1
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Robertson NK, Onel L, Blitz MA, Shannon R, Stone D, Seakins PW, Robertson SH, Kühn C, Pazdera TM, Olzmann M. Temperature-Dependent, Site-Specific Rate Coefficients for the Reaction of OH (OD) with Methyl Formate Isotopologues via Experimental and Theoretical Studies. J Phys Chem A 2024; 128:5028-5040. [PMID: 38885649 PMCID: PMC11215782 DOI: 10.1021/acs.jpca.4c02524] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2024] [Revised: 05/30/2024] [Accepted: 05/30/2024] [Indexed: 06/20/2024]
Abstract
Methyl esters are an important component of combustion and atmospheric systems. Reaction with the OH radical plays an important role in the removal of the simplest methyl ester, methyl formate (MF, CH3OCHO). In this paper, the overall rate coefficients for the reactions of OH and OD with MF isotopologues, studied under pseudo-first-order conditions, are reported using two different laser flash photolysis systems with the decay of OH monitored by laser-induced fluorescence. The room-temperature rate coefficient for OH + MF, (1.95 ± 0.34) × 10-13 cm3 molecule-1 s-1, is in good agreement with the literature. The rate coefficient exhibits curved Arrhenius behavior, and our results bridge the gap between previous low-temperature and shock tube studies. In combination with the literature, the rate coefficient for the reaction of OH with MF between 230 and 1400 K can be parametrized as kOH+MF = (3.2 × 10-13) × (T/300 K)2.3 × exp(-141.4 K/T) cm3 molecule-1 s-1 with an overall estimated uncertainty of ∼30%. The reactions of OD with MF isotopologues show a small enhancement (inverse secondary isotope effect) compared to the respective OH reactions. The reaction of OH/OD with MF shows a normal primary isotope effect, a decrease in the rate coefficient when MF is partially or fully deuterated. Experimental studies have been supported by ab initio calculations at the CCSD(T)-F12/aug-cc-pVTZ//M06-2X/6-31+G** level of theory. The calculated, zero-point-corrected, barrier heights for abstraction at the methyl and formate sites are 1.3 and 6.0 kJ mol-1, respectively, and the ab initio predictions of kinetic isotope effects are in agreement with experiment. Fitting the experimental isotopologue data refines these barriers to 0.9 ± 0.6 and 4.1 ± 0.9 kJ mol-1. The branching ratio is approximately 50:50 at 300 K. Between 300 and 500 K, abstraction via the higher-energy, higher-entropy formate transition state becomes more favored (60:40). However, experiment and calculations suggest that as the temperature increases further, with higher energy, less constrained conformers of the methyl transition state become more significant. The implications of the experimental and theoretical results for the mechanisms of MF atmospheric oxidation and low-temperature combustion are discussed.
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Affiliation(s)
| | - Lavinia Onel
- School
of Chemistry, University of Leeds, Leeds LS2 9JT, U.K.
| | - Mark A. Blitz
- School
of Chemistry, University of Leeds, Leeds LS2 9JT, U.K.
- National
Centre for Atmospheric Science, University
of Leeds, Leeds LS2 9JT, U.K.
| | - Robin Shannon
- School
of Chemistry, University of Leeds, Leeds LS2 9JT, U.K.
| | - Daniel Stone
- School
of Chemistry, University of Leeds, Leeds LS2 9JT, U.K.
| | - Paul W. Seakins
- School
of Chemistry, University of Leeds, Leeds LS2 9JT, U.K.
| | | | - Christian Kühn
- Institut
für Physikalische Chemie, Karlsruher
Institut für Technologie (KIT), 76131 Karlsruhe, Germany
| | - Tobias M. Pazdera
- Institut
für Physikalische Chemie, Karlsruher
Institut für Technologie (KIT), 76131 Karlsruhe, Germany
| | - Matthias Olzmann
- Institut
für Physikalische Chemie, Karlsruher
Institut für Technologie (KIT), 76131 Karlsruhe, Germany
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2
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Gilkes J, Storr MT, Maurer RJ, Habershon S. Predicting Long-Time-Scale Kinetics under Variable Experimental Conditions with Kinetica.jl. J Chem Theory Comput 2024; 20:5196-5214. [PMID: 38829777 PMCID: PMC11209948 DOI: 10.1021/acs.jctc.4c00333] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2024] [Revised: 05/13/2024] [Accepted: 05/13/2024] [Indexed: 06/05/2024]
Abstract
Predicting the degradation processes of molecules over long time scales is a key aspect of industrial materials design. However, it is made computationally challenging by the need to construct large networks of chemical reactions that are relevant to the experimental conditions that kinetic models must mirror, with every reaction requiring accurate kinetic data. Here, we showcase Kinetica.jl, a new software package for constructing large-scale chemical reaction networks in a fully automated fashion by exploring chemical reaction space with a kinetics-driven algorithm; coupled to efficient machine-learning models of activation energies for sampled elementary reactions, we show how this approach readily enables generation and kinetic characterization of networks containing ∼103 chemical species and ≃104-105 reactions. Symbolic-numeric modeling of the generated reaction networks is used to allow for flexible, efficient computation of kinetic profiles under experimentally realizable conditions such as continuously variable temperature regimes, enabling direct connection between bottom-up reaction networks and experimental observations. Highly efficient propagation of long-time-scale kinetic profiles is required for automated reaction network refinement and is enabled here by a new discrete kinetic approximation. The resulting Kinetica.jl simulation package therefore enables automated generation, characterization, and long-time-scale modeling of complex chemical reaction systems. We demonstrate this for hydrocarbon pyrolysis simulated over time scales of seconds, using transient temperature profiles representing those of tubular flow reactor experiments.
