1
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Feng Y, Grönbeck H. Kinetic Monte Carlo Simulations of Low-Temperature NH 3-SCR over Cu-Exchanged Chabazite. Chemphyschem 2024; 25:e202400558. [PMID: 38941111 DOI: 10.1002/cphc.202400558] [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: 05/15/2024] [Revised: 06/27/2024] [Accepted: 06/28/2024] [Indexed: 06/29/2024]
Abstract
Cu-exchanged chabazite (Cu-CHA) is widely used for ammonia assisted selective catalytic reduction of nitrogen oxides (NH3-SCR). The Cu+ ions are at low temperatures solvated by NH3 forming mobile [Cu(NH3)2]+ complexes. The dynamic behaviour of the complexes is critical as O2 adsorption requires a pair of complexes to form a [Cu2(NH3)4O2]2+ peroxo-species over which NO couples with NH3. Here we introduce a first principles-based kinetic Monte Carlo approach to explore the effect of the Al-distribution on the reaction kinetics of NH3-SCR over Cu-CHA. The method allows us to scrutinize the interplay between the pairing of [Cu(NH3)2]+ complexes and the reaction landscape for the NH3-SCR reaction over the peroxo-complex. The Al-distribution affects the stability of the [Cu(NH3)2]+ pairs as well as the kinetic parameters of the SCR-reaction. The turn-over frequency is determined by the stability of the [Cu(NH3)2]+ pairs and the relative strength of NO and NH3 adsorption once a pair is present. The results establish the hierarchy of effects that influences the performance of Cu-CHA over NH3-SCR and provide a computational basis for further development of the Cu-CHA material.
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Affiliation(s)
- Yingxin Feng
- 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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2
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Chen Z, Liu W, Shan B, Pei Y. Analytical approach to structural chemistry origins of mechanical, acoustical and thermal properties. Natl Sci Rev 2024; 11:nwae269. [PMID: 39188384 PMCID: PMC11345612 DOI: 10.1093/nsr/nwae269] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2024] [Revised: 07/28/2024] [Accepted: 07/30/2024] [Indexed: 08/28/2024] Open
Abstract
Crystalline matters with periodically arranged atoms found wide applications in modern science and technology. To facilitate the design of new materials and the advancement of existing ones, accurate and efficient models without relying too much on known inputs for predicting the functionalities are essential. Here, we propose an analytical approach for such a purpose, with only the knowledge of the structural chemistry of crystals. Based on the electrostatic interaction between periodically arranged atoms, the 1st, 2nd and 3rd derivatives of interatomic potential, respectively, enable a prediction of ten kinds in total of mechanical, acoustical and thermal properties. Over a thousand measurements are collected from ∼500 literatures, this results in the symmetric mean percentage error (SMPE) within ±25% and the symmetric mean absolute percentage error (SMAPE) ranging from 22%∼74% across all properties predicted, which further enables a revelation of bond characteristics as the most important but implicit origin for functionalities.
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Affiliation(s)
- Zhiwei Chen
- Interdisciplinary Materials Research Center, School of Materials Science and Engineering, Tongji University, Shanghai 201804, China
| | - Wei Liu
- Interdisciplinary Materials Research Center, School of Materials Science and Engineering, Tongji University, Shanghai 201804, China
| | - Bing Shan
- Interdisciplinary Materials Research Center, School of Materials Science and Engineering, Tongji University, Shanghai 201804, China
| | - Yanzhong Pei
- Interdisciplinary Materials Research Center, School of Materials Science and Engineering, Tongji University, Shanghai 201804, China
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3
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Yang X, Shi Y, Zhang H, Chen Z. Utilizing a synergistic strategy that combines electromagnetic and chemical enhancement to analyze the SERS effect of the Fe 3O 4@GO@Ag on PAHs detection. J Colloid Interface Sci 2024; 678:532-539. [PMID: 39214005 DOI: 10.1016/j.jcis.2024.08.204] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2024] [Revised: 07/31/2024] [Accepted: 08/24/2024] [Indexed: 09/04/2024]
Abstract
A comprehensive understanding of the enhancement mechanism of the substrate material is crucial to ensure the repeatability and functionality of SERS detection technology. Therefore, this study introduces a theoretical analysis method that integrates electromagnetic and chemical enhancement to achieve a comprehensive understanding of the SERS effect on the magnetic composite substrate. The visual model is employed in this study to comprehensively analyze and illustrate the electric field enhancement and optical effects of composite substrate materials. The study also elucidated the adsorption and charge transfer between the substrate material and target molecules. Based on this theory, Fe3O4@GO@Ag material was prepared and used to detect hydrophobic organic molecules such as polycyclic aromatic hydrocarbons (PAHs), with a concentration as low as 0.5 nM. This study comprehensively analyzed the SERS enhancement effect of the composite substrate for the first time, and prepared a magnetic composite substrate material for the detection of hydrophobic organic molecules, opening up a new avenue for theoretical guidance and experimental exploration in SERS detection and analysis.
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Affiliation(s)
- Xu Yang
- Heilongjiang Province Key Laboratory of Laser Spectroscopy Technology and Application, Harbin University of Science and Technology, Harbin 150080, China
| | - Yunbo Shi
- Heilongjiang Province Key Laboratory of Laser Spectroscopy Technology and Application, Harbin University of Science and Technology, Harbin 150080, China.
| | - Haoze Zhang
- School of Instrumentation Science and Engineering, Harbin 150006, China
| | - Zhaoyu Chen
- Space Environment Simulation Research Infrastructure, Harbin 150006, China
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4
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Keller E, Morgenstein J, Reuter K, Margraf JT. Small basis set density functional theory method for cost-efficient, large-scale condensed matter simulations. J Chem Phys 2024; 161:074104. [PMID: 39145548 DOI: 10.1063/5.0222649] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2024] [Accepted: 07/30/2024] [Indexed: 08/16/2024] Open
Abstract
We present an efficient first-principles based method geared toward reliably predicting the structures of solid materials across the Periodic Table. To this end, we use a density functional theory baseline with a compact, near-minimal min+s basis set, yielding low computational costs and memory demands. Since the use of such a small basis set leads to systematic errors in chemical bond lengths, we develop a linear pairwise correction, available for elements Z = 1-86 (excluding the lanthanide series), parameterized for use with the Perdew-Burke-Ernzerhof exchange-correlation functional. We demonstrate the reliability of this corrected approach for equilibrium volumes across the Periodic Table and the transferability to differently coordinated environments and multi-elemental crystals. We examine relative energies, forces, and stresses in geometry optimizations and molecular dynamics simulations.
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Affiliation(s)
- Elisabeth Keller
- Fritz Haber Institute of the Max Planck Society, Berlin, Germany
- Bavarian Center for Battery Technology (BayBatt) and Chair of Physical Chemistry V, University of Bayreuth, Bayreuth, Germany
| | | | - Karsten Reuter
- Fritz Haber Institute of the Max Planck Society, Berlin, Germany
| | - Johannes T Margraf
- Fritz Haber Institute of the Max Planck Society, Berlin, Germany
- Bavarian Center for Battery Technology (BayBatt) and Chair of Physical Chemistry V, University of Bayreuth, Bayreuth, Germany
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5
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Gao Y, Zhu B. Simulating Structural Dynamics of Metal Catalysts under Operative Conditions. J Phys Chem Lett 2024; 15:8351-8359. [PMID: 39110671 DOI: 10.1021/acs.jpclett.4c01907] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/16/2024]
Abstract
Structural reconstructions of metal catalysts have been recognized as common phenomena during catalytic reactions, which play a key role in their activities in heterogeneous catalysis. Precisely identifying the structures under the operative conditions becomes a prerequisite to establish a reliable structure-activity relationship and further rationalize the design of metal catalysts. However, real-time capture of the structural variations of catalysts at the atomic level with high-temporal resolution is a grand challenge for present in situ characterizations. During the past decade, significant progress has been made in theory to couple the structures with the reaction conditions to reproduce the experimental observations and predict the adsorbate-induced changes of catalysts in composition, morphology, size, etc. Modeling the dynamic correlation between the structure and activity of the metal catalysts brings us advanced knowledge of heterogeneous catalysis and becomes indispensable for accurate evaluation of the performance of metal catalysts.
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Affiliation(s)
- 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
| | - Beien Zhu
- 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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6
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Litman Y, Kapil V, Feldman YMY, Tisi D, Begušić T, Fidanyan K, Fraux G, Higer J, Kellner M, Li TE, Pós ES, Stocco E, Trenins G, Hirshberg B, Rossi M, Ceriotti M. i-PI 3.0: A flexible and efficient framework for advanced atomistic simulations. J Chem Phys 2024; 161:062504. [PMID: 39140447 DOI: 10.1063/5.0215869] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2024] [Accepted: 07/11/2024] [Indexed: 08/15/2024] Open
Abstract
Atomic-scale simulations have progressed tremendously over the past decade, largely thanks to the availability of machine-learning interatomic potentials. These potentials combine the accuracy of electronic structure calculations with the ability to reach extensive length and time scales. The i-PI package facilitates integrating the latest developments in this field with advanced modeling techniques thanks to a modular software architecture based on inter-process communication through a socket interface. The choice of Python for implementation facilitates rapid prototyping but can add computational overhead. In this new release, we carefully benchmarked and optimized i-PI for several common simulation scenarios, making such overhead negligible when i-PI is used to model systems up to tens of thousands of atoms using widely adopted machine learning interatomic potentials, such as Behler-Parinello, DeePMD, and MACE neural networks. We also present the implementation of several new features, including an efficient algorithm to model bosonic and fermionic exchange, a framework for uncertainty quantification to be used in conjunction with machine-learning potentials, a communication infrastructure that allows for deeper integration with electronic-driven simulations, and an approach to simulate coupled photon-nuclear dynamics in optical or plasmonic cavities.
