical Engineering Institute, Northwest Minzu University, Lanzhou, Gansu 730030, P. R. China
| | - Zhengang Ke
- Key Laboratory for Green Processing of Chemical Engineering of Xinjiang Bingtuan, School of Chemistry and Chemical Engineering, Shihezi University, Shihezi 832003, P. R. China
| | - Qiong Su
- Key Laboratory of Environment-Friendly Composite Materials of the State Ethnic Affairs Commission, Gansu Provincial Biomass Function Composites Engineering Research Center, Key Laboratory for Utility of Environment-Friendly Composite Materials and Biomass in University of Gansu Province, Chemical Engineering Institute, Northwest Minzu University, Lanzhou, Gansu 730030, P. R. China
| | - Shaofeng Pang
- Key Laboratory of Environment-Friendly Composite Materials of the State Ethnic Affairs Commission, Gansu Provincial Biomass Function Composites Engineering Research Center, Key Laboratory for Utility of Environment-Friendly Composite Materials and Biomass in University of Gansu Province, Chemical Engineering Institute, Northwest Minzu University, Lanzhou, Gansu 730030, P. R. China
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4
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Svensson R, Grönbeck H. Spontaneous Charge Separation at the Metal-Water Interface. Chemphyschem 2024; 25:e202400099. [PMID: 38315759 DOI: 10.1002/cphc.202400099] [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: 02/01/2024] [Accepted: 02/05/2024] [Indexed: 02/07/2024]
Abstract
Reactions at the metal-water interface are essential in a range of fundamental and technological processes. Using Density Functional Theory calculations, we demonstrate that water substantially affects the adsorption of H and O2 on Cu(111), Ag(111), Au(111), Pd(111) and Pt(111). In water, H is found to undergo a spontaneous charge separation, where a proton desorbs to the water solution while an electron is donated to the surface. The reaction is exothermic over Au and Pt and associated with low barriers. The process is facile also over Pd, albeit slightly endothermic. For O2, water is found to increase the metal-to-adsorbate charge transfer, enhancing the adsorption energy and O-O bond length as compared to the adsorption in the absence of water. The magnitudes of the effects are system dependent, which implies that calculations should treat water explicitly. The results elucidate previous experimental results and highlights the importance of charge-transfer effects at the metal-water interface; both to describe the potential energy landscape, and to account for alternative reaction routes in the presence of water.
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Affiliation(s)
- Rasmus Svensson
- Department of Physics and Competence Centre for Catalysis, Chalmers University of Technology, SE-412 96, Göteborg, Sweden
| | - Henrik Grönbeck
- Department of Physics and Competence Centre for Catalysis, Chalmers University of Technology, SE-412 96, Göteborg, Sweden
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5
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Lalith N, Singh AR, Gauthier JA. The Importance of Reaction Energy in Predicting Chemical Reaction Barriers with Machine Learning Models. Chemphyschem 2024:e202300933. [PMID: 38517585 DOI: 10.1002/cphc.202300933] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Revised: 03/21/2024] [Accepted: 03/22/2024] [Indexed: 03/24/2024]
Abstract
Improving our fundamental understanding of complex heterocatalytic processes increasingly relies on electronic structure simulations and microkinetic models based on calculated energy differences. In particular, calculation of activation barriers, usually achieved through compute-intensive saddle point search routines, remains a serious bottleneck in understanding trends in catalytic activity for highly branched reaction networks. Although the well-known Brønsted-Evans-Polyani (BEP) scaling - a one-feature linear regression model - has been widely applied in such microkinetic models, they still rely on calculated reaction energies and may not generalize beyond a single facet on a single class of materials, e. g., a terrace sites on transition metals. For highly branched and energetically shallow reaction networks, such as electrochemical CO2 reduction or wastewater remediation, calculating even reaction energies on many surfaces can become computationally intractable due to the combinatorial explosion of states that must be considered. Here, we investigate the feasibility of activation barrier prediction without knowledge of the reaction energy using linear and nonlinear machine learning (ML) models trained on a new database of over 500 dehydrogenation activation barriers. We also find that inclusion of the reaction energy significantly improves both classes of ML models, but complex nonlinear models can achieve performance similar to the simplest BEP scaling when predicting activation barriers on new systems. Additionally, inclusion of the reaction energy significantly improves generalizability to new systems beyond the training set. Our results suggest that the reaction energy is a critical feature to consider when building models to predict activation barriers, indicating that efforts to reliably predict reaction energies through, e. g., the Open Catalyst Project and others, will be an important route to effective model development for more complex systems.
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Affiliation(s)
- Nithin Lalith
- Department of Chemical Engineering, Texas Tech University, Lubbock, TX 79409, USA
| | | | - Joseph A Gauthier
- Department of Chemical Engineering, Texas Tech University, Lubbock, TX 79409, USA
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6
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Li Z, Zhao C, Wang H, Ding Y, Chen Y, Schwaller P, Yang K, Hua C, He Y. Interpreting chemisorption strength with AutoML-based feature deletion experiments. Proc Natl Acad Sci U S A 2024; 121:e2320232121. [PMID: 38478684 PMCID: PMC10962981 DOI: 10.1073/pnas.2320232121] [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: 11/17/2023] [Accepted: 02/10/2024] [Indexed: 03/27/2024] Open
Abstract
The chemisorption energy of reactants on a catalyst surface, [Formula: see text], is among the most informative characteristics of understanding and pinpointing the optimal catalyst. The intrinsic complexity of catalyst surfaces and chemisorption reactions presents significant difficulties in identifying the pivotal physical quantities determining [Formula: see text]. In response to this, the study proposes a methodology, the feature deletion experiment, based on Automatic Machine Learning (AutoML) for knowledge extraction from a high-throughput density functional theory (DFT) database. The study reveals that, for binary alloy surfaces, the local adsorption site geometric information is the primary physical quantity determining [Formula: see text], compared to the electronic and physiochemical properties of the catalyst alloys. By integrating the feature deletion experiment with instance-wise variable selection (INVASE), a neural network-based explainable AI (XAI) tool, we established the best-performing feature set containing 21 intrinsic, non-DFT computed properties, achieving an MAE of 0.23 eV across a periodic table-wide chemical space involving more than 1,600 types of alloys surfaces and 8,400 chemisorption reactions. This study demonstrates the stability, consistency, and potential of AutoML-based feature deletion experiment in developing concise, predictive, and theoretically meaningful models for complex chemical problems with minimal human intervention.
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Affiliation(s)
- Zhuo Li
- University of Michigan-Shanghai Jiao Tong University Joint Institute, Shanghai Jiao Tong University, Shanghai200240, China
- School of Chemistry and Chemical Engineering, Shanghai Jiao Tong University, Shanghai200240, China
| | - Changquan Zhao
- School of Mathematical Science, Shanghai Jiao Tong University, Shanghai200240, China
| | - Haikun Wang
- Antai College of Economics and Management, Shanghai Jiao Tong University, Shanghai200240, China
| | - Yanqing Ding
- Fu Foundation School of Engineering and Applied Science, Columbia University, New York, NY10027
| | - Yechao Chen
- Antai College of Economics and Management, Shanghai Jiao Tong University, Shanghai200240, China
| | - Philippe Schwaller
- Laboratory of Artificial Chemical Intelligence, Institut des Sciences et Ingénierie Chimiques, École Polytechnique Fédérale de Lausanne, Lausanne1015, Switzerland
- National Centre of Competence in Research Catalysis, École Polytechnique Fédérale de Lausanne, Lausanne1015, Switzerland
| | - Ke Yang
- Key Laboratory of Advanced Energy Materials Chemistry, Nankai University, Tianjin300071, China
| | - Cheng Hua
- Antai College of Economics and Management, Shanghai Jiao Tong University, Shanghai200240, China
| | - Yulian He
- University of Michigan-Shanghai Jiao Tong University Joint Institute, Shanghai Jiao Tong University, Shanghai200240, China
- School of Chemistry and Chemical Engineering, Shanghai Jiao Tong University, Shanghai200240, China
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7
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Miao L, Jia W, Cao X, Jiao L. Computational chemistry for water-splitting electrocatalysis. Chem Soc Rev 2024; 53:2771-2807. [PMID: 38344774 DOI: 10.1039/d2cs01068b] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
Electrocatalytic water splitting driven by renewable electricity has attracted great interest in recent years for producing hydrogen with high-purity. However, the practical applications of this technology are limited by the development of electrocatalysts with high activity, low cost, and long durability. In the search for new electrocatalysts, computational chemistry has made outstanding contributions by providing fundamental laws that govern the electron behavior and enabling predictions of electrocatalyst performance. This review delves into theoretical studies on electrochemical water-splitting processes. Firstly, we introduce the fundamentals of electrochemical water electrolysis and subsequently discuss the current advancements in computational methods and models for electrocatalytic water splitting. Additionally, a comprehensive overview of benchmark descriptors is provided to aid in understanding intrinsic catalytic performance for water-splitting electrocatalysts. Finally, we critically evaluate the remaining challenges within this field.
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Affiliation(s)
- Licheng Miao
- Key Laboratory of Advanced Energy Materials Chemistry (Ministry of Education), Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), College of Chemistry, Nankai University, Tianjin 300071, China.
| | - Wenqi Jia
- Key Laboratory of Advanced Energy Materials Chemistry (Ministry of Education), Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), College of Chemistry, Nankai University, Tianjin 300071, China.
| | - Xuejie Cao
- Key Laboratory of Advanced Energy Materials Chemistry (Ministry of Education), Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), College of Chemistry, Nankai University, Tianjin 300071, China.
| | - Lifang Jiao
- Key Laboratory of Advanced Energy Materials Chemistry (Ministry of Education), Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), College of Chemistry, Nankai University, Tianjin 300071, China.
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8
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Wang S, Kasarapu SSK, Clough PT. High-Throughput Screening of Sulfur-Resistant Catalysts for Steam Methane Reforming Using Machine Learning and Microkinetic Modeling. ACS OMEGA 2024; 9:12184-12194. [PMID: 38496975 PMCID: PMC10938427 DOI: 10.1021/acsomega.4c00119] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Revised: 01/31/2024] [Accepted: 02/21/2024] [Indexed: 03/19/2024]
Abstract
The catalytic activity of bimetallic catalysts for the steam methane reforming (SMR) reaction was extensively studied previously. However, the performance of these materials in the presence of sulfur-containing species is yet to be investigated. In this study, we propose a novel process aided by machine learning (ML) and microkinetic modeling for the rapid screening of sulfur-resistant bimetallic catalysts. First, various ML models were developed to predict atomic adsorption energies (C, H, O, and S) on bimetallic surfaces. Easily accessible physical and chemical properties of the metals and adsorbates were used as input features. The Ensemble learning, artificial neural network, and support vector regression models achieved the best performance with R2 values of 0.74, 0.71, and 0.70, respectively. A microkinetic model was then built based on the elementary steps of the SMR reaction. Finally, the microkinetic model, together with the atomic adsorption energies predicted by the Ensemble model, were used to screen over 500 bimetallic materials. Four Ge-based alloys (Ge3Cu1, Ge3Ni1, Ge3Co1, and Ge3Fe1) and the Ni3Cu1 alloy were identified as promising and cost-effective sulfur-resistant catalysts.
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Affiliation(s)
- Siqi Wang
- Energy and Sustainability
Theme, Cranfield University, Cranfield, Bedfordshire MK43 0AL, U.K.
| | | | - Peter T. Clough
- Energy and Sustainability
Theme, Cranfield University, Cranfield, Bedfordshire MK43 0AL, U.K.