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Affiliation(s)
- Joe Gilkes
- Department
of Chemistry, University of Warwick, Gibbet Hill Road, CV4 7AL Coventry, U.K.
- EPSRC
HetSys Centre for Doctoral Training, University
of Warwick, Gibbet Hill
Rd, CV4 7AL Coventry, U.K.
| | | | - Reinhard J. Maurer
- Department
of Chemistry, University of Warwick, Gibbet Hill Road, CV4 7AL Coventry, U.K.
- Department
of Physics, University of Warwick, Gibbet Hill Road, CV4 7AL Coventry, U.K.
| | - Scott Habershon
- Department
of Chemistry, University of Warwick, Gibbet Hill Road, CV4 7AL Coventry, U.K.
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3
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Csizi KS, Steiner M, Reiher M. Nanoscale chemical reaction exploration with a quantum magnifying glass. Nat Commun 2024; 15:5320. [PMID: 38909029 PMCID: PMC11193806 DOI: 10.1038/s41467-024-49594-2] [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: 09/29/2023] [Accepted: 06/04/2024] [Indexed: 06/24/2024] Open
Abstract
Nanoscopic systems exhibit diverse molecular substructures by which they facilitate specific functions. Theoretical models of them, which aim at describing, understanding, and predicting these capabilities, are difficult to build. Viable quantum-classical hybrid models come with specific challenges regarding atomistic structure construction and quantum region selection. Moreover, if their dynamics are mapped onto a state-to-state mechanism such as a chemical reaction network, its exhaustive exploration will be impossible due to the combinatorial explosion of the reaction space. Here, we introduce a "quantum magnifying glass" that allows one to interactively manipulate nanoscale structures at the quantum level. The quantum magnifying glass seamlessly combines autonomous model parametrization, ultra-fast quantum mechanical calculations, and automated reaction exploration. It represents an approach to investigate complex reaction sequences in a physically consistent manner with unprecedented effortlessness in real time. We demonstrate these features for reactions in bio-macromolecules and metal-organic frameworks, diverse systems that highlight general applicability.
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Affiliation(s)
- Katja-Sophia Csizi
- ETH Zurich, Department of Chemistry and Applied Biosciences, Vladimir-Prelog-Weg 2, 8093, Zurich, Switzerland
| | - Miguel Steiner
- ETH Zurich, Department of Chemistry and Applied Biosciences, Vladimir-Prelog-Weg 2, 8093, Zurich, Switzerland
- ETH Zurich, NCCR Catalysis, Vladimir-Prelog-Weg 2, 8093, Zurich, Switzerland
| | - Markus Reiher
- ETH Zurich, Department of Chemistry and Applied Biosciences, Vladimir-Prelog-Weg 2, 8093, Zurich, Switzerland.
- ETH Zurich, NCCR Catalysis, Vladimir-Prelog-Weg 2, 8093, Zurich, Switzerland.
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4
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Martí C, Devereux C, Najm HN, Zádor J. Evaluation of Rate Coefficients in the Gas Phase Using Machine-Learned Potentials. J Phys Chem A 2024. [PMID: 38427974 DOI: 10.1021/acs.jpca.3c07872] [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
We assess the capability of machine-learned potentials to compute rate coefficients by training a neural network (NN) model and applying it to describe the chemical landscape on the C5H5 potential energy surface, which is relevant to molecular weight growth in combustion and interstellar media. We coupled the resulting NN with an automated kinetics workflow code, KinBot, to perform all necessary calculations to compute the rate coefficients. The NN is benchmarked exhaustively by evaluating its performance at the various stages of the kinetics calculations: from the electronic energy through the computation of zero point energy, barrier heights, entropic contributions, the portion of the PES explored, and finally the overall rate coefficients as formulated by transition state theory.