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Affiliation(s)
- Yair Litman
- Y. Hamied Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, United Kingdom
| | - Venkat Kapil
- Y. Hamied Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, United Kingdom
- Department of Physics and Astronomy, University College London, 17-19 Gordon St, London WC1H 0AH, United Kingdom
- Thomas Young Centre and London Centre for Nanotechnology, 19 Gordon St, London WC1H 0AH, United Kingdom
| | | | - Davide Tisi
- Laboratory of Computational Science and Modeling, Institut des Matériaux, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Tomislav Begušić
- Div. of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California 91125, USA
| | - Karen Fidanyan
- MPI for the Structure and Dynamics of Matter, Hamburg, Germany
| | - Guillaume Fraux
- Laboratory of Computational Science and Modeling, Institut des Matériaux, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Jacob Higer
- School of Physics, Tel Aviv University, Tel Aviv 6997801, Israel
| | - Matthias Kellner
- Laboratory of Computational Science and Modeling, Institut des Matériaux, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Tao E Li
- Department of Physics and Astronomy, University of Delaware, Newark, Delaware 19716, USA
| | - Eszter S Pós
- MPI for the Structure and Dynamics of Matter, Hamburg, Germany
| | - Elia Stocco
- MPI for the Structure and Dynamics of Matter, Hamburg, Germany
| | - George Trenins
- MPI for the Structure and Dynamics of Matter, Hamburg, Germany
| | - Barak Hirshberg
- School of Chemistry, Tel Aviv University, Tel Aviv 6997801, Israel
| | - Mariana Rossi
- MPI for the Structure and Dynamics of Matter, Hamburg, Germany
| | - Michele Ceriotti
- Laboratory of Computational Science and Modeling, Institut des Matériaux, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
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7
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Qiu C, Chen J, Huan F, Deng S, Yao Z, Wang S, Wang J. Curing and Cross-Linking Processes in the Poly(3,3-bis-azidomethyl oxetane)-tetrahydrofuran/Toluene Diisocyanate/Trimethylolpropane System: A Density Functional Theory and Accelerated ReaxFF Molecular Dynamics Investigation. ACS OMEGA 2024; 9:33153-33161. [PMID: 39100291 PMCID: PMC11292815 DOI: 10.1021/acsomega.4c04558] [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: 05/14/2024] [Revised: 06/14/2024] [Accepted: 06/19/2024] [Indexed: 08/06/2024]
Abstract
The physical and chemical properties of solid propellant are influenced by the composition and structure of the binder, with its network structure being formed through curing and cross-linking reactions. Therefore, understanding the mechanisms of these reactions is crucial. In this study, we investigated the curing and cross-linking mechanisms of poly(3,3-bis-azidomethyl oxetane)-tetrahydrofuran (PBT), toluene diisocyanate (TDI), and trimethylolpropane (TMP) using a combination of density functional theory (DFT) calculations and accelerated ReaxFF molecular dynamics (MD) simulations. DFT calculations revealed that the steric effect of the -CH3 group in TDI exerts a significant influence on the curing reaction between TDI and PBT. Additionally, in the cross-linking process, the energy barrier for TDI reacting with TMP was found to be much lower than that for TDI reacting with the PBT-TDI intermediate. Subsequently, we conducted competing reaction processes of TMP/TDI-PBT-TDI cross-linking and TDI-PBT-TDI self-cross-linking using accelerated MD simulations within the fitted ReaxFF framework. The results showed that the successful frequency of TMP/TDI-PBT-TDI cross-linking was substantially higher than that of TDI-PBT-TDI self-cross-linking, consistent with the energy barrier results from DFT calculations. These findings deepen our understanding of the curing and cross-linking mechanisms of the PBT system, providing valuable insights for the optimization and design of solid propellants.
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Affiliation(s)
- Chenglong Qiu
- Institute
of Industrial Catalysis, State Key Laboratory Breeding Base of Green-Chemical
Synthesis Technology, College of Chemical Engineering, Zhejiang University of Technology, Hangzhou 310032, P. R. China
| | - Jianfa Chen
- Shanghai
Space Propulsion Technology Research Institute, Shanghai 201112, China
| | - Feicheng Huan
- Institute
of Industrial Catalysis, State Key Laboratory Breeding Base of Green-Chemical
Synthesis Technology, College of Chemical Engineering, Zhejiang University of Technology, Hangzhou 310032, P. R. China
| | - Shengwei Deng
- Institute
of Industrial Catalysis, State Key Laboratory Breeding Base of Green-Chemical
Synthesis Technology, College of Chemical Engineering, Zhejiang University of Technology, Hangzhou 310032, P. R. China
| | - Zihao Yao
- Institute
of Industrial Catalysis, State Key Laboratory Breeding Base of Green-Chemical
Synthesis Technology, College of Chemical Engineering, Zhejiang University of Technology, Hangzhou 310032, P. R. China
| | - Shibin Wang
- Institute
of Industrial Catalysis, State Key Laboratory Breeding Base of Green-Chemical
Synthesis Technology, College of Chemical Engineering, Zhejiang University of Technology, Hangzhou 310032, P. R. China
| | - Jianguo Wang
- Institute
of Industrial Catalysis, State Key Laboratory Breeding Base of Green-Chemical
Synthesis Technology, College of Chemical Engineering, Zhejiang University of Technology, Hangzhou 310032, P. R. China
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8
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Gu K, Lin S. Advances in the Dynamics of Adsorbate Diffusion on Metal Surfaces: Focus on Hydrogen and Oxygen. Chemphyschem 2024; 25:e202400083. [PMID: 38511509 DOI: 10.1002/cphc.202400083] [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: 01/28/2024] [Revised: 02/26/2024] [Accepted: 03/21/2024] [Indexed: 03/22/2024]
Abstract
Adsorbates on metal surfaces are typically formed from the dissociative chemisorption of molecules occurring at gas-solid interfaces. These adsorbed species exhibit unique diffusion behaviors on metal surfaces, which are influenced by their translational energy. They play crucial roles in various fields, including heterogeneous catalysis and corrosion. This review examines recent theoretical advancements in understanding the diffusion dynamics of adsorbates on metal surfaces, with a specific emphasis on hydrogen and oxygen atoms. The diffusion processes of adsorbates on metal surfaces involve two energy transfer mechanisms: surface phonons and electron-hole pair excitations. This review also surveys new theoretical methods, including the characterization of the electron-hole pair excitation within electronic friction models, the acceleration of quantum chemistry calculations through machine learning, and the treatment of atomic nuclear motion from both quantum mechanical and classical perspectives. Furthermore, this review offers valuable insights into how energy transfer, nuclear quantum effects, supercell sizes, and the topography of potential energy surfaces impact the diffusion behavior of hydrogen and oxygen species on metal surfaces. Lastly, some preliminary research proposals are presented.
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Affiliation(s)
- Kaixuan Gu
- State Key Laboratory of Photocatalysis on Energy and Environment, College of Chemistry, Fuzhou University, Fuzhou, 350002, China
| | - Sen Lin
- State Key Laboratory of Photocatalysis on Energy and Environment, College of Chemistry, Fuzhou University, Fuzhou, 350002, China
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9
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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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10
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Qian S, Dai T, Feng K, Li Z, Sun X, Chen Y, Nie K, Yan B, Cheng Y. Design Principle of Molybdenum-Based Metal Nitrides for Lattice Nitrogen-Mediated Ammonia Production. JACS AU 2024; 4:1975-1985. [PMID: 38818058 PMCID: PMC11134358 DOI: 10.1021/jacsau.4c00194] [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: 03/02/2024] [Revised: 04/30/2024] [Accepted: 05/01/2024] [Indexed: 06/01/2024]
Abstract
Chemical looping ammonia synthesis (CLAS) is a promising technology for reducing the high energy consumption of the conventional ammonia synthesis process. However, the comprehensive understanding of reaction mechanisms and rational design of novel nitrogen carriers has not been achieved due to the high complexity of catalyst structures and the unrevealed relationship between electronic structure and intrinsic activity. Herein, we propose a multistage strategy to establish the connection between catalyst intrinsic activity and microscopic electronic structure fingerprints using density functional theory computational energetics as bridges and apply it to the rational design of metal nitride catalysts for lattice nitrogen-mediated ammonia production. Molybdenum-based nitride catalysts with well-defined structures are employed as prototypes to elucidate the decoupled effects of electronic and geometrical features. The electron-transfer and spin polarization characteristics of the magnetic metals are constructed as descriptors to disclose the atomic-scale causes of intrinsic activity. Based on this design strategy, it is demonstrated that Ni3Mo3N catalysts possess the highest lattice nitrogen-mediated ammonia synthesis activity. This work reveals the structure-activity relationship of metal nitrides for CLAS and provides a multistage perspective on catalyst rational design.