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9
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Wang J, Wang GC. Mechanisms of CH 4 activation over oxygen-preadsorbed transition metals by ReaxFF and AIMD simulations. J Comput Chem 2024; 45:238-246. [PMID: 37746925 DOI: 10.1002/jcc.27233] [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: 07/12/2023] [Revised: 08/26/2023] [Accepted: 09/09/2023] [Indexed: 09/26/2023]
Abstract
The chemisorbed oxygen usually promotes the CH bond activation over less active metals like IB group metals but has no effect or even an inhibition effect over more active metals like Pd based on the static electronic structure study. However, the understanding in terms of dynamics knowledge is far from complete. In the present work, methane dissociation on the oxygen-preadsorbed transition metals including Au, Cu, Ni, Pt, and Pd is systemically studied by reactive force field (ReaxFF). The ReaxFF simulation results indicate that CH4 molecules mainly undergo the direct dissociation on Ni, Pt, and Pd surfaces, while undergo the oxygen-assisted dissociation on Au and Cu surfaces. Additionally, the ab initio molecular dynamics (AIMD) simulations with the umbrella sampling are employed to study the free-energy changes of CH4 dissociation, and the results further support the CH4 dissociation pathway during the ReaxFF simulations. The present results based on ReaxFF and AIMD will provide a deeper dynamic understanding of the effects of pre-adsorbed oxygen species on the CH bond activation compared to that of static DFT.
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Affiliation(s)
- Jie Wang
- Key Laboratory of Advanced Energy Materials Chemistry (Ministry of Education) and the Tianjin key Lab and Molecule-based Material Chemistry, College of Chemistry, Nankai University, Tianjin, China
| | - Gui-Chang Wang
- Key Laboratory of Advanced Energy Materials Chemistry (Ministry of Education) and the Tianjin key Lab and Molecule-based Material Chemistry, College of Chemistry, Nankai University, Tianjin, China
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10
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Deb J, Saikia L, Dihingia KD, Sastry GN. ChatGPT in the Material Design: Selected Case Studies to Assess the Potential of ChatGPT. J Chem Inf Model 2024; 64:799-811. [PMID: 38237025 DOI: 10.1021/acs.jcim.3c01702] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/13/2024]
Abstract
The pursuit of designing smart and functional materials is of paramount importance across various domains, such as material science, engineering, chemical technology, electronics, biomedicine, energy, and numerous others. Consequently, researchers are actively involved in the development of innovative models and strategies for material design. Recent advancements in analytical tools, experimentation, and computer technology additionally enhance the material design possibilities. Notably, data-driven techniques like artificial intelligence and machine learning have achieved substantial progress in exploring various applications within material science. One such approach, ChatGPT, a large language model, holds transformative potential for addressing complex queries. In this article, we explore ChatGPT's understanding of material science by assigning some simple tasks across various subareas of computational material science. The findings indicate that while ChatGPT may make some minor errors in accomplishing general tasks, it demonstrates the capability to learn and adapt through human interactions. However, issues like output consistency, probable hidden errors, and ethical consequences should be addressed.
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Affiliation(s)
- Jyotirmoy Deb
- Advanced Computation and Data Sciences Division, CSIR-North East Institute of Science and Technology, Jorhat 785006, Assam, India
| | - Lakshi Saikia
- Advanced Materials Group, Materials Sciences & Technology Division, CSIR-North East Institute of Science and Technology, Jorhat 785006, Assam, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, Uttar Pradesh, India
| | - Kripa Dristi Dihingia
- Advanced Computation and Data Sciences Division, CSIR-North East Institute of Science and Technology, Jorhat 785006, Assam, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, Uttar Pradesh, India
| | - G Narahari Sastry
- Advanced Computation and Data Sciences Division, CSIR-North East Institute of Science and Technology, Jorhat 785006, Assam, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, Uttar Pradesh, India
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11
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Rey J, Chizallet C, Rocca D, Bučko T, Badawi M. Reference-Quality Free Energy Barriers in Catalysis from Machine Learning Thermodynamic Perturbation Theory. Angew Chem Int Ed Engl 2024; 63:e202312392. [PMID: 38055209 DOI: 10.1002/anie.202312392] [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: 08/23/2023] [Revised: 11/11/2023] [Accepted: 12/06/2023] [Indexed: 12/07/2023]
Abstract
For the first time, we report calculations of the free energies of activation of cracking and isomerization reactions of alkenes that combine several different electronic structure methods with molecular dynamics simulations. We demonstrate that the use of a high level of theory (here Random Phase Approximation-RPA) is necessary to bridge the gap between experimental and computed values. These transformations, catalyzed by zeolites and proceeding via cationic intermediates and transition states, are building blocks of many chemical transformations for valorization of long chain paraffins originating, e.g., from plastic waste, vegetable oils, Fischer-Tropsch waxes or crude oils. Compared with the free energy barriers computed at the PBE+D2 production level of theory via constrained ab initio molecular dynamics, the barriers computed at the RPA level by the application of Machine Learning thermodynamic Perturbation Theory (MLPT) show a significant decrease for isomerization reaction and an increase of a similar magnitude for cracking, yielding an unprecedented agreement with the results obtained by experiments and kinetic modeling.
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Affiliation(s)
- Jérôme Rey
- Laboratoire de Physique et Chimie Théoriques LPCT UMR 7019-CNRS, Université de Lorraine, Vandœuvre-lés-Nancy, France
| | - Céline Chizallet
- IFP Energies nouvelles, Rond-Point de l'Ēchangeur de Solaize, BP3, 69360, Solaize, France
| | - Dario Rocca
- Laboratoire de Physique et Chimie Théoriques LPCT UMR 7019-CNRS, Université de Lorraine, Vandœuvre-lés-Nancy, France
| | - Tomáš Bučko
- Department of Physical and Theoretical Chemistry, Faculty of Natural Sciences, Comenius University in Bratislava, Ilkovičova 6, SK-84215, Bratislava, Slovakia
- Institute of Inorganic Chemistry, Slovak Academy of Sciences, Dúbravská cesta 9, SK-84236, Bratislava, Slovakia
| | - Michael Badawi
- Laboratoire de Physique et Chimie Théoriques LPCT UMR 7019-CNRS, Université de Lorraine, Vandœuvre-lés-Nancy, France
- Laboratoire Lorrain de Chimie Moléculaire L2CM UMR 7053-CNRS, Université de Lorraine, Metz, France
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12
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Yang MY, Wu XP. Level-Shifted Embedded Cluster Method for Modeling the Chemistry of Metal Oxides. J Chem Theory Comput 2024. [PMID: 38300767 DOI: 10.1021/acs.jctc.3c01123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2024]
Abstract
The embedded cluster method has been used extensively in the study of the chemical and physical properties of metal oxides. This method has been a popular tool due to its relatively high accuracy and low computational cost. An even more promising option may entail integrating the embedded cluster method with the combined quantum mechanical and molecular mechanical (QM/MM) approach, thereby enabling further consideration of interactions within the entire system for superior results. We aim to accurately model the chemistry of metal oxides using this combined scheme. Here, using the prototypical MgO(100) surface as a test system, with Mg9O14 as the cluster in the quantum mechanical region, we show that the embedded cluster with untailored boundary effective core potentials (ECPs) can have frontier orbital energy levels that substantially deviate from the quantum mechanical reference results. This occurs even when Mg9O9, which retains the stoichiometry of MgO, is used as the cluster in the quantum mechanical region. As a result, the chemical properties of the embedded cluster models differ from those of the quantum mechanical reference model. To address this issue, we propose a new variant of the embedded cluster method called the level-shifted embedded cluster (LSEC) method, which allows the energy levels to be shifted to match the reference levels by tuning the boundary ECPs. Our validation calculations on the adsorption of various adsorbates with different properties on the MgO(100) surface show that the overall performance of QM/MM with the LSEC method is excellent for the adsorption energies, geometries, and charge properties. The excellent performance holds for both the nonstoichiometric and stoichiometric clusters (i.e., Mg9O14 and Mg9O9, respectively), demonstrating the robustness of the LSEC method. We expect that the LSEC method can be combined with QM/MM or used separately for future chemical studies of metal oxides and other ionically bonded systems.
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Affiliation(s)
- Ming-Yu Yang
- State Key Laboratory of Green Chemical Engineering and Industrial Catalysis, Centre for Computational Chemistry and Research Institute of Industrial Catalysis, School of Chemistry and Molecular Engineering, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, P.R. China
| | - Xin-Ping Wu
- State Key Laboratory of Green Chemical Engineering and Industrial Catalysis, Centre for Computational Chemistry and Research Institute of Industrial Catalysis, School of Chemistry and Molecular Engineering, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, P.R. China
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13
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Gomes GJ, Zalazar MF, Padilha JC, Costa MB, Bazzi CL, Arroyo PA. Unveiling the mechanisms of carboxylic acid esterification on acid zeolites for biomass-to-energy: A review of the catalytic process through experimental and computational studies. CHEMOSPHERE 2024; 349:140879. [PMID: 38061565 DOI: 10.1016/j.chemosphere.2023.140879] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Revised: 11/19/2023] [Accepted: 12/01/2023] [Indexed: 01/10/2024]
Abstract
In recent years, there has been significant interest from industrial and academic areas in the esterification of carboxylic acids catalyzed by acidic zeolites, as it represents a sustainable and economically viable approach to producing a wide range of high-value-added products. However, there is a lack of comprehensive reviews that address the intricate reaction mechanisms occurring at the catalyst interface at both the experimental and atomistic levels. Therefore, in this review, we provide an overview of the esterification reaction on acidic zeolites based on experimental and theoretical studies. The combination of infrared spectroscopy with atomistic calculations and experimental strategies using modulation excitation spectroscopy techniques combined with phase-sensitive detection is presented as an approach to detecting short-lived intermediates at the interface of zeolitic frameworks under realistic reaction conditions. To achieve this goal, this review has been divided into four sections: The first is a brief introduction highlighting the distinctive features of this review. The second addresses questions about the topology and activity of different zeolitic systems, since these properties are closely correlated in the esterification process. The third section deals with the mechanisms proposed in the literature. The fourth section presents advances in IR techniques and theoretical calculations that can be applied to gain new insights into reaction mechanisms. Finally, this review concludes with a subtle approach, highlighting the main aspects and perspectives of combining experimental and theoretical techniques to elucidate different reaction mechanisms in zeolitic systems.