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Affiliation(s)
- Carles Martí
- Combustion Research Facility, Sandia National Laboratories, Livermore, California 94551, United States
| | - Christian Devereux
- Combustion Research Facility, Sandia National Laboratories, Livermore, California 94551, United States
| | - Habib N Najm
- Combustion Research Facility, Sandia National Laboratories, Livermore, California 94551, United States
| | - Judit Zádor
- Combustion Research Facility, Sandia National Laboratories, Livermore, California 94551, United States
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5
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Shannon R, Blitz MA, Seakins PW. Solving the OH + Glyoxal Problem: A Complete Theoretical Description of Post-Transition-State Energy Deposition in Activated Systems. J Phys Chem A 2024; 128:1501-1510. [PMID: 38377581 PMCID: PMC10910583 DOI: 10.1021/acs.jpca.3c07823] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Revised: 01/25/2024] [Accepted: 01/31/2024] [Indexed: 02/22/2024]
Abstract
Activated chemistry in coupled reaction systems has broadened our understanding of the chemical kinetics. In the case of intermediates formed in gas phase abstraction reactions (e.g., OH + HC(O)C(O)H (glyoxal) →HC(O)CO + H2O), it is particularly crucial to understand how the reaction energy is partitioned between product species as this determines the propensity for a given product to undergo "prompt" dissociation (e.g., HC(O)CO → HCO + CO) before the excess reaction energy is removed. An example of such an activated system is the OH + glyoxal + O2 coupled reaction system. In this work, we develop a molecular dynamics pipeline, which, combined with a master equation analysis, accurately models previous experimental measurements. This new work resolves previous complexities and discrepancies from earlier master equation modeling for this reaction system. The detailed molecular dynamics approach employed here is a powerful new tool for modeling challenging activated reaction systems.
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Affiliation(s)
- Robin Shannon
- School
of Chemistry, University of Leeds, Leeds LS2 9JT, U.K.
| | - Mark A. Blitz
- School
of Chemistry, University of Leeds, Leeds LS2 9JT, U.K.
- National
Centre for Atmospheric Science, University
of Leeds, Leeds LS2 9JT, U.K.
| | - Paul W. Seakins
- School
of Chemistry, University of Leeds, Leeds LS2 9JT, U.K.
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6
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Rasmussen MH, Seumer J, Jensen JH. Toward De Novo Catalyst Discovery: Fast Identification of New Catalyst Candidates for Alcohol-Mediated Morita-Baylis-Hillman Reactions. Angew Chem Int Ed Engl 2023; 62:e202310580. [PMID: 37830522 DOI: 10.1002/anie.202310580] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Revised: 09/15/2023] [Accepted: 10/13/2023] [Indexed: 10/14/2023]
Abstract
Recently we have demonstrated how a genetic algorithm (GA) starting from random tertiary amines can be used to discover a new and efficient catalyst for the alcohol-mediated Morita-Baylis-Hillman (MBH) reaction. In particular, the discovered catalyst was shown experimentally to be eight times more active than DABCO, commonly used to catalyze the MBH reaction. This represents a breakthrough in using generative models for catalyst optimization. However, the GA procedure, and hence discovery, relied on two important pieces of information; 1) the knowledge that tertiary amines catalyze the reaction and 2) the mechanism and reaction profile for the catalyzed reaction, in particular the transition state structure of the rate-determining step. Thus, truly de novo catalyst discovery must include these steps. Here we present such a method for discovering catalyst candidates for a specific reaction while simultaneously proposing a mechanism for the catalyzed reaction. We show that tertiary amines and phosphines are potential catalysts for the MBH reaction by screening 11 molecular templates representing common functional groups. The method relies on an automated reaction discovery workflow using meta-dynamics calculations. Combining this method for catalyst candidate discovery with our GA-based catalyst optimization method results in an algorithm for truly de novo catalyst discovery.
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Affiliation(s)
- Maria H Rasmussen
- Department of Chemistry, University of Copenhagen, Universitetsparken 5, 2100, Copenhagen, Denmark
| | - Julius Seumer
- Department of Chemistry, University of Copenhagen, Universitetsparken 5, 2100, Copenhagen, Denmark
| | - Jan H Jensen
- Department of Chemistry, University of Copenhagen, Universitetsparken 5, 2100, Copenhagen, Denmark
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7
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Zhang Y, Xu C, Lan Z. Automated Exploration of Reaction Networks and Mechanisms Based on Metadynamics Nanoreactor Simulations. J Chem Theory Comput 2023. [PMID: 38031422 DOI: 10.1021/acs.jctc.3c00752] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2023]
Abstract
We developed an automated approach to construct a complex reaction network and explore the reaction mechanisms for numerous reactant molecules by integrating several theoretical approaches. Nanoreactor-type molecular dynamics was used to generate possible chemical reactions, in which the metadynamics was used to overcome the reaction barriers, and the semiempirical GFN2-xTB method was used to reduce the computational cost. Reaction events were identified from trajectories using the hidden Markov model based on the evolution of the molecular connectivity. This provided the starting points for further transition-state searches at the electronic structure levels of density functional theory to obtain the reaction mechanism. Finally, the entire reaction network containing multiple pathways was built. The feasibility and efficiency of the automated construction of the reaction network were investigated using the HCHO and NH3 biomolecular reaction and the reaction network for a multispecies system comprising dozens of HCN and H2O molecules. The results indicated that the proposed approach provides a valuable and effective tool for the automated exploration of the reaction networks.