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Affiliation(s)
- Shuairen Qian
- Department
of Chemical Engineering, Tsinghua University, Beijing 100084, P. R. China
| | - Tianying Dai
- Department
of Chemical Engineering, Tsinghua University, Beijing 100084, P. R. China
| | - Kai Feng
- Institute
of Functional Nano & Soft Materials (FUNSOM), Soochow University, Suzhou, Jiangsu 215123, P. R. China
| | - Zhengwen Li
- Department
of Chemical Engineering, Tsinghua University, Beijing 100084, P. R. China
| | - Xiaohang Sun
- Department
of Chemical Engineering, Tsinghua University, Beijing 100084, P. R. China
| | - Yuxin Chen
- Department
of Chemical Engineering, Tsinghua University, Beijing 100084, P. R. China
| | - Kaiqi Nie
- Department
of Chemical Engineering, Tsinghua University, Beijing 100084, P. R. China
| | - Binhang Yan
- Department
of Chemical Engineering, Tsinghua University, Beijing 100084, P. R. China
| | - Yi Cheng
- Department
of Chemical Engineering, Tsinghua University, Beijing 100084, P. R. China
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11
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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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12
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Van den Bossche M. Three-Center Tight-Binding Together with Multipolar Auxiliary Functions. J Chem Theory Comput 2024; 20:2538-2550. [PMID: 38483273 DOI: 10.1021/acs.jctc.4c00018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/27/2024]
Abstract
We present an ab initio tight-binding method that allows to improve on the effective potential and minimal basis approximations employed in semiempirical calculations. Three-center expansions are used to evaluate the zeroth-order Hamiltonian matrix elements and repulsive energy terms in the spirit of the Horsfield method. Self-consistency is handled by expanding atomic orbital products in an auxiliary basis following the work of Giese and York, combined with a two-center expansion of the exchange-correlation kernels. Together with nonminimal main basis sets (double-ζ plus polarization), we show that the resulting method trades a modest amount of accuracy for a significant gain in speed, compared to that of numerical atomic orbital density functional theory, in calculations on small molecules, bulk compounds, and metal nanoclusters.
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13
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Xu W, Diesen E, He T, Reuter K, Margraf JT. Discovering High Entropy Alloy Electrocatalysts in Vast Composition Spaces with Multiobjective Optimization. J Am Chem Soc 2024; 146:7698-7707. [PMID: 38466356 PMCID: PMC10958507 DOI: 10.1021/jacs.3c14486] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2023] [Revised: 02/21/2024] [Accepted: 02/26/2024] [Indexed: 03/13/2024]
Abstract
High entropy alloys (HEAs) are a highly promising class of materials for electrocatalysis as their unique active site distributions break the scaling relations that limit the activity of conventional transition metal catalysts. Existing Bayesian optimization (BO)-based virtual screening approaches focus on catalytic activity as the sole objective and correspondingly tend to identify promising materials that are unlikely to be entropically stabilized. Here, we overcome this limitation with a multiobjective BO framework for HEAs that simultaneously targets activity, cost-effectiveness, and entropic stabilization. With diversity-guided batch selection further boosting its data efficiency, the framework readily identifies numerous promising candidates for the oxygen reduction reaction that strike the balance between all three objectives in hitherto unchartered HEA design spaces comprising up to 10 elements.
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Affiliation(s)
- Wenbin Xu
- Fritz-Haber-Institut
der Max-Planck-Gesellschaft, Berlin D-14195, Germany
- Lawrence
Berkeley National Laboratory, Berkeley, California 94720, United States
| | - Elias Diesen
- Fritz-Haber-Institut
der Max-Planck-Gesellschaft, Berlin D-14195, Germany
| | - Tianwei He
- Yunnan
Key Laboratory for Micro/Nano Materials & Technology, National
Center for International Research on Photoelectric and Energy Materials,
School of Materials and Energy, Yunnan University, Kunming 650091, China
| | - Karsten Reuter
- Fritz-Haber-Institut
der Max-Planck-Gesellschaft, Berlin D-14195, Germany
| | - Johannes T. Margraf
- Fritz-Haber-Institut
der Max-Planck-Gesellschaft, Berlin D-14195, Germany
- Bavarian
Center for Battery Technology (BayBatt), University of Bayreuth, Bayreuth D-95447, Germany
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14
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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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15
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Luo W, Yan X, Pan X, Jiao J, Mai L. What Makes On-Chip Microdevices Stand Out in Electrocatalysis? SMALL (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2024; 20:e2305020. [PMID: 37875658 DOI: 10.1002/smll.202305020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Revised: 09/03/2023] [Indexed: 10/26/2023]
Abstract
Clean and sustainable energy conversion and storage through electrochemistry shows great promise as an alternative to traditional fuel or fossil-consumption energy systems. With regards to practical and high-efficient electrochemistry application, the rational design of active sites and the accurate description of mechanism remain a challenge. Toward this end, in this Perspective, a unique on-chip micro/nano device coupling nanofabrication and low-dimensional electrochemical materials is presented, in which material structure analysis, field-effect regulation, in situ monitoring, and simulation modeling are highlighted. The critical mechanisms that influence electrochemical response are discussed, and how on-chip micro/nano device distinguishes itself is emphasized. The key challenges and opportunities of on-chip electrochemical platforms are also provided through the Perspective.
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Affiliation(s)
- Wen Luo
- Department of Physics, School of Science, Wuhan University of Technology, Wuhan, 430070, China
- State Key Laboratory of Advanced Technology for Materials Synthesis and Processing, Wuhan University of Technology, Wuhan, 430070, China
| | - Xin Yan
- Department of Physics, School of Science, Wuhan University of Technology, Wuhan, 430070, China
- State Key Laboratory of Advanced Technology for Materials Synthesis and Processing, Wuhan University of Technology, Wuhan, 430070, China
| | - Xuelei Pan
- State Key Laboratory of Advanced Technology for Materials Synthesis and Processing, Wuhan University of Technology, Wuhan, 430070, China
- Wolfson Catalysis Centre, Department of Chemistry, University of Oxford, Oxford, OX1 3QR, UK
| | - Jinying Jiao
- Department of Physics, School of Science, Wuhan University of Technology, Wuhan, 430070, China
- State Key Laboratory of Advanced Technology for Materials Synthesis and Processing, Wuhan University of Technology, Wuhan, 430070, China
| | - Liqiang Mai
- State Key Laboratory of Advanced Technology for Materials Synthesis and Processing, Wuhan University of Technology, Wuhan, 430070, China
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16
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Deshpande S, Vlachos DG. A Data and DFT-Driven Framework for Predicting the Microstructure of Submonolayer Inverse Metal Oxide on Metal Catalysts. J Phys Chem Lett 2024:2715-2722. [PMID: 38428034 DOI: 10.1021/acs.jpclett.4c00220] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/03/2024]
Abstract
Metal oxides on metal (inverse) catalysts can selectively drive many important reactions. However, understanding the active site under experimentally relevant conditions is lacking. Herein, we introduce a computational framework for predicting atomic models of stable inverse catalysts and demonstrate it for WOx on Pt(553) and a Pt79 nanoparticle at variable WOx coverages. An evolutionary algorithm identifies a small (5%) subset of promising atomic configurations on which DFT simulations are performed. We predict a maximum coverage of ∼50% WOx on Pt(553), consisting of small clusters (tetramers and pentamers), which preferentially reside on the terrace, with their oxygen atoms interacting with the Pt step sites. Consistently, WOx does not lie on curved and undercoordinated metal sites of Pt nanoparticles. The oxide clusters prefer a partially reduced oxidation state. Theoretical EXAFS spectra for select configurations provide insights into interpreting experimental spectra of inverse catalysts. The framework applies to other catalysts.
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Affiliation(s)
- Siddharth Deshpande
- Catalysis Center for Energy Innovation, 221 Academy Street, Newark, Delaware 19716, United States
- Department of Chemical and Biomolecular Engineering, University of Delaware, 150 Academy Street, Newark, Delaware 19716, United States
| | - Dionisios G Vlachos
- Catalysis Center for Energy Innovation, 221 Academy Street, Newark, Delaware 19716, United States
- Department of Chemical and Biomolecular Engineering, University of Delaware, 150 Academy Street, Newark, Delaware 19716, United States
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17
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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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18
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Sabadell-Rendón A, Kaźmierczak K, Morandi S, Euzenat F, Curulla-Ferré D, López N. Automated MUltiscale simulation environment. DIGITAL DISCOVERY 2023; 2:1721-1732. [PMID: 38054103 PMCID: PMC10694852 DOI: 10.1039/d3dd00163f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/23/2023] [Accepted: 11/05/2023] [Indexed: 12/07/2023]
Abstract
Multiscale techniques integrating detailed atomistic information on materials and reactions to predict the performance of heterogeneous catalytic full-scale reactors have been suggested but lack seamless implementation. The largest challenges in the multiscale modeling of reactors can be grouped into two main categories: catalytic complexity and the difference between time and length scales of chemical and transport phenomena. Here we introduce the Automated MUltiscale Simulation Environment AMUSE, a workflow that starts from Density Functional Theory (DFT) data, automates the analysis of the reaction networks through graph theory, prepares it for microkinetic modeling, and subsequently integrates the results into a standard open-source Computational Fluid Dynamics (CFD) code. We demonstrate the capabilities of AMUSE by applying it to the unimolecular iso-propanol dehydrogenation reaction and then, increasing the complexity, to the pre-commercial Pd/In2O3 catalyst employed for the CO2 hydrogenation to methanol. The results show that AMUSE allows the computational investigation of heterogeneous catalytic reactions in a comprehensive way, providing essential information for catalyst design from the atomistic to the reactor scale level.