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Affiliation(s)
- Glaucio José Gomes
- Laboratorio de Estructura Molecular y Propiedades (LEMyP), Instituto de Química Básica y Aplicada Del Nordeste Argentino, (IQUIBA-NEA), Consejo Nacional de Investigaciones Científicas y Técnicas, Universidad Nacional Del Nordeste (CONICET-UNNE), Avenida Libertad 5460, 3400, Corrientes, Argentina; Laboratório de Catálise Heterogênea e Biodiesel (LCHBio), Universidade Estadual de Maringá (UEM), Avenida Colombo, 5790, (87020-900), Maringá, Paraná, Brazil; Programa de Pós-Graduação Interdisciplinar Em Energia e Sustentabilidade, Universidade Federal da Integração Latino-Americana (UNILA), Avenida Presidente Tancredo Neves, 3838, (85870-650), Foz Do Iguaçu, Paraná, Brazil.
| | - María Fernanda Zalazar
- Laboratorio de Estructura Molecular y Propiedades (LEMyP), Instituto de Química Básica y Aplicada Del Nordeste Argentino, (IQUIBA-NEA), Consejo Nacional de Investigaciones Científicas y Técnicas, Universidad Nacional Del Nordeste (CONICET-UNNE), Avenida Libertad 5460, 3400, Corrientes, Argentina.
| | - Janine Carvalho Padilha
- Programa de Pós-Graduação Interdisciplinar Em Energia e Sustentabilidade, Universidade Federal da Integração Latino-Americana (UNILA), Avenida Presidente Tancredo Neves, 3838, (85870-650), Foz Do Iguaçu, Paraná, Brazil
| | - Michelle Budke Costa
- Universidade Tecnológica Federal Do Paraná (UTFPR), Avenida Brasil 4232, (85884-000), Medianeira, Brazil
| | - Claudio Leones Bazzi
- Universidade Tecnológica Federal Do Paraná (UTFPR), Avenida Brasil 4232, (85884-000), Medianeira, Brazil
| | - Pedro Augusto Arroyo
- Laboratório de Catálise Heterogênea e Biodiesel (LCHBio), Universidade Estadual de Maringá (UEM), Avenida Colombo, 5790, (87020-900), Maringá, Paraná, Brazil
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14
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Javed M, Shah A, Nisar J, Shahzad S, Haleem A, Shah I. Nanostructured Design Cathode Materials for Magnesium-Ion Batteries. ACS OMEGA 2024; 9:4229-4245. [PMID: 38313505 PMCID: PMC10831983 DOI: 10.1021/acsomega.3c06576] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Revised: 12/07/2023] [Accepted: 12/22/2023] [Indexed: 02/06/2024]
Abstract
Energy is undeniably one of the most fundamental requirements of the current generation. Solar and wind energy are sustainable and renewable energy sources; however, their unpredictability points to the development of energy storage systems (ESSs). There has been a substantial increase in the use of batteries, particularly lithium-ion batteries (LIBs), as ESSs. However, low rate capability and degradation due to electric load in long-range electric vehicles are pushing LIBs to their limits. As alternative ESSs, magnesium-ion batteries (MIBs) possess promising properties and advantages. Cathode materials play a crucial role in MIBs. In this regard, a variety of cathode materials, including Mn-based, Se-based, vanadium- and vanadium oxide-based, S-based, and Mg2+-containing cathodes, have been investigated by experimental and theoretical techniques. Results reveal that the discharge capacity, capacity retention, and cycle life of cathode materials need improvement. Nevertheless, maintaining the long-term stability of the electrode-electrolyte interface during high-voltage operation continues to be a hurdle in the execution of MIBs, despite the continuous research in this field. The current Review mainly focuses on the most recent nanostructured-design cathode materials in an attempt to draw attention to MIBs and promote the investigation of suitable cathode materials for this promising energy storage device.
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Affiliation(s)
- Mohsin Javed
- Department
of Chemistry, Quaid-I-Azam University, Islamabad 45320, Pakistan
| | - Afzal Shah
- Department
of Chemistry, Quaid-I-Azam University, Islamabad 45320, Pakistan
| | - Jan Nisar
- National
Centre of Excellence in Physical Chemistry, University of Peshawar, Peshawar 25120, Pakistan
| | - Suniya Shahzad
- Department
of Chemistry, Quaid-I-Azam University, Islamabad 45320, Pakistan
| | - Abdul Haleem
- School
of Chemistry and Chemical Engineering, Jiangsu
University, Zhenjiang, Jiangsu 212013, China
| | - Iltaf Shah
- Department
of Chemistry, College of Science, United
Arab Emirates University, P.O. Box 15551, Al Ain, Abu Dhabi, United Arab Emirates
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15
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Le TH, Ferro-Costas D, Fernández-Ramos A, Ortuño MA. Combined DFT and Kinetic Monte Carlo Study of UiO-66 Catalysts for γ-Valerolactone Production. THE JOURNAL OF PHYSICAL CHEMISTRY. C, NANOMATERIALS AND INTERFACES 2024; 128:1049-1057. [PMID: 38293690 PMCID: PMC10823797 DOI: 10.1021/acs.jpcc.3c06053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Revised: 12/21/2023] [Accepted: 01/02/2024] [Indexed: 02/01/2024]
Abstract
Zr-based metal-organic frameworks (MOFs) are excellent heterogeneous porous catalysts due to their thermal stability. Their tunability via node and linker modifications makes them amenable for theoretical studies on catalyst design. However, detailed benchmarks on MOF-based reaction mechanisms combined with kinetics analysis are still scarce. Thus, we here evaluate different computational models and density functional theory (DFT) methods followed by kinetic Monte Carlo studies for a case reaction relevant in biomass upgrading, i.e., the conversion of methyl levulinate to γ-valerolactone catalyzed by UiO-66. We show the impact of cluster versus periodic models, the importance of the DF of choice, and the direct comparison to experimental data via simulated kinetics data. Overall, we found that Perdew-Burke-Ernzerhof (PBE), a widely employed method in plane-wave periodic calculations, greatly overestimates reaction rates, while M06 with cluster models better fits the available experimental data and is recommended whenever possible.
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Affiliation(s)
- Thanh-Hiep
Thi Le
- Centro
Singular de Investigación en Química Biolóxica
e Materiais Moleculares (CIQUS), Universidade
de Santiago de Compostela, 15782 Santiago de Compostela, Spain
| | - David Ferro-Costas
- Centro
Singular de Investigación en Química Biolóxica
e Materiais Moleculares (CIQUS), Universidade
de Santiago de Compostela, 15782 Santiago de Compostela, Spain
- Departamento
de Química Física, Facultade de Química, Universidade de Santiago de Compostela, 15782 Santiago
de Compostela, Spain
| | - Antonio Fernández-Ramos
- Centro
Singular de Investigación en Química Biolóxica
e Materiais Moleculares (CIQUS), Universidade
de Santiago de Compostela, 15782 Santiago de Compostela, Spain
- Departamento
de Química Física, Facultade de Química, Universidade de Santiago de Compostela, 15782 Santiago
de Compostela, Spain
| | - Manuel A. Ortuño
- Centro
Singular de Investigación en Química Biolóxica
e Materiais Moleculares (CIQUS), Universidade
de Santiago de Compostela, 15782 Santiago de Compostela, Spain
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16
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Xu L, Ye R, Mavrikakis M, Chen P. Molecular-scale Insights into Cooperativity Switching of xTAB Adsorption on Gold Nanoparticles. ACS CENTRAL SCIENCE 2024; 10:65-76. [PMID: 38292618 PMCID: PMC10823513 DOI: 10.1021/acscentsci.3c01075] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Revised: 10/12/2023] [Accepted: 11/27/2023] [Indexed: 02/01/2024]
Abstract
Quantifying adsorption behaviors is crucial for various applications such as catalysis, separation, and sensing, yet it is generally challenging to access in solution. Here, we report a combined experimental and computational study of the adsorption behaviors of alkyl-trimethylammonium bromides (xTAB), a class of ligands important for colloidal nanoparticle stabilization and shape control, with various alkyl chain lengths x on Au nanoparticles. We use density functional theory (DFT) to calculate xTAB binding energies on Au{111} and Au{110} surfaces with standing-up and lying-down configurations, which provides insights into the adsorption affinity and cooperativity differences of xTAB on these two facets. We demonstrate the key role of van der Waals interactions in determining the xTAB adsorption behavior. These computational results predict and explain the experimental discovery of xTAB's adsorption behavior switch from stronger affinity, negative cooperativity to weaker affinity, positive cooperativity when the concentration of xTAB increases in solution. We also show that in the standing-up configuration, bilayer adsorption may occur on both facets, which can lead to different differential binding energies and consequently adsorption crossover between the two facets when the ligand concentration increases. Our combined experimental and computational approaches demonstrate a paradigm for gaining molecular-scale insights into adsorbate-surface interactions.
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Affiliation(s)
- Lang Xu
- Department
of Chemical and Biological Engineering, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
| | - Rong Ye
- Department
of Chemistry and Chemical Biology, Cornell
University, Ithaca, New York 14853, United States
| | - Manos Mavrikakis
- Department
of Chemical and Biological Engineering, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
| | - Peng Chen
- Department
of Chemistry and Chemical Biology, Cornell
University, Ithaca, New York 14853, United States
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17
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Nie S, Wang X. Electron Delocalization and Transfer Across Polyoxometalates-Based Subnanomaterials in Catalytic Reactions. SMALL METHODS 2023:e2301359. [PMID: 38161270 DOI: 10.1002/smtd.202301359] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Revised: 11/27/2023] [Indexed: 01/03/2024]
Abstract
Due to their identical building blocks and high surface-to-volume ratio, subnanomaterials exhibit significant properties compared to their bulk nanomaterial counterparts. The interactions between these building blocks can result in either equal or unequal sharing of electrons, leading to electron transfer in heterojunctions or electron delocalization within symmetric structures. Clusters, possessing electronic properties akin to atoms, can serve as reservoirs of electrons to stabilize crucial intermediates in catalytic reactions. This perspective provides a novel understanding of well-defined subnanomaterials with distinct architectures, such as cluster-based constructions and co-assembled heterojunctions, emphasizing the relationship between electronic structures and catalytic properties. The objective is to provide novel perspectives on the realm of subnanomaterials and cluster-based architectures.
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Affiliation(s)
- Siyang Nie
- Engineering Research Center of Advanced Rare Earth Materials, Department of Chemistry, Tsinghua University, Beijing, 100084, China
| | - Xun Wang
- Engineering Research Center of Advanced Rare Earth Materials, Department of Chemistry, Tsinghua University, Beijing, 100084, China
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18
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Benson RL, Yadavalli SS, Stamatakis M. Speeding up the Detection of Adsorbate Lateral Interactions in Graph-Theoretical Kinetic Monte Carlo Simulations. J Phys Chem A 2023; 127:10307-10319. [PMID: 37988475 PMCID: PMC11065322 DOI: 10.1021/acs.jpca.3c05581] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Revised: 10/22/2023] [Accepted: 10/23/2023] [Indexed: 11/23/2023]
Abstract
Kinetic Monte Carlo (KMC) has become an indispensable tool in heterogeneous catalyst discovery, but realistic simulations remain computationally demanding on account of the need to capture complex and long-range lateral interactions between adsorbates. The Zacros software package (https://zacros.org) adopts a graph-theoretical cluster expansion (CE) framework that allows such interactions to be computed with a high degree of generality and fidelity. This involves solving a series of subgraph isomorphism problems in order to identify relevant interaction patterns in the lattice. In an effort to reduce the computational burden, we have adapted two well-known subgraph isomorphism algorithms, namely, VF2 and RI, for use in KMC simulations and implemented them in Zacros. To benchmark their performance, we simulate a previously established model of catalytic NO oxidation, treating the O* lateral interactions with a series of progressively larger CEs. For CEs with long-range interactions, VF2 and RI are found to provide impressive speedups relative to simpler algorithms. RI performs best, giving speedups reaching more than 150× when combined with OpenMP parallelization. We also simulate a recently developed methane cracking model, showing that RI offers significant improvements in performance at high surface coverages.
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Affiliation(s)
- Raz L. Benson
- Department of Chemical Engineering, University College London, Torrington Place, London WC1E 7JE, U.K.
| | - Sai Sharath Yadavalli
- Department of Chemical Engineering, University College London, Torrington Place, London WC1E 7JE, U.K.
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19
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Szaro NA, Bello M, Fricke CH, Bamidele OH, Heyden A. Benchmarking the Accuracy of Density Functional Theory against the Random Phase Approximation for the Ethane Dehydrogenation Network on Pt(111). J Phys Chem Lett 2023; 14:10769-10778. [PMID: 38011289 DOI: 10.1021/acs.jpclett.3c02723] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
The Random Phase Approximation (RPA) is conceptually the most accurate Density Functional Approximation method, able to simultaneously predict both adsorbate and surface energies accurately; however, this work questions its superiority over DFT for catalytic application on hydrocarbon systems. This work uses microkinetic modeling to benchmark the accuracy of DFT functionals against that of RPA for the ethane dehydrogenation reaction on Pt(111). Eight different functionals, with and without dispersion corrections, across the GGA, meta-GGA and hybrid classes are evaluated: PBE, PBE-D3, RPBE, RPBE-D3, BEEF-vdW, SCAN, SCAN-rVV10, and HSE06. We show that PBE and RPBE, without dispersion correction, closely model RPA energies for adsorption, transition states, reaction, and activation energies. Next, RPA fails to describe the gas phase energy as unsaturation and chain-length increases in the hydrocarbon. Finally, we show that RPBE has the best accuracy-to-cost ratio, and RPA is likely not superior to RPBE or BEEF-vdW, which also gives a measure of uncertainty.