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Affiliation(s)
- Yutai Zhang
- Guangdong Provincial Key Laboratory of Chemical Pollution and Environmental Safety and MOE Key Laboratory of Environmental Theoretical Chemistry, SCNU Environmental Research Institute, School of Environment, South China Normal University, Guangzhou 510006, P. R. China
| | - Chao Xu
- Guangdong Provincial Key Laboratory of Chemical Pollution and Environmental Safety and MOE Key Laboratory of Environmental Theoretical Chemistry, SCNU Environmental Research Institute, School of Environment, South China Normal University, Guangzhou 510006, P. R. China
| | - Zhenggang Lan
- Guangdong Provincial Key Laboratory of Chemical Pollution and Environmental Safety and MOE Key Laboratory of Environmental Theoretical Chemistry, SCNU Environmental Research Institute, School of Environment, South China Normal University, Guangzhou 510006, P. R. China
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8
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Hayashi H, Maeda S, Mita T. Quantum chemical calculations for reaction prediction in the development of synthetic methodologies. Chem Sci 2023; 14:11601-11616. [PMID: 37920348 PMCID: PMC10619630 DOI: 10.1039/d3sc03319h] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Accepted: 09/29/2023] [Indexed: 11/04/2023] Open
Abstract
Quantum chemical calculations have been used in the development of synthetic methodologies to analyze the reaction mechanisms of the developed reactions. Their ability to estimate chemical reaction pathways, including transition state energies and connected equilibria, has led researchers to embrace their use in predicting unknown reactions. This perspective highlights strategies that leverage quantum chemical calculations for the prediction of reactions in the discovery of new methodologies. Selected examples demonstrate how computation has driven the development of unknown reactions, catalyst design, and the exploration of synthetic routes to complex molecules prior to often laborious, costly, and time-consuming experimental investigations.
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Affiliation(s)
- Hiroki Hayashi
- Institute for Chemical Reaction Design and Discovery (WPI-ICReDD), Hokkaido University Kita 21, Nishi 10, Kita-ku Sapporo Hokkaido 001-0021 Japan
- JST-ERATO, Maeda Artificial Intelligence in Chemical Reaction Design and Discovery Project Kita 10, Nishi 8, Kita-ku Sapporo Hokkaido 060-0810 Japan
| | - Satoshi Maeda
- Institute for Chemical Reaction Design and Discovery (WPI-ICReDD), Hokkaido University Kita 21, Nishi 10, Kita-ku Sapporo Hokkaido 001-0021 Japan
- JST-ERATO, Maeda Artificial Intelligence in Chemical Reaction Design and Discovery Project Kita 10, Nishi 8, Kita-ku Sapporo Hokkaido 060-0810 Japan
- Department of Chemistry, Faculty of Science, Hokkaido University Kita 10, Nishi 8, Kita-ku Sapporo Hokkaido 060-0810 Japan
| | - Tsuyoshi Mita
- Institute for Chemical Reaction Design and Discovery (WPI-ICReDD), Hokkaido University Kita 21, Nishi 10, Kita-ku Sapporo Hokkaido 001-0021 Japan
- JST-ERATO, Maeda Artificial Intelligence in Chemical Reaction Design and Discovery Project Kita 10, Nishi 8, Kita-ku Sapporo Hokkaido 060-0810 Japan
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9
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Petrus E, Garay-Ruiz D, Reiher M, Bo C. Multi-Time-Scale Simulation of Complex Reactive Mixtures: How Do Polyoxometalates Form? J Am Chem Soc 2023; 145:18920-18930. [PMID: 37496164 DOI: 10.1021/jacs.3c05514] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/28/2023]
Abstract
Understanding the dynamics of reactive mixtures still challenges both experiments and theory. A relevant example can be found in the chemistry of molecular metal-oxide nanoclusters, also known as polyoxometalates. The high number of species potentially involved, the interconnectivity of the reaction network, and the precise control of the pH and concentrations needed in the synthesis of such species make the theoretical/computational treatment of such processes cumbersome. This work addresses this issue relying on a unique combination of recently developed computational methods that tackle the construction, kinetic simulation, and analysis of complex chemical reaction networks. By using the Bell-Evans-Polanyi approximation for estimating activation energies, and an accurate and robust linear scaling for correcting the computed pKa values, we report herein multi-time-scale kinetic simulations for the self-assembly processes of polyoxotungstates that comprise 22 orders of magnitude, from tens of femtoseconds to months of reaction time. This very large time span was required to reproduce very fast processes such as the acid/base equilibria (at 10-12 s), relatively slow reactions such as the formation of key clusters such as the metatungstate (at 103 s), and the very slow assembly of the decatungstate (at 106 s). Analysis of the kinetic data and of the reaction network topology shed light onto the details of the main reaction mechanisms, which explains the origin of kinetic and thermodynamic control followed by the reaction. Simulations at alkaline pH fully reproduce experimental evidence since clusters do not form under those conditions.