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Affiliation(s)
- Albert Sabadell-Rendón
- Institute of Chemical Research of Catalonia (ICIQ-CERCA), The Barcelona Institute of Science and Technology, (BIST) Av. Paisos Catalans 16 Tarragona 43007 Spain
| | - Kamila Kaźmierczak
- TotalEnergies, TotalEnergies One Tech Belgium Zone industrielle C, 7181 Feluy Belgium
| | - Santiago Morandi
- Institute of Chemical Research of Catalonia (ICIQ-CERCA), The Barcelona Institute of Science and Technology, (BIST) Av. Paisos Catalans 16 Tarragona 43007 Spain
- Department of Physical and Inorganic Chemistry, Universitat Rovira i Virgili Campus Sescelades, N4 Block, C. Marcel·lí Domingo 1 Tarragona 43007 Spain
| | - Florian Euzenat
- TotalEnergies Research and Technology Gonfreville, Route Industrielle, Carrefour 4, Port 4864 76700 Rogerville France
| | - Daniel Curulla-Ferré
- TotalEnergies, TotalEnergies One Tech Belgium Zone industrielle C, 7181 Feluy Belgium
| | - Núria López
- Institute of Chemical Research of Catalonia (ICIQ-CERCA), The Barcelona Institute of Science and Technology, (BIST) Av. Paisos Catalans 16 Tarragona 43007 Spain
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19
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Laurent H, Hughes MDG, Walko M, Brockwell DJ, Mahmoudi N, Youngs TGA, Headen TF, Dougan L. Visualization of Self-Assembly and Hydration of a β-Hairpin through Integrated Small and Wide-Angle Neutron Scattering. Biomacromolecules 2023; 24:4869-4879. [PMID: 37874935 PMCID: PMC10646990 DOI: 10.1021/acs.biomac.3c00583] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Revised: 10/03/2023] [Indexed: 10/26/2023]
Abstract
Fundamental understanding of the structure and assembly of nanoscale building blocks is crucial for the development of novel biomaterials with defined architectures and function. However, accessing self-consistent structural information across multiple length scales is challenging. This limits opportunities to exploit atomic scale interactions to achieve emergent macroscale properties. In this work we present an integrative small- and wide-angle neutron scattering approach coupled with computational modeling to reveal the multiscale structure of hierarchically self-assembled β hairpins in aqueous solution across 4 orders of magnitude in length scale from 0.1 Å to 300 nm. Our results demonstrate the power of this self-consistent cross-length scale approach and allows us to model both the large-scale self-assembly and small-scale hairpin hydration of the model β hairpin CLN025. Using this combination of techniques, we map the hydrophobic/hydrophilic character of this model self-assembled biomolecular surface with atomic resolution. These results have important implications for the multiscale investigation of aqueous peptides and proteins, for the prediction of ligand binding and molecular associations for drug design, and for understanding the self-assembly of peptides and proteins for functional biomaterials.
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Affiliation(s)
- Harrison Laurent
- School
of Physics and Astronomy, University of
Leeds, Leeds, United Kingdom, LS2
9JT
| | - Matt D. G. Hughes
- School
of Physics and Astronomy, University of
Leeds, Leeds, United Kingdom, LS2
9JT
- Astbury
Centre for Structural Molecular Biology, University of Leeds, Leeds, United Kingdom LS2
9JT
| | - Martin Walko
- School
of Chemistry, University of Leeds, Leeds, United
Kingdom, LS2 9JT
| | - David J. Brockwell
- Astbury
Centre for Structural Molecular Biology, University of Leeds, Leeds, United Kingdom LS2
9JT
| | - Najet Mahmoudi
- ISIS
Neutron and Muon Source, Rutherford Appleton
Laboratory, Harwell Oxford, Didcot, United Kingdom, OX11 0QX
| | - Tristan G. A. Youngs
- ISIS
Neutron and Muon Source, Rutherford Appleton
Laboratory, Harwell Oxford, Didcot, United Kingdom, OX11 0QX
| | - Thomas F. Headen
- ISIS
Neutron and Muon Source, Rutherford Appleton
Laboratory, Harwell Oxford, Didcot, United Kingdom, OX11 0QX
| | - Lorna Dougan
- School
of Physics and Astronomy, University of
Leeds, Leeds, United Kingdom, LS2
9JT
- Astbury
Centre for Structural Molecular Biology, University of Leeds, Leeds, United Kingdom LS2
9JT
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20
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Stocker S, Jung H, Csányi G, Goldsmith CF, Reuter K, Margraf JT. Estimating Free Energy Barriers for Heterogeneous Catalytic Reactions with Machine Learning Potentials and Umbrella Integration. J Chem Theory Comput 2023; 19:6796-6804. [PMID: 37747812 PMCID: PMC10569033 DOI: 10.1021/acs.jctc.3c00541] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Indexed: 09/27/2023]
Abstract
Predicting the rate constants of elementary reaction steps is key for the computational modeling of catalytic processes. Within transition state theory (TST), this requires an accurate estimation of the corresponding free energy barriers. While sophisticated methods for estimating free energy differences exist, these typically require extensive (biased) molecular dynamics simulations that are computationally prohibitive with the first-principles electronic structure methods that are typically used in catalysis research. In this contribution, we show that machine-learning (ML) interatomic potentials can be trained in an automated iterative workflow to perform such free energy calculations at a much reduced computational cost as compared to a direct density functional theory (DFT) based evaluation. For the decomposition of CHO on Rh(111), we find that thermal effects are substantial and lead to a decrease in the free energy barrier, which can be vanishingly small, depending on the DFT functional used. This is in stark contrast to previously reported estimates based on a harmonic TST approximation, which predicted an increase in the barrier at elevated temperatures. Since CHO is the reactant of the putative rate limiting reaction step in syngas conversion on Rh(111) and essential for the selectivity toward oxygenates containing multiple carbon atoms (C2+ oxygenates), our results call into question the reported mechanism established by microkinetic models.
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Affiliation(s)
- Sina Stocker
- Fritz-Haber-Institut
der Max-Planck-Gesellschaft, Faradayweg 4-6, 14195 Berlin, Germany
| | - Hyunwook Jung
- Fritz-Haber-Institut
der Max-Planck-Gesellschaft, Faradayweg 4-6, 14195 Berlin, Germany
| | - Gábor Csányi
- Engineering
Laboratory, University of Cambridge, Cambridge CB2 1PZ, United Kingdom
| | - C. Franklin Goldsmith
- Fritz-Haber-Institut
der Max-Planck-Gesellschaft, Faradayweg 4-6, 14195 Berlin, Germany
- School
of Engineering, Brown University, Providence, Rhode Island 02912, United States
| | - Karsten Reuter
- Fritz-Haber-Institut
der Max-Planck-Gesellschaft, Faradayweg 4-6, 14195 Berlin, Germany
| | - Johannes T. Margraf
- Fritz-Haber-Institut
der Max-Planck-Gesellschaft, Faradayweg 4-6, 14195 Berlin, Germany
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21
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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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22
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Wilsey MK, Taseska T, Meng Z, Yu W, Müller AM. Advanced electrocatalytic redox processes for environmental remediation of halogenated organic water pollutants. Chem Commun (Camb) 2023; 59:11895-11922. [PMID: 37740361 DOI: 10.1039/d3cc03176d] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/24/2023]
Abstract
Halogenated organic compounds are widespread, and decades of heavy use have resulted in global bioaccumulation and contamination of the environment, including water sources. Here, we introduce the most common halogenated organic water pollutants, their classification by type of halogen (fluorine, chlorine, or bromine), important policies and regulations, main applications, and environmental and human health risks. Remediation techniques are outlined with particular emphasis on carbon-halogen bond strengths. Aqueous advanced redox processes are discussed, highlighting mechanistic details, including electrochemical oxidations and reductions of the water-oxygen system, and thermodynamic potentials, protonation states, and lifetimes of radicals and reactive oxygen species in aqueous electrolytes at different pH conditions. The state of the art of aqueous advanced redox processes for brominated, chlorinated, and fluorinated organic compounds is presented, along with reported mechanisms for aqueous destruction of select PFAS (per- and polyfluoroalkyl substances). Future research directions for aqueous electrocatalytic destruction of organohalogens are identified, emphasizing the crucial need for developing a quantitative mechanistic understanding of degradation pathways, the improvement of analytical detection methods for organohalogens and transient species during advanced redox processes, and the development of new catalysts and processes that are globally scalable.
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Affiliation(s)
- Madeleine K Wilsey
- Materials Science Program, University of Rochester, Rochester, New York 14627, USA.
| | - Teona Taseska
- Department of Chemical Engineering, University of Rochester, Rochester, New York 14627, USA
| | - Ziyi Meng
- Materials Science Program, University of Rochester, Rochester, New York 14627, USA.
| | - Wanqing Yu
- Department of Chemical Engineering, University of Rochester, Rochester, New York 14627, USA
| | - Astrid M Müller
- Materials Science Program, University of Rochester, Rochester, New York 14627, USA.