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Affiliation(s)
- Nicholas A Szaro
- Department of Chemical Engineering, University of South Carolina, 301 South Main Street, Columbia, South Carolina 29208, United States
| | - Mubarak Bello
- Department of Chemical Engineering, University of South Carolina, 301 South Main Street, Columbia, South Carolina 29208, United States
| | - Charles H Fricke
- Department of Chemical Engineering, University of South Carolina, 301 South Main Street, Columbia, South Carolina 29208, United States
| | - Olajide H Bamidele
- Department of Chemical Engineering, University of South Carolina, 301 South Main Street, Columbia, South Carolina 29208, United States
| | - Andreas Heyden
- Department of Chemical Engineering, University of South Carolina, 301 South Main Street, Columbia, South Carolina 29208, United States
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20
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Kanhaiya K, Nathanson M, In 't Veld PJ, Zhu C, Nikiforov I, Tadmor EB, Choi YK, Im W, Mishra RK, Heinz H. Accurate Force Fields for Atomistic Simulations of Oxides, Hydroxides, and Organic Hybrid Materials up to the Micrometer Scale. J Chem Theory Comput 2023; 19:8293-8322. [PMID: 37962992 DOI: 10.1021/acs.jctc.3c00750] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2023]
Abstract
The simulation of metals, oxides, and hydroxides can accelerate the design of therapeutics, alloys, catalysts, cement-based materials, ceramics, bioinspired composites, and glasses. Here we introduce the INTERFACE force field (IFF) and surface models for α-Al2O3, α-Cr2O3, α-Fe2O3, NiO, CaO, MgO, β-Ca(OH)2, β-Mg(OH)2, and β-Ni(OH)2. The force field parameters are nonbonded, including atomic charges for Coulomb interactions, Lennard-Jones (LJ) potentials for van der Waals interactions with 12-6 and 9-6 options, and harmonic bond stretching for hydroxide ions. The models outperform DFT calculations and earlier atomistic models (Pedone, ReaxFF, UFF, CLAYFF) up to 2 orders of magnitude in reliability, compatibility, and interpretability due to a quantitative representation of chemical bonding consistent with other compounds across the periodic table and curated experimental data for validation. The IFF models exhibit average deviations of 0.2% in lattice parameters, <10% in surface energies (to the extent known), and 6% in bulk moduli relative to experiments. The parameters and models can be used with existing parameters for solvents, inorganic compounds, organic compounds, biomolecules, and polymers in IFF, CHARMM, CVFF, AMBER, OPLS-AA, PCFF, and COMPASS, to simulate bulk oxides, hydroxides, electrolyte interfaces, and multiphase, biological, and organic hybrid materials at length scales from atoms to micrometers. The nonbonded character of the models also enables the analysis of mixed oxides, glasses, and certain chemical reactions, and well-performing nonbonded models for silica phases, SiO2, are introduced. Automated model building is available in the CHARMM-GUI Nanomaterial Modeler. We illustrate applications of the models to predict the structure of mixed oxides, and energy barriers of ion migration, as well as binding energies of water and organic molecules in outstanding agreement with experimental data and calculations at the CCSD(T) level. Examples of model building for hydrated, pH-sensitive oxide surfaces to simulate solid-electrolyte interfaces are discussed.
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Affiliation(s)
- Krishan Kanhaiya
- Department of Chemical and Biological Engineering, University of Colorado at Boulder, Boulder, Colorado 80309, United States
| | - Michael Nathanson
- Department of Chemical and Biological Engineering, University of Colorado at Boulder, Boulder, Colorado 80309, United States
| | - Pieter J In 't Veld
- BASF SE, Molecular Modeling & Drug Discovery, Carl Bosch Str. 38, 67056 Ludwigshafen, Germany
| | - Cheng Zhu
- Department of Chemical and Biological Engineering, University of Colorado at Boulder, Boulder, Colorado 80309, United States
| | - Ilia Nikiforov
- Department of Aerospace Engineering and Mechanics, University of Minnesota, Minneapolis, Minnesota 55455, United States
| | - Ellad B Tadmor
- Department of Aerospace Engineering and Mechanics, University of Minnesota, Minneapolis, Minnesota 55455, United States
| | - Yeol Kyo Choi
- Department of Biological Sciences, Lehigh University, Bethlehem, Pennsylvania 18015, United States
| | - Wonpil Im
- Department of Biological Sciences, Lehigh University, Bethlehem, Pennsylvania 18015, United States
| | - Ratan K Mishra
- BASF SE, Molecular Modeling & Drug Discovery, Carl Bosch Str. 38, 67056 Ludwigshafen, Germany
| | - Hendrik Heinz
- Department of Chemical and Biological Engineering, University of Colorado at Boulder, Boulder, Colorado 80309, United States
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21
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Lin F, Li M, Zeng L, Luo M, Guo S. Intermetallic Nanocrystals for Fuel-Cells-Based Electrocatalysis. Chem Rev 2023; 123:12507-12593. [PMID: 37910391 DOI: 10.1021/acs.chemrev.3c00382] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2023]
Abstract
Electrocatalysis underpins the renewable electrochemical conversions for sustainability, which further replies on metallic nanocrystals as vital electrocatalysts. Intermetallic nanocrystals have been known to show distinct properties compared to their disordered counterparts, and been long explored for functional improvements. Tremendous progresses have been made in the past few years, with notable trend of more precise engineering down to an atomic level and the investigation transferring into more practical membrane electrode assembly (MEA), which motivates this timely review. After addressing the basic thermodynamic and kinetic fundamentals, we discuss classic and latest synthetic strategies that enable not only the formation of intermetallic phase but also the rational control of other catalysis-determinant structural parameters, such as size and morphology. We also demonstrate the emerging intermetallic nanomaterials for potentially further advancement in energy electrocatalysis. Then, we discuss the state-of-the-art characterizations and representative intermetallic electrocatalysts with emphasis on oxygen reduction reaction evaluated in a MEA setup. We summarize this review by laying out existing challenges and offering perspective on future research directions toward practicing intermetallic electrocatalysts for energy conversions.
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Affiliation(s)
- Fangxu Lin
- School of Materials Science and Engineering, Peking University, Beijing 100871, China
- Beijing Innovation Centre for Engineering Science and Advanced Technology, Peking University, Beijing 100871, China
| | - Menggang Li
- School of Materials Science and Engineering, Peking University, Beijing 100871, China
| | - Lingyou Zeng
- School of Materials Science and Engineering, Peking University, Beijing 100871, China
| | - Mingchuan Luo
- School of Materials Science and Engineering, Peking University, Beijing 100871, China
| | - Shaojun Guo
- School of Materials Science and Engineering, Peking University, Beijing 100871, China
- Beijing Innovation Centre for Engineering Science and Advanced Technology, Peking University, Beijing 100871, China
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22
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Shi B, Zen A, Kapil V, Nagy PR, Grüneis A, Michaelides A. Many-Body Methods for Surface Chemistry Come of Age: Achieving Consensus with Experiments. J Am Chem Soc 2023; 145:25372-25381. [PMID: 37948071 PMCID: PMC10683001 DOI: 10.1021/jacs.3c09616] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2023] [Revised: 10/15/2023] [Accepted: 10/17/2023] [Indexed: 11/12/2023]
Abstract
The adsorption energy of a molecule onto the surface of a material underpins a wide array of applications, spanning heterogeneous catalysis, gas storage, and many more. It is the key quantity where experimental measurements and theoretical calculations meet, with agreement being necessary for reliable predictions of chemical reaction rates and mechanisms. The prototypical molecule-surface system is CO adsorbed on MgO, but despite intense scrutiny from theory and experiment, there is still no consensus on its adsorption energy. In particular, the large cost of accurate many-body methods makes reaching converged theoretical estimates difficult, generating a wide range of values. In this work, we address this challenge, leveraging the latest advances in diffusion Monte Carlo (DMC) and coupled cluster with single, double, and perturbative triple excitations [CCSD(T)] to obtain accurate predictions for CO on MgO. These reliable theoretical estimates allow us to evaluate the inconsistencies in published temperature-programed desorption experiments, revealing that they arise from variations in employed pre-exponential factors. Utilizing this insight, we derive new experimental estimates of the (electronic) adsorption energy with a (more) precise pre-exponential factor. As a culmination of all of this effort, we are able to reach a consensus between multiple theoretical calculations and multiple experiments for the first time. In addition, we show that our recently developed cluster-based CCSD(T) approach provides a low-cost route toward achieving accurate adsorption energies. This sets the stage for affordable and reliable theoretical predictions of chemical reactions on surfaces to guide the realization of new catalysts and gas storage materials.
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Affiliation(s)
- Benjamin
X. Shi
- Yusuf
Hamied Department of Chemistry, University
of Cambridge, Lensfield Road, CB2 1EW Cambridge, U.K.
| | - Andrea Zen
- Dipartimento
di Fisica Ettore Pancini, Università
di Napoli Federico II, Monte S. Angelo, I-80126 Napoli, Italy
- Department
of Earth Sciences, University College London, Gower Street, WC1E 6BT London, U.K.
| | - Venkat Kapil
- Yusuf
Hamied Department of Chemistry, University
of Cambridge, Lensfield Road, CB2 1EW Cambridge, U.K.
| | - Péter R. Nagy
- Department
of Physical Chemistry and Materials Science, Faculty of Chemical Technology
and Biotechnology, Budapest University of
Technology and Economics, Müegyetem rkp. 3, H-1111 Budapest, Hungary
- HUN-REN-BME
Quantum Chemistry Research Group, Müegyetem rkp. 3, H-1111 Budapest, Hungary
- MTA-BME
Lendület Quantum Chemistry Research Group, Müegyetem rkp. 3, H-1111 Budapest, Hungary
| | - Andreas Grüneis
- Institute
for Theoretical Physics, TU Wien, Wiedner Hauptstraße 8-10/136, 1040 Vienna, Austria
| | - Angelos Michaelides
- Yusuf
Hamied Department of Chemistry, University
of Cambridge, Lensfield Road, CB2 1EW Cambridge, U.K.
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23
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Chen Z, Cao S, Li J, Yang C, Wei S, Liu S, Wang Z, Lu X. N,S coordination in Ni single-atom catalyst promoting CO 2RR towards HCOOH. Phys Chem Chem Phys 2023; 25:29951-29959. [PMID: 37902067 DOI: 10.1039/d3cp03722c] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/31/2023]
Abstract
Carbon-based single atom catalysts (SACs) are attracting extensive attention in the CO2 reduction reaction (CO2RR) due to their maximal atomic utilization, easily regulated active center and high catalytic activity, in which the coordination environment plays a crucial role in the intrinsic catalytic activity. Taking NiN4 as an example, this study reveals that the introduction of different numbers of S atoms into N coordination (Ni-NxS4-x (x = 1-4)) results in outstanding structural stability and catalytic activity. Owing to the additional orbitals around -1.60 eV and abundant Ni dxz, dyz, dx2, and dz2 orbital occupation after S substitution, N,S coordination can effectively facilitate the protonation of adsorbed intermediates and thus accelerate the overall CO2RR. The CO2RR mechanisms for CO and HCOOH generation via two-electron pathways are systematically elucidated on NiN4, NiN3S1 and NiN2S2. NiN2S2 yields HCOOH as the most favorable product with a limiting potential of -0.24 V, surpassing NiN4 (-1.14 V) and NiN3S1 (-0.50 V), which indicates that the different S-atom substitution of NiN4 has considerable influence on the CO2RR performance. This work highlights NiN2S2 as a high-performance CO2RR catalyst to produce HCOOH, and demonstrates that N,S coordination is an effective strategy to regulate the performance of atomically dispersed electrocatalysts.