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Affiliation(s)
- Enric Petrus
- Institute of Chemical Research of Catalonia (ICIQ), The Barcelona Institute of Science and Technology (BIST), Avenida Països Catalans, 16, Tarragona 43007, Spain
| | - Diego Garay-Ruiz
- Institute of Chemical Research of Catalonia (ICIQ), The Barcelona Institute of Science and Technology (BIST), Avenida Països Catalans, 16, Tarragona 43007, Spain
| | - Markus Reiher
- Department of Chemistry and Applied Biosciences, ETH Zürich, Vladimir-Prelog-Weg 2, Zürich 8093, Switzerland
| | - Carles Bo
- Institute of Chemical Research of Catalonia (ICIQ), The Barcelona Institute of Science and Technology (BIST), Avenida Països Catalans, 16, Tarragona 43007, Spain
- Departament de Química Física i Inorgànica, Universitat Rovira i Virgili, Marcel•li Domingo s/n, Tarragona 43007, Spain
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10
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Zádor J, Martí C, Van de Vijver R, Johansen SL, Yang Y, Michelsen HA, Najm HN. Automated Reaction Kinetics of Gas-Phase Organic Species over Multiwell Potential Energy Surfaces. J Phys Chem A 2023; 127:565-588. [PMID: 36607817 DOI: 10.1021/acs.jpca.2c06558] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
Automation of rate-coefficient calculations for gas-phase organic species became possible in recent years and has transformed how we explore these complicated systems computationally. Kinetics workflow tools bring rigor and speed and eliminate a large fraction of manual labor and related error sources. In this paper we give an overview of this quickly evolving field and illustrate, through five detailed examples, the capabilities of our own automated tool, KinBot. We bring examples from combustion and atmospheric chemistry of C-, H-, O-, and N-atom-containing species that are relevant to molecular weight growth and autoxidation processes. The examples shed light on the capabilities of automation and also highlight particular challenges associated with the various chemical systems that need to be addressed in future work.
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Affiliation(s)
- Judit Zádor
- Combustion Research Facility, Sandia National Laboratories, Livermore94550, California, United States
| | - Carles Martí
- Combustion Research Facility, Sandia National Laboratories, Livermore94550, California, United States
| | | | - Sommer L Johansen
- Combustion Research Facility, Sandia National Laboratories, Livermore94550, California, United States
| | - Yoona Yang
- Combustion Research Facility, Sandia National Laboratories, Livermore94550, California, United States
| | - Hope A Michelsen
- Department of Mechanical Engineering, University of Colorado Boulder, Boulder80309, Colorado, United States
| | - Habib N Najm
- Combustion Research Facility, Sandia National Laboratories, Livermore94550, California, United States
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11
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Hashemi A, Bougueroua S, Gaigeot MP, Pidko EA. ReNeGate: A Reaction Network Graph-Theoretical Tool for Automated Mechanistic Studies in Computational Homogeneous Catalysis. J Chem Theory Comput 2022; 18:7470-7482. [PMID: 36321652 DOI: 10.1021/acs.jctc.2c00404] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Exploration of the chemical reaction space of chemical transformations in multicomponent mixtures is one of the main challenges in contemporary computational chemistry. To remove expert bias from mechanistic studies and to discover new chemistries, an automated graph-theoretical methodology is proposed, which puts forward a network formalism of homogeneous catalysis reactions and utilizes a network analysis tool for mechanistic studies. The method can be used for analyzing trajectories with single and multiple catalytic species and can provide unique conformers of catalysts including multinuclear catalyst clusters along with other catalytic mixture components. The presented three-step approach has the integrated ability to handle multicomponent catalytic systems of arbitrary complexity (mixtures of reactants, catalyst precursors, ligands, additives, and solvents). It is not limited to predefined chemical rules, does not require prealignment of reaction mixture components consistent with a reaction coordinate, and is not agnostic to the chemical nature of transformations. Conformer exploration, reactive event identification, and reaction network analysis are the main steps taken for identifying the pathways in catalytic systems given the starting precatalytic reaction mixture as the input. Such a methodology allows us to efficiently explore catalytic systems in realistic conditions for either previously observed or completely unknown reactive events in the context of a network representing different intermediates. Our workflow for the catalytic reaction space exploration exclusively focuses on the identification of thermodynamically feasible conversion channels, representative of the (secondary) catalyst deactivation or inhibition paths, which are usually most difficult to anticipate based solely on expert chemical knowledge. Thus, the expert bias is sought to be removed at all steps, and the chemical intuition is limited to the choice of the thermodynamic constraint imposed by the applicable experimental conditions in terms of threshold energy values for allowed transformations. The capabilities of the proposed methodology have been tested by exploring the reactivity of Mn complexes relevant for catalytic hydrogenation chemistry to verify previously postulated activation mechanisms and unravel unexpected reaction channels relevant to rare deactivation events.