- Department of Chemical Engineering, University of Rochester, Rochester, New York 14627, USA
- Department of Chemistry, University of Rochester, Rochester, New York 14627, USA
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23
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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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24
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Ojelade OA. CO 2 Hydrogenation to Gasoline and Aromatics: Mechanistic and Predictive Insights from DFT, DRIFTS and Machine Learning. Chempluschem 2023; 88:e202300301. [PMID: 37580947 DOI: 10.1002/cplu.202300301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Revised: 08/10/2023] [Accepted: 08/14/2023] [Indexed: 08/16/2023]
Abstract
The emission of CO2 from fossil fuels is the largest driver of global climate change. To realize the target of a carbon-neutrality by 2050, CO2 capture and utilization is crucial. The efficient conversion of CO2 to C5+ gasoline and aromatics remains elusive mainly due to CO2 thermodynamic stability and the high energy barrier of the C-C coupling step. Herein, advances in mechanistic understanding via Diffuse Reflectance Infrared Fourier Transform Spectroscopy (DRIFTS), density functional theory (DFT), and microkinetic modeling are discussed. It further emphasizes the power of machine learning (ML) to accelerate the search for optimal catalysts. A significant effort has been invested into this field of research with volumes of experimental and characterization data, this study discusses how they can be used as input features for machine learning prediction in a bid to better understand catalytic properties capable of accelerating breakthroughs in the process.
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Affiliation(s)
- Opeyemi A Ojelade
- School of Chemical & Biomolecular Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
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25
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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: 6] [Impact Index Per Article: 6.0] [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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26
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Hao Z, Yang C, Huang K. A robust sparse identification method for nonlinear dynamic systems affected by non-stationary noise. CHAOS (WOODBURY, N.Y.) 2023; 33:083119. [PMID: 37549114 DOI: 10.1063/5.0164484] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Accepted: 07/24/2023] [Indexed: 08/09/2023]
Abstract
In the field of science and engineering, identifying the nonlinear dynamics of systems from data is a significant yet challenging task. In practice, the collected data are often contaminated by noise, which often severely reduce the accuracy of the identification results. To address the issue of inaccurate identification induced by non-stationary noise in data, this paper proposes a method called weighted ℓ1-regularized and insensitive loss function-based sparse identification of dynamics. Specifically, the robust identification problem is formulated using a sparse identification mathematical model that takes into account the presence of non-stationary noise in a quantitative manner. Then, a novel weighted ℓ1-regularized and insensitive loss function is proposed to account for the nature of non-stationary noise. Compared to traditional loss functions like least squares and least absolute deviation, the proposed method can mitigate the adverse effects of non-stationary noise and better promote the sparsity of results, thereby enhancing the accuracy of identification. Third, to overcome the non-smooth nature of the objective function induced by the inclusion of loss and regularization terms, a smooth approximation of the non-smooth objective function is presented, and the alternating direction multiplier method is utilized to develop an efficient optimization algorithm. Finally, the robustness of the proposed method is verified by extensive experiments under different types of nonlinear dynamical systems. Compared to some state-of-the-art methods, the proposed method achieves better identification accuracy.
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Affiliation(s)
- Zhihang Hao
- School of Automation, Central South University, Changsha 410083, China
| | - Chunhua Yang
- School of Automation, Central South University, Changsha 410083, China
| | - Keke Huang
- School of Automation, Central South University, Changsha 410083, China
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27
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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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28
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Ruiz VG, Wagner C, Maaß F, Arefi HH, Stremlau S, Tegeder P, Tautz FS, Tkatchenko A. Accurate quantification of the stability of the perylene-tetracarboxylic dianhydride on Au(111) molecule-surface interface. Commun Chem 2023; 6:136. [PMID: 37400714 DOI: 10.1038/s42004-023-00925-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Accepted: 06/05/2023] [Indexed: 07/05/2023] Open
Abstract
Studying inorganic/organic hybrid systems is a stepping stone towards the design of increasingly complex interfaces. A predictive understanding requires robust experimental and theoretical tools to foster trust in the obtained results. The adsorption energy is particularly challenging in this respect, since experimental methods are scarce and the results have large uncertainties even for the most widely studied systems. Here we combine temperature-programmed desorption (TPD), single-molecule atomic force microscopy (AFM), and nonlocal density-functional theory (DFT) calculations, to accurately characterize the stability of a widely studied interface consisting of perylene-tetracarboxylic dianhydride (PTCDA) molecules on Au(111). This network of methods lets us firmly establish the adsorption energy of PTCDA/Au(111) via TPD (1.74 ± 0.10 eV) and single-molecule AFM (2.00 ± 0.25 eV) experiments which agree within error bars, exemplifying how implicit replicability in a research design can benefit the investigation of complex materials properties.
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Affiliation(s)
- Victor G Ruiz
- Helmholtz-Zentrum Berlin für Materialien und Energie, Hahn-Meitner-Platz 1, 14109, Berlin, Germany.
| | - Christian Wagner
- Peter Grünberg Institut, Forschungszentrum Jülich, 52425, Jülich, Germany
- Jülich Aachen Research Alliance (JARA)-Fundamentals of Future Information Technology, 52425, Jülich, Germany
| | - Friedrich Maaß
- Ruprecht-Karls-Universität Heidelberg, Physikalisch-Chemisches Institut, Im Neuenheimer Feld 253, 69120, Heidelberg, Germany
| | - Hadi H Arefi
- Peter Grünberg Institut, Forschungszentrum Jülich, 52425, Jülich, Germany
- Jülich Aachen Research Alliance (JARA)-Fundamentals of Future Information Technology, 52425, Jülich, Germany
| | - Stephan Stremlau
- Ruprecht-Karls-Universität Heidelberg, Physikalisch-Chemisches Institut, Im Neuenheimer Feld 253, 69120, Heidelberg, Germany
| | - Petra Tegeder
- Ruprecht-Karls-Universität Heidelberg, Physikalisch-Chemisches Institut, Im Neuenheimer Feld 253, 69120, Heidelberg, Germany
| | - F Stefan Tautz
- Peter Grünberg Institut, Forschungszentrum Jülich, 52425, Jülich, Germany
- Jülich Aachen Research Alliance (JARA)-Fundamentals of Future Information Technology, 52425, Jülich, Germany
- Experimentalphysik IV A, RWTH Aachen University, Otto-Blumenthal-Straße, 52074, Aachen, Germany
| | - Alexandre Tkatchenko
- Department of Physics and Materials Science, University of Luxembourg, L-1511, Luxembourg City, Luxembourg.
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29
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Yasumura S, Saita K, Miyakage T, Nagai K, Kon K, Toyao T, Maeno Z, Taketsugu T, Shimizu KI. Designing main-group catalysts for low-temperature methane combustion by ozone. Nat Commun 2023; 14:3926. [PMID: 37400448 DOI: 10.1038/s41467-023-39541-y] [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: 08/24/2022] [Accepted: 06/16/2023] [Indexed: 07/05/2023] Open
Abstract
The catalytic combustion of methane at a low temperature is becoming increasingly key to controlling unburned CH4 emissions from natural gas vehicles and power plants, although the low activity of benchmark platinum-group-metal catalysts hinders its broad application. Based on automated reaction route mapping, we explore main-group elements catalysts containing Si and Al for low-temperature CH4 combustion with ozone. Computational screening of the active site predicts that strong Brønsted acid sites are promising for methane combustion. We experimentally demonstrate that catalysts containing strong Bronsted acid sites exhibit improved CH4 conversion at 250 °C, correlating with the theoretical predictions. The main-group catalyst (proton-type beta zeolite) delivered a reaction rate that is 442 times higher than that of a benchmark catalyst (5 wt% Pd-loaded Al2O3) at 190 °C and exhibits higher tolerance to steam and SO2. Our strategy demonstrates the rational design of earth-abundant catalysts based on automated reaction route mapping.
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Affiliation(s)
- Shunsaku Yasumura
- Institute for Catalysis, Hokkaido University, N-21 W-10, Sapporo, Hokkaido, 001-0021, Japan
| | - Kenichiro Saita
- Department of Chemistry, Faculty of Science, Hokkaido University, Sapporo, Hokkaido, 060-0810, Japan
| | - Takumi Miyakage
- Institute for Catalysis, Hokkaido University, N-21 W-10, Sapporo, Hokkaido, 001-0021, Japan
| | - Ken Nagai
- Institute for Catalysis, Hokkaido University, N-21 W-10, Sapporo, Hokkaido, 001-0021, Japan
| | - Kenichi Kon
- Institute for Catalysis, Hokkaido University, N-21 W-10, Sapporo, Hokkaido, 001-0021, Japan
| | - Takashi Toyao
- Institute for Catalysis, Hokkaido University, N-21 W-10, Sapporo, Hokkaido, 001-0021, Japan
| | - Zen Maeno
- School of Advanced Engineering, Kogakuin University, Tokyo, 192-0015, Japan
| | - Tetsuya Taketsugu
- Department of Chemistry, Faculty of Science, Hokkaido University, Sapporo, Hokkaido, 060-0810, Japan
- Institute for Chemical Reaction Design and Discovery (WPI-ICReDD), Hokkaido University, Sapporo, Hokkaido, 001-0021, Japan
| | - Ken-Ichi Shimizu
- Institute for Catalysis, Hokkaido University, N-21 W-10, Sapporo, Hokkaido, 001-0021, Japan.