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Affiliation(s)
- Zengxuan Chen
- School of Materials Science and Engineering, China University of Petroleum, Qingdao, Shandong 266580, P. R. China.
| | - Shoufu Cao
- School of Materials Science and Engineering, China University of Petroleum, Qingdao, Shandong 266580, P. R. China.
| | - Jiao Li
- School of Materials Science and Engineering, China University of Petroleum, Qingdao, Shandong 266580, P. R. China.
| | - Chunyu Yang
- School of Materials Science and Engineering, China University of Petroleum, Qingdao, Shandong 266580, P. R. China.
| | - Shuxian Wei
- College of Science, China University of Petroleum, Qingdao, Shandong 266580, P. R. China
| | - Siyuan Liu
- School of Materials Science and Engineering, China University of Petroleum, Qingdao, Shandong 266580, P. R. China.
| | - Zhaojie Wang
- School of Materials Science and Engineering, China University of Petroleum, Qingdao, Shandong 266580, P. R. China.
| | - Xiaoqing Lu
- School of Materials Science and Engineering, China University of Petroleum, Qingdao, Shandong 266580, P. R. China.
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24
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Abbaspourtamijani A, Chakraborty D, White HS, Neurock M, Qi Y. Tailoring Ag Electron Donating Ability for Organohalide Reduction: A Bilayer Electrode Design. LANGMUIR : THE ACS JOURNAL OF SURFACES AND COLLOIDS 2023; 39:15705-15715. [PMID: 37885069 DOI: 10.1021/acs.langmuir.3c02260] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/28/2023]
Abstract
Electrochemical reduction of organohalides provides a green approach in the reduction of environmental pollutants, the synthesis of new organic molecules, and many other applications. The presence of a catalytic electrode can make the process more energetically efficient. Ag is known to be a very good electrode for the reduction of a wide range of organohalides. Herein, we examine the elementary adsorption and reaction steps that occur on Ag and the changes that result from changes in the Ag-coated metal, strain in Ag, solvent, and substrate geometry. The results are used to develop an electrode design strategy that can possibly be used to further increase the catalytic activity of pure Ag electrodes. We have shown how epitaxially depositing one to three layers of Ag on catalytically inert or less active support metal can increase the surface electron donating ability, thus increasing the adsorption of organic halide and the catalytic activity. Many factors, such as molecular geometry, lattice mismatches, work function, and solvents, contribute to the adsorption of organic halide molecules over the bilayer electrode surface. To isolate and rank these factors, we examined three model organic halides, namely, halothane, bromobenzene (BrBz), and benzyl bromide (BzBr) adsorption on Ag/metal (metal = Au, Bi, Pt, and Ti) bilayer electrodes in both vacuum and acetonitrile (ACN) solvent. The different metal supports offer a range of lattice mismatches and work function differences with Ag. Our calculations show that the surface of Ag becomes more electron donating and accessible to adsorption when it forms a bilayer with Ti as it has a lower work function and almost zero lattice mismatch with Ag. We believe this study will help to increase the electron donating ability of the Ag surface by choosing the right metal support, which in turn can improve the catalytic activity of the working electrode.
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Affiliation(s)
- Ali Abbaspourtamijani
- School of Engineering, Brown University, Providence, Rhode Island 02912, United States
| | - Dwaipayan Chakraborty
- School of Engineering, Brown University, Providence, Rhode Island 02912, United States
| | - Henry Sheldon White
- Department of Chemistry, University of Utah, Salt Lake City, Utah 84112, United States
| | - Matthew Neurock
- Department of Chemical Engineering & Materials Science, University of Minnesota, Minneapolis, Minnesota 55455, United States
| | - Yue Qi
- School of Engineering, Brown University, Providence, Rhode Island 02912, United States
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25
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Kolodzeiski E, Stein CJ. Automated, Consistent, and Even-Handed Selection of Active Orbital Spaces for Quantum Embedding. J Chem Theory Comput 2023; 19:6643-6655. [PMID: 37775093 PMCID: PMC10569175 DOI: 10.1021/acs.jctc.3c00653] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Indexed: 10/01/2023]
Abstract
A widely used strategy to reduce the computational cost of quantum-chemical calculations is to partition the system into an active subsystem, which is the focus of the computational efforts, and an environment that is treated at a lower computational level. The system partitioning is mostly based on localized molecular orbitals. When reaction paths or energy differences are to be calculated, it is crucial to keep the orbital space consistent for all structures. Inconsistencies in orbital space can lead to unpredictable errors on the potential energy surface. While successful strategies to ensure this consistency have been established for organic and even metal-organic systems, these methods often fail for metal clusters or nanoparticles with a high density of near-degenerate and delocalized molecular orbitals. However, such systems are highly relevant for catalysis. Accurate yet feasible quantum-mechanical ab initio calculations are therefore highly desired. In this work, we present an approach based on the subsystem projected atomic orbital decomposition algorithm that allows us to ensure automated and consistent partitioning even for systems with delocalized and near-degenerate molecular orbitals and demonstrate the validity of this method for the binding energies of small molecules on transition-metal clusters.
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Affiliation(s)
- Elena Kolodzeiski
- Technical University of Munich, TUM
School of Natural Sciences, Department of Chemistry, Lichtenbergstr. 4, Garching D-85748, Germany
| | - Christopher J. Stein
- Technical University of Munich, TUM
School of Natural Sciences, Department of Chemistry, Lichtenbergstr. 4, Garching D-85748, Germany
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26
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Noh J, Chang H. Data-Driven Prediction of Configurational Stability of Molecule-Adsorbed Heterogeneous Catalysts. J Chem Inf Model 2023; 63:5981-5995. [PMID: 37715300 DOI: 10.1021/acs.jcim.3c00591] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/17/2023]
Abstract
The design of new heterogeneous catalysts that convert small molecules into valuable chemicals is a key challenge for constructing sustainable energy systems. Density functional theory (DFT)-based design frameworks based on the understanding of molecular adsorption on the catalytic surface have been widely proposed to accelerate experimental approaches to develop novel catalysts. In addition, a machine learning (ML)-combined design framework was recently proposed to further reduce the inherent time cost of DFT-based frameworks. However, because of the lack of prior information on chemical interactions between arbitrary surfaces and adsorbates, the efficacy of the computational screening approaches would be reduced by obtaining unexpected structural anomalies (i.e., abnormally converged surface-adsorbate geometries after the DFT calculations) during an exhaustive exploration of chemical space. To overcome this challenge, we propose an ML framework that directly predicts the configurational stability of a given initial surface-adsorbate geometry. Our benchmark experiments with the Open Catalysts 20 (OC20) dataset show promising performance on classifying stable geometry (i.e., F1-score of 0.922, the area under the receiver operating characteristics (AUROC) of 0.906, and Matthews correlation coefficient (MCC) of 0.633) with a high precision of 0.921 by utilizing an ensemble approach. We further interpret the generalizability and domain applicability of the trained model in terms of the chemical space of the OC20 dataset. Furthermore, from an experiment on the training set size dependence of model performance, we found that our ML model could be practically applicable to classify stable configurations even with a relatively small number of training data.
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Affiliation(s)
- Juhwan Noh
- Korea Research Institute of Chemical Technology (KRICT), Daejeon 34114, Republic of Korea
| | - Hyunju Chang
- Korea Research Institute of Chemical Technology (KRICT), Daejeon 34114, Republic of Korea
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27
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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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28
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Semidalas E, Martin JML. Correlation Consistent Basis Sets for Explicitly Correlated Theory: The Transition Metals. J Chem Theory Comput 2023; 19:5806-5820. [PMID: 37540641 PMCID: PMC10500978 DOI: 10.1021/acs.jctc.3c00506] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Indexed: 08/06/2023]
Abstract
We present correlation consistent basis sets for explicitly correlated (F12) calculations, denoted VnZ(-PP)-F12-wis (n = D,T), for the d-block elements. The cc-pVDZ-F12-wis basis set is contracted to [8s7p5d2f] for the 3d-block, while its ECP counterpart for the 4d and 5d-blocks, cc-pVDZ-PP-F12-wis, is contracted to [6s6p5d2f]. The corresponding contracted sizes for cc-pVTZ(-PP)-F12-wis are [9s8p6d3f2g] for the 3d-block elements and [7s7p6d3f2g] for the 4d and 5d-block elements. Our VnZ(-PP)-F12-wis basis sets are evaluated on challenging test sets for metal-organic barrier heights (MOBH35) and group-11 metal clusters (CUAGAU-2). In F12 calculations, they are found to be about as close to the complete basis set limit as the combination of standard cc-pVnZ-F12 on main-group elements with the standard aug-cc-pV(n+1)Z(-PP) basis sets on the transition metal(s). While our basis sets are somewhat more compact than aug-cc-pV(n+1)Z(-PP), the CPU time benefit is negligible for catalytic complexes that contain only one or two transition metals among dozens of main-group elements; however, it is somewhat more significant for metal clusters.
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Affiliation(s)
- Emmanouil Semidalas
- Department of Molecular Chemistry
and Materials Science, Weizmann Institute
of Science, 7610001 Reḥovot, Israel
| | - Jan M. L. Martin
- Department of Molecular Chemistry
and Materials Science, Weizmann Institute
of Science, 7610001 Reḥovot, Israel
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29
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Van Speybroeck V, Bocus M, Cnudde P, Vanduyfhuys L. Operando Modeling of Zeolite-Catalyzed Reactions Using First-Principles Molecular Dynamics Simulations. ACS Catal 2023; 13:11455-11493. [PMID: 37671178 PMCID: PMC10476167 DOI: 10.1021/acscatal.3c01945] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2023] [Revised: 07/27/2023] [Indexed: 09/07/2023]
Abstract
Within this Perspective, we critically reflect on the role of first-principles molecular dynamics (MD) simulations in unraveling the catalytic function within zeolites under operating conditions. First-principles MD simulations refer to methods where the dynamics of the nuclei is followed in time by integrating the Newtonian equations of motion on a potential energy surface that is determined by solving the quantum-mechanical many-body problem for the electrons. Catalytic solids used in industrial applications show an intriguing high degree of complexity, with phenomena taking place at a broad range of length and time scales. Additionally, the state and function of a catalyst critically depend on the operating conditions, such as temperature, moisture, presence of water, etc. Herein we show by means of a series of exemplary cases how first-principles MD simulations are instrumental to unravel the catalyst complexity at the molecular scale. Examples show how the nature of reactive species at higher catalytic temperatures may drastically change compared to species at lower temperatures and how the nature of active sites may dynamically change upon exposure to water. To simulate rare events, first-principles MD simulations need to be used in combination with enhanced sampling techniques to efficiently sample low-probability regions of phase space. Using these techniques, it is shown how competitive pathways at operating conditions can be discovered and how broad transition state regions can be explored. Interestingly, such simulations can also be used to study hindered diffusion under operating conditions. The cases shown clearly illustrate how first-principles MD simulations reveal insights into the catalytic function at operating conditions, which could not be discovered using static or local approaches where only a few points are considered on the potential energy surface (PES). Despite these advantages, some major hurdles still exist to fully integrate first-principles MD methods in a standard computational catalytic workflow or to use the output of MD simulations as input for multiple length/time scale methods that aim to bridge to the reactor scale. First of all, methods are needed that allow us to evaluate the interatomic forces with quantum-mechanical accuracy, albeit at a much lower computational cost compared to currently used density functional theory (DFT) methods. The use of DFT limits the currently attainable length/time scales to hundreds of picoseconds and a few nanometers, which are much smaller than realistic catalyst particle dimensions and time scales encountered in the catalysis process. One solution could be to construct machine learning potentials (MLPs), where a numerical potential is derived from underlying quantum-mechanical data, which could be used in subsequent MD simulations. As such, much longer length and time scales could be reached; however, quite some research is still necessary to construct MLPs for the complex systems encountered in industrially used catalysts. Second, most currently used enhanced sampling techniques in catalysis make use of collective variables (CVs), which are mostly determined based on chemical intuition. To explore complex reactive networks with MD simulations, methods are needed that allow the automatic discovery of CVs or methods that do not rely on a priori definition of CVs. Recently, various data-driven methods have been proposed, which could be explored for complex catalytic systems. Lastly, first-principles MD methods are currently mostly used to investigate local reactive events. We hope that with the rise of data-driven methods and more efficient methods to describe the PES, first-principles MD methods will in the future also be able to describe longer length/time scale processes in catalysis. This might lead to a consistent dynamic description of all steps-diffusion, adsorption, and reaction-as they take place at the catalyst particle level.