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Affiliation(s)
- Ali Hashemi
- Inorganic Systems Engineering, Department of Chemical Engineering, Faculty of Applied Sciences, Delft University of Technology, Van der Maasweg 9, Delft 2629 HZ, The Netherlands
| | - Sana Bougueroua
- Laboratoire Analyse et Modélisation pour la Biologie et l'Environnement (LAMBE) UMR8587, Universite Paris-Saclay, Univ Evry, CNRS, LAMBE UMR8587, Evry-Courcouronnes 91025, France
| | - Marie-Pierre Gaigeot
- Laboratoire Analyse et Modélisation pour la Biologie et l'Environnement (LAMBE) UMR8587, Universite Paris-Saclay, Univ Evry, CNRS, LAMBE UMR8587, Evry-Courcouronnes 91025, France
| | - Evgeny A Pidko
- Inorganic Systems Engineering, Department of Chemical Engineering, Faculty of Applied Sciences, Delft University of Technology, Van der Maasweg 9, Delft 2629 HZ, The Netherlands
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12
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Ji L, Li Y, Wang J, Ning A, Zhang N, Liang S, He J, Zhang T, Qu Z, Gao J. Community Reaction Network Reduction for Constructing a Coarse-Grained Representation of Combustion Reaction Mechanisms. J Chem Inf Model 2022; 62:2352-2364. [PMID: 35442657 DOI: 10.1021/acs.jcim.2c00240] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
A community-reaction network reduction (CNR) approach is presented for mechanism reduction on the basis of a network-based community detection technique, a concept related to pre-equilibrium in chemical kinetics. In this method, the detailed combustion mechanism is first transformed into a weighted network, in which communities of species that have dense inner connections under the critical ignition conditions are identified. By analyzing the community partitions in different regions, we determine the effective functional groups and driving processes. Then, a skeletal model for the overall mechanism is deduced according to the network centrality data, including transition pathway identification and reaction-path flux. The CNR method is illustrated on the hydrogen autoignition system which has been extensively investigated, and a new reduced mechanism involving seven processes is proposed. Dynamics simulations employing the present CNR model show that the computed ignition time and distribution of major species on a wide range of temperature and pressure conditions are in accord with the experiments and results from other methods.
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Affiliation(s)
- Lin Ji
- Department of Chemistry, Capital Normal University, Beijing 100048, China
| | - Yue Li
- Department of Chemistry, Capital Normal University, Beijing 100048, China
| | - Jie Wang
- Department of Chemistry, Capital Normal University, Beijing 100048, China
| | - An Ning
- Department of Chemistry, Capital Normal University, Beijing 100048, China
| | - Naixin Zhang
- Department of Chemistry, Capital Normal University, Beijing 100048, China
| | - Shengyao Liang
- Department of Chemistry, Capital Normal University, Beijing 100048, China
| | - Jiyun He
- Department of Chemistry, Capital Normal University, Beijing 100048, China
| | - Tianyu Zhang
- Department of Chemistry, Capital Normal University, Beijing 100048, China
| | - Zexing Qu
- Laboratory of Theoretical and Computational Chemistry, Jilin University, Changchun 130015, China
| | - Jiali Gao
- Institute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen 518055, China.,Department of Chemistry and Supercomputing Institute, University of Minnesota, Minneapolis, Minnesota 55455, United States
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13
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Xing Y, Dong Y, Goergakis C, Zhuang Y, Zhang L, Du J, Meng Q. Automatic Data‐driven Stoichiometry Identification and Kinetic Modeling Framework for Homogeneous Organic Reactions. AIChE J 2022. [DOI: 10.1002/aic.17713] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Affiliation(s)
- Yafeng Xing
- School of Chemical Engineering Institute of Chemical Process Systems Engineering, Dalian University of Technology Dalian Liaoning China
| | - Yachao Dong
- School of Chemical Engineering Institute of Chemical Process Systems Engineering, Dalian University of Technology Dalian Liaoning China
| | - Christos Goergakis
- Chemical and Biological Engineering and Systems Research Institute, Tufts University Medford Massachusetts USA
| | - Yu Zhuang
- School of Chemical Engineering Institute of Chemical Process Systems Engineering, Dalian University of Technology Dalian Liaoning China
| | - Lei Zhang
- School of Chemical Engineering Institute of Chemical Process Systems Engineering, Dalian University of Technology Dalian Liaoning China
| | - Jian Du
- School of Chemical Engineering Institute of Chemical Process Systems Engineering, Dalian University of Technology Dalian Liaoning China
| | - Qingwei Meng
- State Key Laboratory of Fine Chemicals, School of Pharmaceutical Science and Technology Department Dalian University of Technology Dalian China
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14
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Rasmussen MH, Jensen JH. Fast and automated identification of reactions with low barriers using meta-MD simulations. PEERJ PHYSICAL CHEMISTRY 2022. [DOI: 10.7717/peerj-pchem.22] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
We test our meta-molecular dynamics (MD) based approach for finding low-barrier (<30 kcal/mol) reactions on uni- and bimolecular reactions extracted from the barrier dataset developed by Grambow, Pattanaik & Green (2020). For unimolecular reactions the meta-MD simulations identify 25 of the 26 products found by Grambow, Pattanaik & Green (2020), while the subsequent semiempirical screening eliminates an additional four reactions due to an overestimation of the reaction energies or estimated barrier heights relative to DFT. In addition, our approach identifies 36 reactions not found by Grambow, Pattanaik & Green (2020), 10 of which are <30 kcal/mol. For bimolecular reactions the meta-MD simulations identify 19 of the 20 reactions found by Grambow, Pattanaik & Green (2020), while the subsequent semiempirical screening eliminates an additional reaction. In addition, we find 34 new low-barrier reactions. For bimolecular reactions we found that it is necessary to “encourage” the reactants to go to previously undiscovered products, by including products found by other MD simulations when computing the biasing potential as well as decreasing the size of the molecular cavity in which the MD occurs, until a reaction is observed. We also show that our methodology can find the correct products for two reactions that are more representative of those encountered in synthetic organic chemistry. The meta-MD hyperparameters used in this study thus appear to be generally applicable to finding low-barrier reactions.