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30
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Svensson R, Grönbeck H. Site Communication in Direct Formation of H 2O 2 over Single-Atom Pd@Au Nanoparticles. J Am Chem Soc 2023; 145:11579-11588. [PMID: 37192331 DOI: 10.1021/jacs.3c00656] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/18/2023]
Abstract
Single atom alloy catalysts offer possibilities to obtain turnover frequencies and selectivities unattainable by their monometallic counterparts. One example is direct formation of H2O2 from O2 and H2 over Pd embedded in Au hosts. Here, a first-principles-based kinetic Monte Carlo approach is developed to investigate the catalytic performance of Pd embedded in Au nanoparticles in an aqueous solution. The simulations reveal an efficient site separation where Pd monomers act as active centers for H2 dissociation, whereas H2O2 is formed over undercoordinated Au sites. After dissociation, atomic H may undergo an exothermic redox reaction, forming a hydronium ion in the solution and a negative charge on the surface. H2O2 is preferably formed from reactions between dissolved H+ and oxygen species on the Au surface. The simulations show that tuning the nanoparticle composition and reaction conditions can enhance the selectivity toward H2O2. The outlined approach is general and applicable for a range of different hydrogenation reactions over single atom alloy nanoparticles.
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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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31
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Yasumura S, Kato T, Toyao T, Maeno Z, Shimizu KI. An automated reaction route mapping for the reaction of NO and active species on Ag 4 clusters in zeolites. Phys Chem Chem Phys 2023; 25:8524-8531. [PMID: 36883572 DOI: 10.1039/d2cp04761f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/09/2023]
Abstract
A computational investigation of the catalytic reaction on multinuclear sites is very challenging. Here, using an automated reaction route mapping method, the single-component artificial force induced reaction (SC-AFIR) algorithm, the catalytic reaction of NO and OH/OOH species over the Ag42+ cluster in a zeolite is investigated. The results of the reaction route mapping for H2 + O2 reveal that OH and OOH species are formed over the Ag42+ cluster via an activation barrier lower than that of OH formation from H2O dissociation. Then, reaction route mapping is performed to examine the reactivity of the OH and OOH species with NO molecules over the Ag42+ cluster, resulting in the facile reaction path of HONO formation. With the aid of the automated reaction route mapping, the promotion effect of H2 addition on the SCR reaction was computationally proposed (boosting the formation of OH and OOH species). In addition, the present study emphasizes that automated reaction route mapping is a powerful tool to elucidate the complicated reaction pathway on multi-nuclear clusters.
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Affiliation(s)
- Shunsaku Yasumura
- Institute for Catalysis, Hokkaido University, N-21, W-10, Sapporo, 001-0021, Japan.
| | - Taisetsu Kato
- Institute for Catalysis, Hokkaido University, N-21, W-10, Sapporo, 001-0021, Japan.
| | - Takashi Toyao
- Institute for Catalysis, Hokkaido University, N-21, W-10, Sapporo, 001-0021, Japan.
| | - Zen Maeno
- School of Advanced Engineering, Kogakuin University, Tokyo, 192-0015, Japan
| | - Ken-Ichi Shimizu
- Institute for Catalysis, Hokkaido University, N-21, W-10, Sapporo, 001-0021, Japan.
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32
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Foppa L, Rüther F, Geske M, Koch G, Girgsdies F, Kube P, Carey SJ, Hävecker M, Timpe O, Tarasov AV, Scheffler M, Rosowski F, Schlögl R, Trunschke A. Data-Centric Heterogeneous Catalysis: Identifying Rules and Materials Genes of Alkane Selective Oxidation. J Am Chem Soc 2023; 145:3427-3442. [PMID: 36745555 PMCID: PMC9936587 DOI: 10.1021/jacs.2c11117] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Artificial intelligence (AI) can accelerate catalyst design by identifying key physicochemical descriptive parameters correlated with the underlying processes triggering, favoring, or hindering the performance. In analogy to genes in biology, these parameters might be called "materials genes" of heterogeneous catalysis. However, widely used AI methods require big data, and only the smallest part of the available data meets the quality requirement for data-efficient AI. Here, we use rigorous experimental procedures, designed to consistently take into account the kinetics of the catalyst active states formation, to measure 55 physicochemical parameters as well as the reactivity of 12 catalysts toward ethane, propane, and n-butane oxidation reactions. These materials are based on vanadium or manganese redox-active elements and present diverse phase compositions, crystallinities, and catalytic behaviors. By applying the sure-independence-screening-and-sparsifying-operator symbolic-regression approach to the consistent data set, we identify nonlinear property-function relationships depending on several key parameters and reflecting the intricate interplay of processes that govern the formation of olefins and oxygenates: local transport, site isolation, surface redox activity, adsorption, and the material dynamical restructuring under reaction conditions. These processes are captured by parameters derived from N2 adsorption, X-ray photoelectron spectroscopy (XPS), and near-ambient-pressure in situ XPS. The data-centric approach indicates the most relevant characterization techniques to be used for catalyst design and provides "rules" on how the catalyst properties may be tuned in order to achieve the desired performance.
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Affiliation(s)
- Lucas Foppa
- The
NOMAD Laboratory at the Fritz-Haber-Institut of the Max-Planck-Gesellschaft
and IRIS-Adlershof of the Humboldt-Universität zu Berlin, Faradayweg 4-6, D-14195 Berlin, Germany,
| | - Frederik Rüther
- BasCat
- UniCat BASF JointLab, Hardenbergstraße 36, D-10623 Berlin, Germany
| | - Michael Geske
- BasCat
- UniCat BASF JointLab, Hardenbergstraße 36, D-10623 Berlin, Germany
| | - Gregor Koch
- Department
of Inorganic Chemistry, Fritz-Haber-Institut
of the Max-Planck-Gesellschaft, Faradayweg 4-6, D-14195 Berlin, Germany
| | - Frank Girgsdies
- Department
of Inorganic Chemistry, Fritz-Haber-Institut
of the Max-Planck-Gesellschaft, Faradayweg 4-6, D-14195 Berlin, Germany
| | - Pierre Kube
- Department
of Inorganic Chemistry, Fritz-Haber-Institut
of the Max-Planck-Gesellschaft, Faradayweg 4-6, D-14195 Berlin, Germany
| | - Spencer J. Carey
- Department
of Inorganic Chemistry, Fritz-Haber-Institut
of the Max-Planck-Gesellschaft, Faradayweg 4-6, D-14195 Berlin, Germany
| | - Michael Hävecker
- Department
of Inorganic Chemistry, Fritz-Haber-Institut
of the Max-Planck-Gesellschaft, Faradayweg 4-6, D-14195 Berlin, Germany,Max
Planck Institute for Chemical Energy Conversion, 45470 Mülheim, Germany
| | - Olaf Timpe
- Department
of Inorganic Chemistry, Fritz-Haber-Institut
of the Max-Planck-Gesellschaft, Faradayweg 4-6, D-14195 Berlin, Germany
| | - Andrey V. Tarasov
- Department
of Inorganic Chemistry, Fritz-Haber-Institut
of the Max-Planck-Gesellschaft, Faradayweg 4-6, D-14195 Berlin, Germany
| | - Matthias Scheffler
- The
NOMAD Laboratory at the Fritz-Haber-Institut of the Max-Planck-Gesellschaft
and IRIS-Adlershof of the Humboldt-Universität zu Berlin, Faradayweg 4-6, D-14195 Berlin, Germany
| | - Frank Rosowski
- BasCat
- UniCat BASF JointLab, Hardenbergstraße 36, D-10623 Berlin, Germany,BASF
SE, Catalysis Research, Carl-Bosch-Straße 38, D-67065 Ludwigshafen, Germany
| | - Robert Schlögl
- Department
of Inorganic Chemistry, Fritz-Haber-Institut
of the Max-Planck-Gesellschaft, Faradayweg 4-6, D-14195 Berlin, Germany
| | - Annette Trunschke
- Department
of Inorganic Chemistry, Fritz-Haber-Institut
of the Max-Planck-Gesellschaft, Faradayweg 4-6, D-14195 Berlin, Germany,
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33
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Ashraf M, Ahmad MS, Inomata Y, Ullah N, Tahir MN, Kida T. Transition metal nanoparticles as nanocatalysts for Suzuki, Heck and Sonogashira cross-coupling reactions. Coord Chem Rev 2023. [DOI: 10.1016/j.ccr.2022.214928] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
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34
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Exploring catalytic reaction networks with machine learning. Nat Catal 2023. [DOI: 10.1038/s41929-022-00896-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
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35
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Xu G, Cai C, Zhao W, Liu Y, Wang T. Rational design of catalysts with earth‐abundant elements. WIRES COMPUTATIONAL MOLECULAR SCIENCE 2022. [DOI: 10.1002/wcms.1654] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Affiliation(s)
- Gaomou Xu
- Center of Artificial Photosynthesis for Solar Fuels and Department of Chemistry, School of Science Westlake University Hangzhou Zhejiang Province China
- Institute of Natural Sciences, Westlake Institute for Advanced Study Hangzhou Zhejiang Province China
| | - Cheng Cai
- Center of Artificial Photosynthesis for Solar Fuels and Department of Chemistry, School of Science Westlake University Hangzhou Zhejiang Province China
- Institute of Natural Sciences, Westlake Institute for Advanced Study Hangzhou Zhejiang Province China
| | - Wanghui Zhao
- Center of Artificial Photosynthesis for Solar Fuels and Department of Chemistry, School of Science Westlake University Hangzhou Zhejiang Province China
- Institute of Natural Sciences, Westlake Institute for Advanced Study Hangzhou Zhejiang Province China
| | - Yonghua Liu
- Center of Artificial Photosynthesis for Solar Fuels and Department of Chemistry, School of Science Westlake University Hangzhou Zhejiang Province China
- Institute of Natural Sciences, Westlake Institute for Advanced Study Hangzhou Zhejiang Province China
| | - Tao Wang
- Center of Artificial Photosynthesis for Solar Fuels and Department of Chemistry, School of Science Westlake University Hangzhou Zhejiang Province China
- Institute of Natural Sciences, Westlake Institute for Advanced Study Hangzhou Zhejiang Province China
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36
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Gao H, Belova V, La Porta F, Cingolani JS, Andersen M, Saedi M, Konovalov OV, Jankowski M, Heenen HH, Groot IMN, Renaud G, Reuter K. Graphene at Liquid Copper Catalysts: Atomic-Scale Agreement of Experimental and First-Principles Adsorption Height. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2022; 9:e2204684. [PMID: 36351774 PMCID: PMC9798965 DOI: 10.1002/advs.202204684] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Revised: 10/07/2022] [Indexed: 06/16/2023]
Abstract
Liquid metal catalysts have recently attracted attention for synthesizing high-quality 2D materials facilitated via the catalysts' perfectly smooth surface. However, the microscopic catalytic processes occurring at the surface are still largely unclear because liquid metals escape the accessibility of traditional experimental and computational surface science approaches. Hence, numerous controversies are found regarding different applications, with graphene (Gr) growth on liquid copper (Cu) as a prominent prototype. In this work, novel in situ and in silico techniques are employed to achieve an atomic-level characterization of the graphene adsorption height above liquid Cu, reaching quantitative agreement within 0.1 Å between experiment and theory. The results are obtained via in situ synchrotron X-ray reflectivity (XRR) measurements over wide-range q-vectors and large-scale molecular dynamics simulations based on efficient machine-learning (ML) potentials trained to first-principles density functional theory (DFT) data. The computational insight is demonstrated to be robust against inherent DFT errors and reveals the nature of graphene binding to be highly comparable at liquid Cu and solid Cu(111). Transporting the predictive first-principles quality via ML potentials to the scales required for liquid metal catalysis thus provides a powerful approach to reach microscopic understanding, analogous to the established computational approaches for catalysis at solid surfaces.