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Affiliation(s)
| | - Massimo Bocus
- Center for Molecular Modeling, Ghent University, Technologiepark 46, 9052 Zwijnaarde, Belgium
| | - Pieter Cnudde
- Center for Molecular Modeling, Ghent University, Technologiepark 46, 9052 Zwijnaarde, Belgium
| | - Louis Vanduyfhuys
- Center for Molecular Modeling, Ghent University, Technologiepark 46, 9052 Zwijnaarde, Belgium
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30
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Johnson MS, Gierada M, Hermes ED, Bross DH, Sargsyan K, Najm HN, Zádor J. Pynta─An Automated Workflow for Calculation of Surface and Gas-Surface Kinetics. J Chem Inf Model 2023; 63:5153-5168. [PMID: 37559203 DOI: 10.1021/acs.jcim.3c00948] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/11/2023]
Abstract
Many important industrial processes rely on heterogeneous catalytic systems. However, given all possible catalysts and conditions of interest, it is impractical to optimize most systems experimentally. Automatically generated microkinetic models can be used to efficiently consider many catalysts and conditions. However, these microkinetic models require accurate estimation of many thermochemical and kinetic parameters. Manually calculating these parameters is tedious and error prone, involving many interconnected computations. We present Pynta, a workflow software for automating the calculation of surface and gas-surface reactions. Pynta takes the reactants, products, and atom maps for the reactions of interest, generates sets of initial guesses for all species and saddle points, runs all optimizations, frequency, and IRC calculations, and computes the associated thermochemistry and rate coefficients. It is able to consider all unique adsorption configurations for both adsorbates and saddle points, allowing it to handle high index surfaces and bidentate species. Pynta implements a new saddle point guess generation method called harmonically forced saddle point searching (HFSP). HFSP defines harmonic potentials based on the optimized adsorbate geometries and which bonds are breaking and forming that allow initial placements to be optimized using the GFN1-xTB semiempirical method to create reliable saddle point guesses. This method is reaction class agnostic and fast, allowing Pynta to consider all possible adsorbate site placements efficiently. We demonstrate Pynta on 11 diverse reactions involving monodenate, bidentate, and gas-phase species, many distinct reaction classes, and both a low and a high index facet of Cu. Our results suggest that it is very important to consider reactions between adsorbates adsorbed in all unique configurations for interadsorbate group transfers and reactions on high index surfaces.
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Affiliation(s)
- Matthew S Johnson
- Combustion Research Facility, Sandia National Laboratories, Livermore, California 94550, United States
| | - Maciej Gierada
- Combustion Research Facility, Sandia National Laboratories, Livermore, California 94550, United States
| | - Eric D Hermes
- Combustion Research Facility, Sandia National Laboratories, Livermore, California 94550, United States
| | - David H Bross
- Chemical Sciences and Engineering Division, Argonne National Laboratory, Lemont, Illinois 60439, United States
| | - Khachik Sargsyan
- Combustion Research Facility, Sandia National Laboratories, Livermore, California 94550, United States
| | - Habib N Najm
- Combustion Research Facility, Sandia National Laboratories, Livermore, California 94550, United States
| | - Judit Zádor
- Combustion Research Facility, Sandia National Laboratories, Livermore, California 94550, United States
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31
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Xu L, Mavrikakis M. Adsorbate-Induced Adatom Formation on Lithium, Iron, Cobalt, Ruthenium, and Rhenium Surfaces. JACS AU 2023; 3:2216-2225. [PMID: 37654598 PMCID: PMC10466328 DOI: 10.1021/jacsau.3c00256] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/20/2023] [Revised: 06/27/2023] [Accepted: 06/28/2023] [Indexed: 09/02/2023]
Abstract
Recent experimental and theoretical studies have demonstrated the reaction-driven metal-metal bond breaking in metal catalytic surfaces even under relatively mild conditions. Here, we construct a density functional theory (DFT) database for the adsorbate-induced adatom formation energy on the close-packed facets of three hexagonal close-packed metals (Co, Ru, and Re) and two body-centered cubic metals (Li and Fe), where the source of the ejected metal atom is either a step edge or a close-packed surface. For Co and Ru, we also considered their metastable face-centered cubic structures. We studied 18 different adsorbates relevant to catalytic processes and predicted noticeably easier adatom formation on Li and Fe compared to the other three metals. The NH3- and CO-induced adatom formation on Fe(110) is possible at room temperature, a result relevant to NH3 synthesis and Fischer-Tropsch synthesis, respectively. There also exist other systems with favorable adsorbate effects for adatom formation relevant to catalytic processes at elevated temperatures (500-700 K). Our results offer insight into the reaction-driven formation of metal clusters, which could play the role of active sites in reactions catalyzed by Li, Fe, Co, Ru, and Re catalysts.
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Affiliation(s)
- Lang Xu
- Department of Chemical &
Biological Engineering, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
| | - Manos Mavrikakis
- Department of Chemical &
Biological Engineering, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
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32
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Hou B, Zheng H, Zhang K, Wu Q, Qin C, Sun C, Pan Q, Kang Z, Wang X, Su Z. Electron delocalization of robust high-nuclear bismuth-oxo clusters for promoted CO 2 electroreduction. Chem Sci 2023; 14:8962-8969. [PMID: 37621429 PMCID: PMC10445447 DOI: 10.1039/d3sc02924g] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Accepted: 07/31/2023] [Indexed: 08/26/2023] Open
Abstract
The integration of high activity, selectivity and stability in one electrocatalyst is highly desirable for electrochemical CO2 reduction (ECR), yet it is still a knotty issue. The unique electronic properties of high-nuclear clusters may bring about extraordinary catalytic performance; however, construction of a high-nuclear structure for ECR remains a challenging task. In this work, a family of calix[8]arene-protected bismuth-oxo clusters (BiOCs), including Bi4 (BiOC-1/2), Bi8Al (BiOC-3), Bi20 (BiOC-4), Bi24 (BiOC-5) and Bi40Mo2 (BiOC-6), were prepared and used as robust and efficient ECR catalysts. The Bi40Mo2 cluster in BiOC-6 is the largest metal-oxo cluster encapsulated by calix[8]arenes. As an electrocatalyst, BiOC-5 exhibited outstanding electrochemical stability and 97% Faraday efficiency for formate production at a low potential of -0.95 V vs. RHE, together with a high turnover frequency of up to 405.7 h-1. Theoretical calculations reveal that large-scale electron delocalization of BiOCs is achieved, which promotes structural stability and effectively decreases the energy barrier of rate-determining *OCHO generation. This work provides a new perspective for the design of stable high-nuclear clusters for efficient electrocatalytic CO2 conversion.
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Affiliation(s)
- Baoshan Hou
- Key Lab of Polyoxometalate Science of Ministry of Education, National & Local United Engineering Laboratory for Power Battery Institution, Northeast Normal University Changchun Jilin 130024 China
| | - Haiyan Zheng
- Key Lab of Polyoxometalate Science of Ministry of Education, National & Local United Engineering Laboratory for Power Battery Institution, Northeast Normal University Changchun Jilin 130024 China
| | - Kunhao Zhang
- Shanghai Synchrotron Radiation Facility 239 Zhangheng Road, Pudong New District Shanghai 200120 China
| | - Qi Wu
- Key Lab of Polyoxometalate Science of Ministry of Education, National & Local United Engineering Laboratory for Power Battery Institution, Northeast Normal University Changchun Jilin 130024 China
| | - Chao Qin
- Key Lab of Polyoxometalate Science of Ministry of Education, National & Local United Engineering Laboratory for Power Battery Institution, Northeast Normal University Changchun Jilin 130024 China
| | - Chunyi Sun
- Key Lab of Polyoxometalate Science of Ministry of Education, National & Local United Engineering Laboratory for Power Battery Institution, Northeast Normal University Changchun Jilin 130024 China
| | - Qinhe Pan
- Key Laboratory of Advanced Materials of Tropical Island Resources, Ministry of Education, Hainan University Haikou 570228 China
| | - Zhenhui Kang
- Institute of Functional Nano & Soft Materials, Jiangsu Key Laboratory for Carbon-Based Functional Materials & Devices, Soochow University Suzhou 215123 Jiangsu China
| | - Xinlong Wang
- Key Lab of Polyoxometalate Science of Ministry of Education, National & Local United Engineering Laboratory for Power Battery Institution, Northeast Normal University Changchun Jilin 130024 China
- Key Laboratory of Advanced Materials of Tropical Island Resources, Ministry of Education, Hainan University Haikou 570228 China
| | - Zhongmin Su
- Key Laboratory of Advanced Materials of Tropical Island Resources, Ministry of Education, Hainan University Haikou 570228 China
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33
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Chen BWJ, Zhang X, Zhang J. Accelerating explicit solvent models of heterogeneous catalysts with machine learning interatomic potentials. Chem Sci 2023; 14:8338-8354. [PMID: 37564405 PMCID: PMC10411631 DOI: 10.1039/d3sc02482b] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Accepted: 07/11/2023] [Indexed: 08/12/2023] Open
Abstract
Realistically modelling how solvents affect catalytic reactions is a longstanding challenge due to its prohibitive computational cost. Typically, an explicit atomistic treatment of the solvent molecules is needed together with molecular dynamics (MD) simulations and enhanced sampling methods. Here, we demonstrate the utility of machine learning interatomic potentials (MLIPs), coupled with active learning, to enable fast and accurate explicit solvent modelling of adsorption and reactions on heterogeneous catalysts. MLIPs trained on-the-fly were able to accelerate ab initio MD simulations by up to 4 orders of magnitude while reproducing with high fidelity the geometrical features of water in the bulk and at metal-water interfaces. Using these ML-accelerated simulations, we accurately predicted key catalytic quantities such as the adsorption energies of CO*, OH*, COH*, HCO*, and OCCHO* on Cu surfaces and the free energy barriers of C-H scission of ethylene glycol over Cu and Pd surfaces, as validated with ab initio calculations. We envision that such simulations will pave the way towards detailed and realistic studies of solvated catalysts at large time- and length-scales.