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15
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Chen X, Liu M, Gao J. CARNOT: a Fragment-Based Direct Molecular Dynamics and Virtual-Reality Simulation Package for Reactive Systems. J Chem Theory Comput 2022; 18:1297-1313. [PMID: 35129348 DOI: 10.1021/acs.jctc.1c01032] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Traditionally, the study of reaction mechanisms of complex reaction systems such as combustion has been performed on an individual basis by optimizations of transition structure and minimum energy path or by reaction dynamics trajectory calculations for one elementary reaction at a time. It is effective, but time-consuming, whereas important and unexpected processes could have been missed. In this article, we present a direct molecular dynamics (DMD) approach and a virtual-reality simulation program, CARNOT, in which plausible chemical reactions are simulated simultaneously at finite temperature and pressure conditions. A key concept of the present ab initio molecular dynamics method is to partition a large, chemically reactive system into molecular fragments that can be adjusted on the fly of a DMD simulation. The theory represents an extension of the explicit polarization method to reactive events, called ReX-Pol. We propose a highest-and-lowest adapted-spin approximation to define the local spins of individual fragments, rather than treating the entire system by a delocalized wave function. Consequently, the present ab initio DMD can be applied to reactive systems consisting of an arbitrarily varying number of closed and open-shell fragments such as free radicals, zwitterions, and separate ions found in combustion and other reactions. A graph-data structure algorithm was incorporated in CARNOT for the analysis of reaction networks, suitable for reaction mechanism reduction. Employing the PW91 density functional theory and the 6-31+G(d) basis set, the capabilities of the CARNOT program were illustrated by a combustion reaction, consisting of 28 650 atoms, and by reaction network analysis that revealed a range of mechanistic and dynamical events. The method may be useful for applications to other types of complex reactions.
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Affiliation(s)
- Xin Chen
- Peking University Shenzhen Graduate School, Shenzhen, Guangdong 581055, China.,Institute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen, Guangdong 581055, China
| | - Meiyi Liu
- Peking University Shenzhen Graduate School, Shenzhen, Guangdong 581055, China.,Institute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen, Guangdong 581055, China
| | - Jiali Gao
- Peking University Shenzhen Graduate School, Shenzhen, Guangdong 581055, China.,Institute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen, Guangdong 581055, China.,Department of Chemistry and Supercomputing Institute, University of Minnesota, Minneapolis, Minnesota 55455, United States
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16
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Garay-Ruiz D, Álvarez-Moreno M, Bo C, Martínez-Núñez E. New Tools for Taming Complex Reaction Networks: The Unimolecular Decomposition of Indole Revisited. ACS PHYSICAL CHEMISTRY AU 2022; 2:225-236. [PMID: 36855573 PMCID: PMC9718323 DOI: 10.1021/acsphyschemau.1c00051] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
The level of detail attained in the computational description of reaction mechanisms can be vastly improved through tools for automated chemical space exploration, particularly for systems of small to medium size. Under this approach, the unimolecular decomposition landscape for indole was explored through the automated reaction mechanism discovery program AutoMeKin. Nevertheless, the sheer complexity of the obtained mechanisms might be a hindrance regarding their chemical interpretation. In this spirit, the new Python library amk-tools has been designed to read and manipulate complex reaction networks, greatly simplifying their overall analysis. The package provides interactive dashboards featuring visualizations of the network, the three-dimensional (3D) molecular structures and vibrational normal modes of all chemical species, and the corresponding energy profiles for selected pathways. The combination of the joined mechanism generation and postprocessing workflow with the rich chemistry of indole decomposition enabled us to find new details of the reaction (obtained at the CCSD(T)/aug-cc-pVTZ//M06-2X/MG3S level of theory) that were not reported before: (i) 16 pathways leading to the formation of HCN and NH3 (via amino radical); (ii) a barrierless reaction between methylene radical and phenyl isocyanide, which might be an operative mechanism under the conditions of the interstellar medium; and (iii) reaction channels leading to both hydrogen cyanide and hydrogen isocyanide, of potential astrochemical interest as the computed HNC/HCN ratios greatly exceed the calculated equilibrium value at very low temperatures. The reported reaction networks can be very valuable to supplement databases of kinetic data, which is of remarkable interest for pyrolysis and astrochemical studies.