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Affiliation(s)
- Hao Gao
- Fritz‐Haber‐Institut der Max‐Planck‐GesellschaftFaradayweg 4–614195BerlinGermany
| | - Valentina Belova
- The European Synchrotron‐ ESRF71 Avenue des Martyrs, CS 40220Grenoble Cedex 938043France
| | - Francesco La Porta
- The European Synchrotron‐ ESRF71 Avenue des Martyrs, CS 40220Grenoble Cedex 938043France
| | - Juan Santiago Cingolani
- Chair for Theoretical Chemistry and Catalysis Research CenterTechnische Universität MünchenLichtenbergstraße 485747GarchingGermany
| | - Mie Andersen
- Aarhus Institute of Advanced Studies & Center for Interstellar CatalysisDepartment of Physics and AstronomyAarhus UniversityAarhus CDK‐8000Denmark
| | - Mehdi Saedi
- Leiden Institute of ChemistryLeiden UniversityP.O. Box 9502RA Leiden2300The Netherlands
| | - Oleg V. Konovalov
- The European Synchrotron‐ ESRF71 Avenue des Martyrs, CS 40220Grenoble Cedex 938043France
| | - Maciej Jankowski
- The European Synchrotron‐ ESRF71 Avenue des Martyrs, CS 40220Grenoble Cedex 938043France
| | - Hendrik H. Heenen
- Fritz‐Haber‐Institut der Max‐Planck‐GesellschaftFaradayweg 4–614195BerlinGermany
| | - Irene M. N. Groot
- Leiden Institute of ChemistryLeiden UniversityP.O. Box 9502RA Leiden2300The Netherlands
| | - Gilles Renaud
- Université Grenoble AlpesCEA, IRIG/MEM/NRSGrenoble38000France
| | - Karsten Reuter
- Fritz‐Haber‐Institut der Max‐Planck‐GesellschaftFaradayweg 4–614195BerlinGermany
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37
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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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38
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Chen W, Qian G, Wan Y, Chen D, Zhou X, Yuan W, Duan X. Mesokinetics as a Tool Bridging the Microscopic-to-Macroscopic Transition to Rationalize Catalyst Design. Acc Chem Res 2022; 55:3230-3241. [PMID: 36321554 DOI: 10.1021/acs.accounts.2c00483] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Heterogeneous catalysis is the workhorse of the chemical industry, and a heterogeneous catalyst possesses numerous active sites working together to drive the conversion of reactants to desirable products. Over the decades, much focus has been placed on identifying the factors affecting the active sites to gain deep insights into the structure-performance relationship, which in turn guides the design and preparation of more active, selective, and stable catalysts. However, the molecular-level interplay between active sites and catalytic function still remains qualitative or semiquantitative, ascribed to the difficulty and uncertainty in elucidating the nature of active sites for its controllable manipulation. Hence, bridging the microscopic properties of active sites and the macroscopic catalytic performance, that is, microscopic-to-macroscopic transition, to afford a quantitative description is intriguing yet challenging, and progress toward this promises to revolutionize catalyst design and preparation.In this Account, we propose mesokinetics modeling, for the first time enabling a quantitative description of active site characteristics and the related mechanistic information, as a versatile tool to guide rational catalyst design. Exemplified by a pseudo-zero-order reaction, the kinetics derivation from the Pt particle size-sensitive catalytic activity and size-insensitive activation energy suggests only one type of surface site as the dominant active site, in which the Pt(111) with almost unchanged turnover frequency (TOF111) is further identified as the dominating active site. Such a method has been extended to identify and quantify the number (Ni) of active sites for various thermo-, electro-, and photocatalysts in chemical synthesis, hydrogen generation, environment application, etc. Then, the kinetics derivation from the kinetic compensation effects suggests a thermodynamic balance between the activation entropy and enthalpy, which exhibit linear dependences on Pt charge. Accordingly, the Pt charge can serve as a catalytic descriptor for its quantitative determination of TOFi. This strategy has been further applied to Pt-catalyzed CO oxidation with nonzero-order reaction characteristic by taking the site coverages of surface species into consideration.Hence, substituting the above statistical correlations of Ni and TOFi into the rate equation R = ∑Ni × TOFi offers the mesokinetics model, which can precisely predict catalytic function and screen catalysts. Finally, based on the disentanglement of the factors underlying Pt electronic structures, a de novo strategy, from the interfacial charge distribution to reaction mechanism, kinetics, and thermodynamics parameters of the rate-determining step, and ultimately catalytic performance, is developed to map the unified mechanistic and kinetics picture of reaction. Overall, the mesokinetics not only demonstrates much potential to elucidate the quantitative interplay between active sites and catalytic activity but also provides a new research direction in kinetics analysis to rationalize catalyst design.
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Affiliation(s)
- Wenyao Chen
- State Key Laboratory of Chemical Engineering, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China
| | - Gang Qian
- State Key Laboratory of Chemical Engineering, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China
| | - Ying Wan
- State Key Laboratory of Chemical Engineering, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China
| | - De Chen
- Department of Chemical Engineering, Norwegian University of Science and Technology, Trondheim 7491, Norway
| | - Xinggui Zhou
- State Key Laboratory of Chemical Engineering, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China
| | - Weikang Yuan
- State Key Laboratory of Chemical Engineering, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China
| | - Xuezhi Duan
- State Key Laboratory of Chemical Engineering, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China
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Huang J, Climent V, Groß A, Feliu JM. Understanding surface charge effects in electrocatalysis. Part 2: Hydrogen peroxide reactions at platinum. CHINESE JOURNAL OF CATALYSIS 2022. [DOI: 10.1016/s1872-2067(22)64138-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/31/2022]
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40
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Agarwal S, Joshi K. Looking beyond Adsorption Energies to Understand Interactions at Surface using Machine Learning. ChemistrySelect 2022. [DOI: 10.1002/slct.202202414] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Affiliation(s)
- Sheena Agarwal
- Physical and Materials Chemistry Division CSIR-National Chemical Laboratory Dr. Homi Bhabha Road Pune 411008 India
- Academy of Scientific and Innovative Research (AcSIR) Ghaziabad 201002 India
| | - Kavita Joshi
- Physical and Materials Chemistry Division CSIR-National Chemical Laboratory Dr. Homi Bhabha Road Pune 411008 India
- Academy of Scientific and Innovative Research (AcSIR) Ghaziabad 201002 India
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Hao H, Ruiz Pestana L, Qian J, Liu M, Xu Q, Head‐Gordon T. Chemical transformations and transport phenomena at interfaces. WIRES COMPUTATIONAL MOLECULAR SCIENCE 2022. [DOI: 10.1002/wcms.1639] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Affiliation(s)
- Hongxia Hao
- Kenneth S. Pitzer Theory Center and Department of Chemistry University of California Berkeley California USA
- Chemical Sciences Division Lawrence Berkeley National Laboratory Berkeley California USA
| | - Luis Ruiz Pestana
- Department of Civil and Architectural Engineering University of Miami Coral Gables Florida USA
| | - Jin Qian
- Chemical Sciences Division Lawrence Berkeley National Laboratory Berkeley California USA
| | - Meili Liu
- Department of Civil and Architectural Engineering University of Miami Coral Gables Florida USA
| | - Qiang Xu
- Chemical Sciences Division Lawrence Berkeley National Laboratory Berkeley California USA
| | - Teresa Head‐Gordon
- Kenneth S. Pitzer Theory Center and Department of Chemistry University of California Berkeley California USA
- Chemical Sciences Division Lawrence Berkeley National Laboratory Berkeley California USA
- Department of Bioengineering and Chemical and Biomolecular Engineering University of California Berkeley California USA
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42
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Ismail I, Chantreau Majerus R, Habershon S. Graph-Driven Reaction Discovery: Progress, Challenges, and Future Opportunities. J Phys Chem A 2022; 126:7051-7069. [PMID: 36190262 PMCID: PMC9574932 DOI: 10.1021/acs.jpca.2c06408] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Revised: 09/22/2022] [Indexed: 11/29/2022]
Abstract
Graph-based descriptors, such as bond-order matrices and adjacency matrices, offer a simple and compact way of categorizing molecular structures; furthermore, such descriptors can be readily used to catalog chemical reactions (i.e., bond-making and -breaking). As such, a number of graph-based methodologies have been developed with the goal of automating the process of generating chemical reaction network models describing the possible mechanistic chemistry in a given set of reactant species. Here, we outline the evolution of these graph-based reaction discovery schemes, with particular emphasis on more recent methods incorporating graph-based methods with semiempirical and ab initio electronic structure calculations, minimum-energy path refinements, and transition state searches. Using representative examples from homogeneous catalysis and interstellar chemistry, we highlight how these schemes increasingly act as "virtual reaction vessels" for interrogating mechanistic questions. Finally, we highlight where challenges remain, including issues of chemical accuracy and calculation speeds, as well as the inherent challenge of dealing with the vast size of accessible chemical reaction space.