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Affiliation(s)
- Benjamin W J Chen
- Institute of High Performance Computing (IHPC), Agency for Science, Technology and Research (A*STAR) 1 Fusionopolis Way, #16-16 Connexis Singapore 138632 Singapore
| | - Xinglong Zhang
- Institute of High Performance Computing (IHPC), Agency for Science, Technology and Research (A*STAR) 1 Fusionopolis Way, #16-16 Connexis Singapore 138632 Singapore
| | - Jia Zhang
- Institute of High Performance Computing (IHPC), Agency for Science, Technology and Research (A*STAR) 1 Fusionopolis Way, #16-16 Connexis Singapore 138632 Singapore
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34
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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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35
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Rapetti D, Delle Piane M, Cioni M, Polino D, Ferrando R, Pavan GM. Machine learning of atomic dynamics and statistical surface identities in gold nanoparticles. Commun Chem 2023; 6:143. [PMID: 37407706 DOI: 10.1038/s42004-023-00936-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Accepted: 06/19/2023] [Indexed: 07/07/2023] Open
Abstract
It is known that metal nanoparticles (NPs) may be dynamic and atoms may move within them even at fairly low temperatures. Characterizing such complex dynamics is key for understanding NPs' properties in realistic regimes, but detailed information on, e.g., the stability, survival, and interconversion rates of the atomic environments (AEs) populating them are non-trivial to attain. In this study, we decode the intricate atomic dynamics of metal NPs by using a machine learning approach analyzing high-dimensional data obtained from molecular dynamics simulations. Using different-shape gold NPs as a representative example, an AEs' dictionary allows us to label step-by-step the individual atoms in the NPs, identifying the native and non-native AEs and populating them along the MD simulations at various temperatures. By tracking the emergence, annihilation, lifetime, and dynamic interconversion of the AEs, our approach permits estimating a "statistical equivalent identity" for metal NPs, providing a comprehensive picture of the intrinsic atomic dynamics that shape their properties.
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Affiliation(s)
- Daniele Rapetti
- Department of Applied Science and Technology, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129, Torino, Italy
| | - Massimo Delle Piane
- Department of Applied Science and Technology, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129, Torino, Italy
| | - Matteo Cioni
- Department of Applied Science and Technology, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129, Torino, Italy
| | - Daniela Polino
- Department of Innovative Technologies, University of Applied Sciences and Arts of Southern Switzerland, Polo Universitario Lugano, Campus Est, Via la Santa 1, 6962, Lugano-Viganello, Switzerland
| | - Riccardo Ferrando
- Department of Physics, Università degli Studi di Genova, Via Dodecaneso 33, 16146, Genova, Italy
| | - Giovanni M Pavan
- Department of Applied Science and Technology, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129, Torino, Italy.
- Department of Innovative Technologies, University of Applied Sciences and Arts of Southern Switzerland, Polo Universitario Lugano, Campus Est, Via la Santa 1, 6962, Lugano-Viganello, Switzerland.
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36
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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: 3] [Impact Index Per Article: 3.0] [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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37
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Yadavalli SS, Jones G, Benson RL, Stamatakis M. Assessing the Impact of Adlayer Description Fidelity on Theoretical Predictions of Coking on Ni(111) at Steam Reforming Conditions. THE JOURNAL OF PHYSICAL CHEMISTRY. C, NANOMATERIALS AND INTERFACES 2023; 127:8591-8606. [PMID: 37197383 PMCID: PMC10184169 DOI: 10.1021/acs.jpcc.3c02323] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Revised: 04/13/2023] [Indexed: 05/19/2023]
Abstract
Methane steam reforming is an important industrial process for hydrogen production, employing Ni as a low-cost, highly active catalyst, which, however, suffers from coking due to methane cracking. Coking is the accumulation of a stable poison over time, occurring at high temperatures; thus, to a first approximation, it can be treated as a thermodynamic problem. In this work, we developed an Ab initio kinetic Monte Carlo (KMC) model for methane cracking on Ni(111) at steam reforming conditions. The model captures C-H activation kinetics in detail, while graphene sheet formation is described at the level of thermodynamics, to obtain insights into the "terminal (poisoned) state" of graphene/coke within reasonable computational times. We used cluster expansions (CEs) of progressively higher fidelity to systematically assess the influence of effective cluster interactions between adsorbed or covalently bonded C and CH species on the "terminal state" morphology. Moreover, we compared the predictions of KMC models incorporating these CEs into mean-field microkinetic models in a consistent manner. The models show that the "terminal state" changes significantly with the level of fidelity of the CEs. Furthermore, high-fidelity simulations predict C-CH island/rings that are largely disconnected at low temperatures but completely encapsulate the Ni(111) surface at high temperatures.
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Affiliation(s)
- Sai Sharath Yadavalli
- Thomas
Young Centre and Department of Chemical Engineering, University College London, Roberts Building, Torrington Place, London WC1E 7JE, U.K.
| | - Glenn Jones
- Johnson
Matthey Technology Centre, Sonning Common, Reading RG4 9NH, U.K.
| | - Raz L. Benson
- Thomas
Young Centre and Department of Chemical Engineering, University College London, Roberts Building, Torrington Place, London WC1E 7JE, U.K.
| | - Michail Stamatakis
- Thomas
Young Centre and Department of Chemical Engineering, University College London, Roberts Building, Torrington Place, London WC1E 7JE, U.K.
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38
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Shayesteh Zadeh A, Khan SA, Vandervelden C, Peters B. Site-Averaged Ab Initio Kinetics: Importance Learning for Multistep Reactions on Amorphous Supports. J Chem Theory Comput 2023; 19:2873-2886. [PMID: 37093705 DOI: 10.1021/acs.jctc.3c00160] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/25/2023]
Abstract
Single-atom centers on amorphous supports include catalysts for polymerization, partial oxidation, metathesis, hydrogenolysis, and more. The disordered environment makes each site different, and the kinetics exponentially magnifies these differences to make ab initio site-averaged kinetics calculations extremely difficult. This work extends the importance learning algorithm for efficient and precise site-averaged kinetics estimates to ab initio calculations and multistep reaction mechanisms. Specifically, we calculate site-averaged proton transfer relaxation rates on an ensemble of cluster models representing Brønsted acid sites on silica-alumina. We include direct and water-assisted proton transfer pathways and simultaneously estimate the water adsorption and activation enthalpies for forward and backward proton transfers. We use density functional theory (DFT) to obtain a site-averaged rate, somewhat like a turnover frequency, for the proton transfer relaxation rate. Finally, we show that importance learning can provide orders-of-magnitude acceleration over standard sampling methods for site-averaged rate calculations in cases where the rate is dominated by a few highly active sites.
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Affiliation(s)
- Armin Shayesteh Zadeh
- Chemical and Biomolecular Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States
| | - Salman A Khan
- Delaware Energy Institute (DEI), University of Delaware, Newark, Delaware 19711, United States
| | | | - Baron Peters
- Chemical and Biomolecular Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States
- Department of Chemistry, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States
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39
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Xu L, Papanikolaou KG, Lechner BAJ, Je L, Somorjai GA, Salmeron M, Mavrikakis M. Formation of active sites on transition metals through reaction-driven migration of surface atoms. Science 2023; 380:70-76. [PMID: 37023183 DOI: 10.1126/science.add0089] [Citation(s) in RCA: 20] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/08/2023]
Abstract
Adopting low-index single-crystal surfaces as models for metal nanoparticle catalysts has been questioned by the experimental findings of adsorbate-induced formation of subnanometer clusters on several single-crystal surfaces. We used density functional theory calculations to elucidate the conditions that lead to cluster formation and show how adatom formation energies enable efficient screening of the conditions required for adsorbate-induced cluster formation. We studied a combination of eight face-centered cubic transition metals and 18 common surface intermediates and identified systems relevant to catalytic reactions, such as carbon monoxide (CO) oxidation and ammonia (NH3) oxidation. We used kinetic Monte Carlo simulations to elucidate the CO-induced cluster formation process on a copper surface. Scanning tunneling microscopy of CO on a nickel (111) surface that contains steps and dislocations points to the structure sensitivity of this phenomenon. Metal-metal bond breaking that leads to the evolution of catalyst structures under realistic reaction conditions occurs much more broadly than previously thought.
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Affiliation(s)
- Lang Xu
- Department of Chemical and Biological Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA
| | | | - Barbara A J Lechner
- Department of Chemistry and Catalysis Research Center, School of Natural Sciences, Technical University of Munich, 85748 Garching, Germany
- Division of Materials Science, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
| | - Lisa Je
- Department of Chemical and Biological Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA
| | - Gabor A Somorjai
- Division of Materials Science, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
- Department of Chemistry, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Miquel Salmeron
- Division of Materials Science, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
- Department of Materials Science and Engineering, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Manos Mavrikakis
- Department of Chemical and Biological Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA
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40
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Rebarchik M, Bhandari S, Kropp T, Mavrikakis M. Insights into the Oxygen Evolution Reaction on Graphene-Based Single-Atom Catalysts from First-Principles-Informed Microkinetic Modeling. ACS Catal 2023. [DOI: 10.1021/acscatal.3c00474] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/03/2023]
Affiliation(s)
- Michael Rebarchik
- Department of Chemical and Biological Engineering, University of Wisconsin-Madison, 1415 Engineering Drive, Madison, Wisconsin 53706, United States
| | - Saurabh Bhandari
- Department of Chemical and Biological Engineering, University of Wisconsin-Madison, 1415 Engineering Drive, Madison, Wisconsin 53706, United States
| | - Thomas Kropp
- Department of Chemical and Biological Engineering, University of Wisconsin-Madison, 1415 Engineering Drive, Madison, Wisconsin 53706, United States
| | - Manos Mavrikakis
- Department of Chemical and Biological Engineering, University of Wisconsin-Madison, 1415 Engineering Drive, Madison, Wisconsin 53706, United States
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41
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Chen BW. Equilibrium and kinetic isotope effects in heterogeneous catalysis: A density functional theory perspective. CATAL COMMUN 2023. [DOI: 10.1016/j.catcom.2023.106654] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/29/2023] Open
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42
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Bridging the complexity gap in computational heterogeneous catalysis with machine learning. Nat Catal 2023. [DOI: 10.1038/s41929-023-00911-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/03/2023]
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43
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Chen Z, Liu Z, Xu X. Accurate descriptions of molecule-surface interactions in electrocatalytic CO 2 reduction on the copper surfaces. Nat Commun 2023; 14:936. [PMID: 36807556 PMCID: PMC9941474 DOI: 10.1038/s41467-023-36695-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Accepted: 02/14/2023] [Indexed: 02/22/2023] Open
Abstract
Copper-based catalysts play a pivotal role in many industrial processes and hold a great promise for electrocatalytic CO2 reduction reaction into valuable chemicals and fuels. Towards the rational design of catalysts, the growing demand on theoretical study is seriously at odds with the low accuracy of the most widely used functionals of generalized gradient approximation. Here, we present results using a hybrid scheme that combines the doubly hybrid XYG3 functional and the periodic generalized gradient approximation, whose accuracy is validated against an experimental set on copper surfaces. A near chemical accuracy is established for this set, which, in turn, leads to a substantial improvement for the calculated equilibrium and onset potentials as against the experimental values for CO2 reduction to CO on Cu(111) and Cu(100) electrodes. We anticipate that the easy use of the hybrid scheme will boost the predictive power for accurate descriptions of molecule-surface interactions in heterogeneous catalysis.