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Affiliation(s)
- Diego Garay-Ruiz
- Institute
of Chemical Research of Catalonia (ICIQ), Barcelona Institute of Science & Technology (BIST), Avinguda Països Catalans,
16, 43007 Tarragona, Spain,Departament
de Química Física i Inorgànica, Universitat Rovira i Virgili (URV), Marcel·lí Domingo s/n, 43007 Tarragona, Spain
| | - Moises Álvarez-Moreno
- Institute
of Chemical Research of Catalonia (ICIQ), Barcelona Institute of Science & Technology (BIST), Avinguda Països Catalans,
16, 43007 Tarragona, Spain
| | - Carles Bo
- Institute
of Chemical Research of Catalonia (ICIQ), Barcelona Institute of Science & Technology (BIST), Avinguda Països Catalans,
16, 43007 Tarragona, Spain,Departament
de Química Física i Inorgànica, Universitat Rovira i Virgili (URV), Marcel·lí Domingo s/n, 43007 Tarragona, Spain,
| | - Emilio Martínez-Núñez
- Departmento
de Química Física, Facultade de Química, Universidade de Santiago de Compostela, 15782 Santiago
de Compostela, Spain,
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17
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Cui Q, Peng J, Xu C, Lan Z. Automatic Approach to Explore the Multireaction Mechanism for Medium-Sized Bimolecular Reactions via Collision Dynamics Simulations and Transition State Searches. J Chem Theory Comput 2022; 18:910-924. [DOI: 10.1021/acs.jctc.1c00795] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Qinghai Cui
- Guangdong Provincial Key Laboratory of Chemical Pollution and Environmental Safety and MOE Key Laboratory of Environmental Theoretical Chemistry, SCNU Environmental Research Institute, School of Environment, South China Normal University, Guangzhou 510006, P. R. China
| | - Jiawei Peng
- Guangdong Provincial Key Laboratory of Chemical Pollution and Environmental Safety and MOE Key Laboratory of Environmental Theoretical Chemistry, SCNU Environmental Research Institute, School of Environment, South China Normal University, Guangzhou 510006, P. R. China
| | - Chao Xu
- Guangdong Provincial Key Laboratory of Chemical Pollution and Environmental Safety and MOE Key Laboratory of Environmental Theoretical Chemistry, SCNU Environmental Research Institute, School of Environment, South China Normal University, Guangzhou 510006, P. R. China
- Key Laboratory of Theoretical Chemistry of Environment, Ministry of Education; School of Chemistry, South China Normal University, Guangzhou 510006, P. R. China
| | - Zhenggang Lan
- Guangdong Provincial Key Laboratory of Chemical Pollution and Environmental Safety and MOE Key Laboratory of Environmental Theoretical Chemistry, SCNU Environmental Research Institute, School of Environment, South China Normal University, Guangzhou 510006, P. R. China
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18
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Shannon RJ, Deeks HM, Burfoot E, Clark E, Jones AJ, Mulholland AJ, Glowacki DR. Exploring human-guided strategies for reaction network exploration: Interactive molecular dynamics in virtual reality as a tool for citizen scientists. J Chem Phys 2021; 155:154106. [PMID: 34686059 DOI: 10.1063/5.0062517] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
The emerging fields of citizen science and gamification reformulate scientific problems as games or puzzles to be solved. Through engaging the wider non-scientific community, significant breakthroughs may be made by analyzing citizen-gathered data. In parallel, recent advances in virtual reality (VR) technology are increasingly being used within a scientific context and the burgeoning field of interactive molecular dynamics in VR (iMD-VR) allows users to interact with dynamical chemistry simulations in real time. Here, we demonstrate the utility of iMD-VR as a medium for gamification of chemistry research tasks. An iMD-VR "game" was designed to encourage users to explore the reactivity of a particular chemical system, and a cohort of 18 participants was recruited to playtest this game as part of a user study. The reaction game encouraged users to experiment with making chemical reactions between a propyne molecule and an OH radical, and "molecular snapshots" from each game session were then compiled and used to map out reaction pathways. The reaction network generated by users was compared to existing literature networks demonstrating that users in VR capture almost all the important reaction pathways. Further comparisons between humans and an algorithmic method for guiding molecular dynamics show that through using citizen science to explore these kinds of chemical problems, new approaches and strategies start to emerge.
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Affiliation(s)
- Robin J Shannon
- School of Chemistry, University of Bristol, Bristol BS8 1TS, United Kingdom
| | - Helen M Deeks
- School of Chemistry, University of Bristol, Bristol BS8 1TS, United Kingdom
| | - Eleanor Burfoot
- School of Chemistry, University of Bristol, Bristol BS8 1TS, United Kingdom
| | - Edward Clark
- School of Chemistry, University of Bristol, Bristol BS8 1TS, United Kingdom
| | - Alex J Jones
- School of Chemistry, University of Bristol, Bristol BS8 1TS, United Kingdom
| | | | - David R Glowacki
- ArtSci Foundation International, 5th floor Mariner House, Bristol, BS1 4QD, United Kingdom
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