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Affiliation(s)
- Idil Ismail
- Department of Chemistry, University
of Warwick, CoventryCV4 7AL, United Kingdom
| | | | - Scott Habershon
- Department of Chemistry, University
of Warwick, CoventryCV4 7AL, United Kingdom
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43
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Chemical looping oxidative propane dehydrogenation controlled by oxygen bulk diffusion over FeVO4 oxygen carrier pellets. Chin J Chem Eng 2022. [DOI: 10.1016/j.cjche.2022.10.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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Fan J, Li W, Li S, Yang J. High-Throughput Screening of Bicationic Redox Materials for Chemical Looping Ammonia Synthesis. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2022; 9:e2202811. [PMID: 35871554 PMCID: PMC9507380 DOI: 10.1002/advs.202202811] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Revised: 06/16/2022] [Indexed: 06/15/2023]
Abstract
Ammonia recently has gained increasing attention as a carrier for the efficient and safe usage of hydrogen to further advance the hydrogen economy. However, there is a pressing need to develop new ammonia synthesis techniques to overcome the problem of intense energy consumption associated with the widely used Haber-Bosch process. Chemical looping ammonia synthesis (CLAS) is a promising approach to tackle this problem, but the ideal redox materials to drive these chemical looping processes are yet to be discovered. Here, by mining the well-established MP database, the reaction free energies for CLAS involving 1699 bicationic inorganic redox pairs are screened to comprehensively investigate their potentials as efficient redox materials in four different CLAS schemes. A state-of-the-art machine learning strategy is further deployed to significantly widen the chemical space for discovering the promising redox materials from more than half a million candidates. Most importantly, using the three-step H2 O-CL as an example, a new metric is introduced to determine bicationic redox pairs that are "cooperatively enhanced" compared to their corresponding monocationic counterparts. It is found that bicationic compounds containing a combination of alkali/alkaline-earth metals and transition metal (TM)/post-TM/metalloid elements are compounds that are particularly promising in this respect.
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Affiliation(s)
- Jiaxin Fan
- Materials and Manufacturing Futures InstituteSchool of Material Science and EngineeringUniversity of New South WalesSydneyNew South Wales2052Australia
| | - Wenxian Li
- Materials and Manufacturing Futures InstituteSchool of Material Science and EngineeringUniversity of New South WalesSydneyNew South Wales2052Australia
| | - Sean Li
- Materials and Manufacturing Futures InstituteSchool of Material Science and EngineeringUniversity of New South WalesSydneyNew South Wales2052Australia
| | - Jack Yang
- Materials and Manufacturing Futures InstituteSchool of Material Science and EngineeringUniversity of New South WalesSydneyNew South Wales2052Australia
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De Wispelaere K, Plessow PN, Studt F. Toward Computing Accurate Free Energies in Heterogeneous Catalysis: a Case Study for Adsorbed Isobutene in H-ZSM-5. ACS PHYSICAL CHEMISTRY AU 2022; 2:399-406. [PMID: 36855690 PMCID: PMC9955322 DOI: 10.1021/acsphyschemau.2c00020] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Herein, we propose a novel computational protocol that enables calculating free energies with improved accuracy by combining the best available techniques for enthalpy and entropy calculation. While the entropy is described by enhanced sampling molecular dynamics techniques, the energy is calculated using ab initio methods. We apply the method to assess the stability of isobutene adsorption intermediates in the zeolite H-SSZ-13, a prototypical problem that is computationally extremely challenging in terms of calculating enthalpy and entropy. We find that at typical operating conditions for zeolite catalysis (400 °C), the physisorbed π-complex, and not the tertiary carbenium ion as often reported, is the most stable intermediate. This method paves the way for sampling-based techniques to calculate the accurate free energies in a broad range of chemistry-related disciplines, thus presenting a big step forward toward predictive modeling.
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Affiliation(s)
- Kristof De Wispelaere
- Center
for Molecular Modeling, Ghent University, Technologiepark 46, B-9052 Ghent, Belgium,
| | - Philipp N. Plessow
- Institute
of Catalysis Research and Technology, Karlsruhe
Institute of Technology, Hermann-von-Helmholtz-Platz 1, D-76344 Eggenstein-Leopoldshafen, Germany,
| | - Felix Studt
- Institute
of Catalysis Research and Technology, Karlsruhe
Institute of Technology, Hermann-von-Helmholtz-Platz 1, D-76344 Eggenstein-Leopoldshafen, Germany,Institute
for Chemical Technology and Polymer Chemistry, Karlsruhe Institute of Technology, D-76131 Karlsruhe, Germany,
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Anderson SD, Kreitz B, Turek T, Wehinger GD. Assessment of Concentration and Temperature Distribution in a Berty Reactor for an Exothermic Reaction. Ind Eng Chem Res 2022. [DOI: 10.1021/acs.iecr.2c01459] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Scott D. Anderson
- Institute of Chemical and Electrochemical Process Engineering, Clausthal University of Technology, Clausthal-Zellerfeld, 38678, Germany
| | - Bjarne Kreitz
- Institute of Chemical and Electrochemical Process Engineering, Clausthal University of Technology, Clausthal-Zellerfeld, 38678, Germany
- School of Engineering, Brown University, Providence, Rhode Island 02912, United States
| | - Thomas Turek
- Institute of Chemical and Electrochemical Process Engineering, Clausthal University of Technology, Clausthal-Zellerfeld, 38678, Germany
| | - Gregor D. Wehinger
- Institute of Chemical and Electrochemical Process Engineering, Clausthal University of Technology, Clausthal-Zellerfeld, 38678, Germany
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Kreitz B, Wehinger GD, Goldsmith CF, Turek T. Microkinetic modeling of the transient CO2 methanation with DFT‐based uncertainties in a Berty reactor. ChemCatChem 2022. [DOI: 10.1002/cctc.202200570] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Bjarne Kreitz
- Brown University School of Engineering 184 Hope Street 02906 Providence UNITED STATES
| | - Gregor D. Wehinger
- Technische Universitat Clausthal Institute for Chemical and Electrochemical Engineering GERMANY
| | | | - Thomas Turek
- TU Clausthal Institut für Chemische und Elektrochemische Verfahrenstechnik Leibnizstr. 17 38678 Clausthal-Zellerfeld GERMANY
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Meng Y, Liu X, Ma Y, Gao X, Wen X. Investigation of water gas shift reactivity on Fe5C2 (111): A DFT study. MOLECULAR CATALYSIS 2022. [DOI: 10.1016/j.mcat.2022.112538] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/16/2022]
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50
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Quinlivan Domínguez JE, Neyman KM, Bruix A. Stability of oxidized states of free-standing and ceria-supported PtO x particles. J Chem Phys 2022; 157:094709. [DOI: 10.1063/5.0099927] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
Nanostructured materials based on CeO2 and Pt play a fundamental role in catalyst design. However, their characterization is often challenging due to their structural complexity and the tendency of the materials to change under reaction conditions. In this work, we combine calculations based on the density functional theory, a machine-learning assisted global optimization method (GOFEE), and ab initio thermodynamics to characterize stable oxidation states of ceria-supported PtyOx particles in different environments. The collection of global minima structures for different stoichiometries resulting from the global optimisation effort is used to assess the effect of temperature, oxygen pressure, and support interactions on the phase diagrams, oxidation states, and geometries of the PtyOx particles. We thus identify favoured structural motifs and O:Pt ratios, revealing that oxidized states of free-standing and ceria-supported platinum particles are more stable than reduced ones under a wide range of conditions. These results indicate that studies rationalizing activity of ceria-supported Pt clusters must consider oxidized states, and that previous understanding of such materials obtained only with fully reduced Pt clusters may be incomplete.
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Affiliation(s)
| | - Konstantin M. Neyman
- Departament de Quimica Fisica, Universitat de Barcelona Departament de Química-Física, Spain
| | - Albert Bruix
- Universitat de Barcelona Departament de Química-Física, Spain
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