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Affiliation(s)
- Zheng Chen
- grid.8547.e0000 0001 0125 2443Collaborative Innovation Center of Chemistry for Energy Materials, Shanghai Key Laboratory of Molecular Catalysis and Innovative Materials, MOE Key Laboratory of Computational Physical Sciences, Department of Chemistry, Fudan University, 200433 Shanghai, People’s Republic of China
| | - Zhangyun Liu
- grid.8547.e0000 0001 0125 2443Collaborative Innovation Center of Chemistry for Energy Materials, Shanghai Key Laboratory of Molecular Catalysis and Innovative Materials, MOE Key Laboratory of Computational Physical Sciences, Department of Chemistry, Fudan University, 200433 Shanghai, People’s Republic of China
| | - Xin Xu
- Collaborative Innovation Center of Chemistry for Energy Materials, Shanghai Key Laboratory of Molecular Catalysis and Innovative Materials, MOE Key Laboratory of Computational Physical Sciences, Department of Chemistry, Fudan University, 200433, Shanghai, People's Republic of China. .,Hefei National Laboratory, 230088, Hefei, P. R. China.
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44
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Tran R, Lan J, Shuaibi M, Wood BM, Goyal S, Das A, Heras-Domingo J, Kolluru A, Rizvi A, Shoghi N, Sriram A, Therrien F, Abed J, Voznyy O, Sargent EH, Ulissi Z, Zitnick CL. The Open Catalyst 2022 (OC22) Dataset and Challenges for Oxide Electrocatalysts. ACS Catal 2023. [DOI: 10.1021/acscatal.2c05426] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/18/2023]
Affiliation(s)
- Richard Tran
- Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania 15217, United States
| | - Janice Lan
- Fundamental AI Research, Meta AI, Menlo Park, California 94025, United States
| | - Muhammed Shuaibi
- Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania 15217, United States
- Fundamental AI Research, Meta AI, Menlo Park, California 94025, United States
| | - Brandon M. Wood
- Fundamental AI Research, Meta AI, Menlo Park, California 94025, United States
| | - Siddharth Goyal
- Fundamental AI Research, Meta AI, Menlo Park, California 94025, United States
| | - Abhishek Das
- Fundamental AI Research, Meta AI, Menlo Park, California 94025, United States
| | - Javier Heras-Domingo
- Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania 15217, United States
| | - Adeesh Kolluru
- Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania 15217, United States
| | - Ammar Rizvi
- Fundamental AI Research, Meta AI, Menlo Park, California 94025, United States
| | - Nima Shoghi
- Fundamental AI Research, Meta AI, Menlo Park, California 94025, United States
| | - Anuroop Sriram
- Fundamental AI Research, Meta AI, Menlo Park, California 94025, United States
| | - Félix Therrien
- Department of Electrical and Computer Engineering, University of Toronto, 10 King’s College Road, Toronto, Ontario M5S 3G4, Canada
- Department of Physical and Environmental Sciences, University of Toronto Scarborough, Scarborough, Ontario M1C 1A4, Canada
| | - Jehad Abed
- Department of Electrical and Computer Engineering, University of Toronto, 10 King’s College Road, Toronto, Ontario M5S 3G4, Canada
- Department of Materials Science and Engineering, University of Toronto, 10 King’s College Road, Toronto, Ontario M5S 3G4, Canada
| | - Oleksandr Voznyy
- Department of Physical and Environmental Sciences, University of Toronto Scarborough, Scarborough, Ontario M1C 1A4, Canada
| | - Edward H. Sargent
- Department of Electrical and Computer Engineering, University of Toronto, 10 King’s College Road, Toronto, Ontario M5S 3G4, Canada
| | - Zachary Ulissi
- Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania 15217, United States
- Scott Institute for Energy Innovation, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, United States
| | - C. Lawrence Zitnick
- Fundamental AI Research, Meta AI, Menlo Park, California 94025, United States
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45
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Rosen AS, Vijay S, Persson KA. Free-atom-like d states beyond the dilute limit of single-atom alloys. Chem Sci 2023; 14:1503-1511. [PMID: 36794204 PMCID: PMC9906637 DOI: 10.1039/d2sc05772g] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Accepted: 01/13/2023] [Indexed: 01/21/2023] Open
Abstract
Through a data-mining and high-throughput density functional theory approach, we identify a diverse range of metallic compounds that are predicted to have transition metals with "free-atom-like" d states that are highly localized in terms of their energetic distribution. Design principles that favor the formation of localized d states are uncovered, among which we note that site isolation is often necessary but that the dilute limit, as in most single-atom alloys, is not a pre-requisite. Additionally, the majority of localized d state transition metals identified from the computational screening study exhibit partial anionic character due to charge transfer from neighboring metal species. Using CO as a representative probe molecule, we show that localized d states for Rh, Ir, Pd, and Pt tend to reduce the binding strength of CO compared to their pure elemental analogues, whereas this does not occur as consistently for the Cu binding sites. These trends are rationalized through the d-band model, which suggests that the significantly reduced d-band width results in an increased orthogonalization energy penalty upon CO chemisorption. With the multitude of inorganic solids that are predicted to have highly localized d states, the results of the screening study are likely to result in new avenues for heterogeneous catalyst design from an electronic structure perspective.
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Affiliation(s)
- Andrew S. Rosen
- Department of Materials Science and Engineering, University of California, BerkeleyBerkeleyCalifornia94720USA,Miller Institute for Basic Research in Science, University of California, BerkeleyBerkeleyCalifornia 94720USA,Materials Science Division, Lawrence Berkeley National LaboratoryBerkeleyCalifornia 94720USA
| | - Sudarshan Vijay
- Department of Materials Science and Engineering, University of California, BerkeleyBerkeleyCalifornia94720USA,Materials Science Division, Lawrence Berkeley National LaboratoryBerkeleyCalifornia 94720USA
| | - Kristin A. Persson
- Department of Materials Science and Engineering, University of California, BerkeleyBerkeleyCalifornia94720USA,Molecular Foundry, Lawrence Berkeley National LaboratoryBerkeleyCalifornia 94720USA
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46
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Molecular Dynamics Approach to the Physical Mixture of In 2O 3 and ZrO 2: Defect Formation and Ionic Diffusion. Int J Mol Sci 2023; 24:ijms24032426. [PMID: 36768746 PMCID: PMC9917225 DOI: 10.3390/ijms24032426] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Revised: 01/23/2023] [Accepted: 01/23/2023] [Indexed: 01/28/2023] Open
Abstract
Recent research on the use of physical mixtures In2O3-ZrO2 has raised interesting questions as to how their combination enhances catalytic activity and selectivity. Specifically, the relationship between oxygen diffusion and defect formation and the epitaxial tension in the mixture should be further investigated. In this study, we aim to clarify some of these relationships through a molecular dynamics approach. Various potentials for the two oxides are compared and selected to describe the physical mixture of In2O3 and ZrO2. Different configurations of each single crystal and their physical mixture are simulated, and oxygen defect formation and diffusion are measured and compared. Significant oxygen defect formation is found in both crystals. In2O3 seems to be stabilized by the mixture, while ZrO2 is destabilized. Similar results were found for the ZrO2 doping with In and ln2O3 doping with Zr. The results explain the high activity and selectivity catalyst activity of the mixture for the production of isobutylene from ethanol.
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47
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Dietze EM, Grönbeck H. Ensemble Effects in Adsorbate-Adsorbate Interactions in Microkinetic Modeling. J Chem Theory Comput 2023; 19:1044-1049. [PMID: 36652690 PMCID: PMC9933425 DOI: 10.1021/acs.jctc.2c01005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
Adsorbates on a surface experience lateral interactions that result in a distribution of adsorption energies. The adsorbate-adsorbate interactions are known to affect the kinetics of surface reactions, which motivates efforts to develop models that accurately account for the interactions. Here, we use density functional theory (DFT) calculations combined with Monte Carlo simulations to investigate how the distribution of adsorbates affects adsorption and desorption of CO from Pt(111). We find that the mean of the average adsorption energy determines the adsorption process, whereas the desorption process can be described by the low energy part of the adsorbate stability distribution. The simulated results are in very good agreement with calorimetry and temperature-programmed desorption experiments and provide a guideline of how to include adsorbate-adsorbate interactions in DFT-based mean-field kinetic models.
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48
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Copper-Based Metal–Organic Frameworks (MOFs) as an Emerging Catalytic Framework for Click Chemistry. Catalysts 2023. [DOI: 10.3390/catal13010130] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023] Open
Abstract
In the extensive terrain of catalytic procedures for the synthesis of organic molecules, metal–organic frameworks (MOFs) as heterogenous catalysts have been investigated in a variety of chemical processes, including Friedel–Crafts reactions, condensation reactions, oxidations, and coupling reactions, and utilized owing to their specific properties such as high porosity, tuneability, extraordinary catalytic activity, and recyclability. The eminent copper-tailored MOF materials can be exceptionally dynamic and regioselective catalysts for click reactions (1,3-dipolar cycloaddition reaction). Considering the fact that Cu(I)-catalyzed alkyne–azide cycloaddition (CuAAC) reactions can be catalyzed by several other copper catalysts such as Cu (II)-β-cyclodextrin, Cu(OAc)2, Fe3O4@SiO2, picolinimidoamide–Cu(II) complex, and Cu(II) porphyrin graphene, the properties of sorption and reusability, as well as the high density of copper-MOFs, open an efficient and robust pathway for regimented catalysis of this reaction. This review provides a comprehensive description and analysis of the relevant literature on the utilization of Cu-MOFs as catalysts for CuAAC ‘click’ reactions published in the past decade.
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49
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Rusalev YV, Motseyko AV, Guda AA, Guda SA, Soldatov AV, Ter-Oganessian NV. Development of a ReaxFF potential for Au-Pd. JOURNAL OF PHYSICS. CONDENSED MATTER : AN INSTITUTE OF PHYSICS JOURNAL 2022; 35:065901. [PMID: 36368048 DOI: 10.1088/1361-648x/aca250] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Accepted: 11/10/2022] [Indexed: 06/16/2023]
Abstract
The bimetallic alloys often outperform their single-component counterparts due to synergistic effects. Being widely known, the Au-Pd alloy is a promising candidate for the novel heterogeneous nanocatalysts. Rational design of such systems requires theoretical simulations under ambient conditions.Ab initioquantum-mechanical calculations employ the density functional theory (DFT) and are limited to the systems with few tens of atoms and short timescales. The alternative solution implies development of reliable atomistic potentials. Among different approaches ReaxFF combines chemical accuracy and low computational costs. However, the development of a new potential is a problem without unique solution and thus requires accurate validation criteria. In this work we construct ReaxFF potential for the Au-Pd system based onab initioDFT calculations for bulk structures, slabs and nanoparticles with different stoichiometry. The validation was performed with molecular dynamics and Monte-Carlo calculations. We present several optimal parametrizations that describe experimental bulk mechanical and thermal properties, atomic order-disorder phase transition temperatures and the resulting ordered crystal structures.
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Affiliation(s)
- Yu V Rusalev
- The Smart Materials Research Institute, Southern Federal University, Sladkova 178/24, Rostov-on-Don 344090, Russia
| | - A V Motseyko
- Institute of Physics, Southern Federal University, Stachki 194, Rostov-on-Don 344090, Russia
| | - A A Guda
- The Smart Materials Research Institute, Southern Federal University, Sladkova 178/24, Rostov-on-Don 344090, Russia
| | - S A Guda
- The Smart Materials Research Institute, Southern Federal University, Sladkova 178/24, Rostov-on-Don 344090, Russia
- Institute of mathematics, mechanics and computer science, Southern Federal University, Milchakova 8a, 344090 Rostov-on-Don, Russia
| | - A V Soldatov
- The Smart Materials Research Institute, Southern Federal University, Sladkova 178/24, Rostov-on-Don 344090, Russia
| | - N V Ter-Oganessian
- Institute of Physics, Southern Federal University, Stachki 194, Rostov-on-Don 344090, Russia
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50
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Rangarajan S, Tian H. Improving the predictive power of microkinetic models via machine learning. Curr Opin Chem Eng 2022. [DOI: 10.1016/j.coche.2022.100858] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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