Efficient Reaction Space Exploration with ChemTraYzer-TAD

Rational Understanding Hydroxide Diffusion Mechanism in Anion Exchange Membranes during Electrochemical Processes with RDAnalyzer

Enhancing the understanding of hydroxide transport mechanisms in anion exchange membranes (AEMs) is beneficial for the rational design of high-performance AEMs in the renewable energy system. However, the high complexity and lack of adequate analytic tools make it challenging to clarify different mechanisms unambiguously. Herein, we developed an in-house toolkit, the Reactive Diffusion Analyzer (RDAnalyzer), to conduct an effective analysis of hydroxide diffusion mechanisms from ReaxFF molecular dynamic simulations. Using the experimentally well-synthesized T20NC6NC5N as a model system, we successfully decoupled the hydroxide diffusion mechanisms into free Vehicular and free Grotthuss, as well as associated Vehicular and associated Grotthuss, which was not yet achieved previously. Meanwhile, RDAnalyzer managed to specifically identify the drift length of hydroxide species for each mechanism under the electric field, which worked as a useful variable for calculating the conductivity of AEMs. Our theoretically predicted conductivity for T20NC6NC5N agrees reasonably with experimental results, indicating the reliability of RDAnalyzer. This work not only provides a rational understanding of the complex hydroxide diffusion mechanisms in AEMs but also holds the potential to guide the rational design of high-performance AEMs with computations.

Tracking Thermo-Oxidation Reaction Products and Pathways of Modified Lignin Structures from Reactive Molecular Dynamics Simulations

Thermo-oxidation of biomass is an important process that occurs through a variety of reaction pathways depending on the chemical nature of the molecules and reaction conditions. These processes can be modeled using reactive molecular dynamics to study chemical reactions and the evolution of converted molecules over time. The advantage of this approach is that many molecules can be modeled, but it is challenging to use the large amount of data obtained from such a simulation to determine reaction products and pathways. In this study, we developed a tracking approach to identify the reaction pathways of the dominant reaction products from reactive molecular dynamics simulations. We demonstrated the approach for thermo-oxidation reactions of modified model lignin compounds. For two modified lignin structures, we tracked the evolving chemical species to find the most common reaction products. Subsequently, we monitored specific bonds to determine the individual steps in the reaction process. This combined approach of reactive molecular dynamics and tracking enabled us to identify the most likely thermo-oxidation pathways. The methodology can be used to investigate the thermo-oxidative pathways of a wider range of chemical compounds.

Automated Skeleton Network Generation for ReaxFF Molecular Dynamics Simulations of Hydrocarbon Fuel Pyrolysis and Oxidation via a Rate-Based Algorithm

In this study, we present an automated approach of rate-based skeleton network generation for ReaxFF MD simulation (RxMD-SN) for deriving the reaction kinetic mechanism of large hydrocarbon fuels in pyrolysis and oxidation from large-scale ReaxFF MD simulations. The approach contains the statistical calculation of reaction rate constants and the generation of skeleton reaction networks using a rate-based algorithm. The RxMD-SN method takes advantage of reaction flux ranking at a small time interval in terms of temporal reaction rate to extract the core reaction networks, which allows for keeping the rare reaction events that may be dominant in a certain period of the reaction network. The kinetic models derived from ReaxFF MD simulation in CH4 oxidation can reproduce what was obtained in the ReaxFF MD simulation, which demonstrates the capability of RxMD-SN in capturing the global reaction kinetics. An evaluation of reaction rate constants indicates that close kinetic parameters are shared for n-octane oxidation of similar reaction classes, shared oxidation reactions of CH4 against n-heptane, and shared pyrolysis reactions of the RP-3 surrogate fuel against n-heptane. This capability of RxMD-SN is particularly beneficial in meeting the challenges in characterizing the oxidation reaction kinetics of large hydrocarbon molecules. RxMD-SN approach is potentially a general approach in chemical kinetics modeling on the basis of ReaxFF MD simulations.

Generating a skeleton reaction network for reactions of large-scale ReaxFF MD pyrolysis simulations based on a machine learning predicted reaction class

The reactive molecular dynamics using ReaxFF provides an effective means to generate global reactions for pyrolysis of realistic fuel mixtures. The reactions from large-scale pyrolysis simulations of a fuel mixture may be characterized by multiple reaction sites, explosion of intermediate species structures, and scattered contribution of diversified pathways to product species. This work proposes an approach of SRG-Reax aiming at generating skeleton reaction networks based on reaction patterns or classes of reaction centers from huge reactions obtained from ReaxFF MD simulations of realistic fuel pyrolysis. SRG-Reax (Skeleton Reaction network Generation for ReaxFF MD) is implemented through building a semi-supervised machine learning model of tri-training for predicting the reaction classes of pyrolysis reactions based on an extended reaction center. Three different reaction center descriptions of reaction features and reaction transformation fingerprints are employed as inputs for developing the tri-training classifier. Major reaction pathways can be identified based on reaction class ratios and product species ratios calculated by merging reaction pathways of the same reaction class. The SRG-Reax approach was applied in skeleton reaction network generation for RP-3 pyrolysis based on the ReaxFF MD simulations of a high-fidelity 45-component RP-3 fuel model. The skeleton reaction networks for n-paraffins, iso-paraffins, cycloparaffins, olefins, and aromatics in RP-3 pyrolysis were obtained. The reaction class ratios and product species ratios in the obtained skeleton reaction network provide comprehensive intuitive insight into global pyrolysis chemistry. SRG-Reax has the potential to obtain relatively complete skeleton reaction networks for the pyrolysis of hydrocarbon fuel, polymers, biomass, coal, and more.

Automated Exploration of Reaction Networks and Mechanisms Based on Metadynamics Nanoreactor Simulations

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.

Quantum chemical calculations for reaction prediction in the development of synthetic methodologies

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.

Combined molecular dynamics and coordinate driving method for automatically searching complicated reaction pathways

The combined molecular dynamics and coordinate driving (MD/CD) method is updated and generalized in this work to broaden its applications in automatically searching reaction pathways for complicated reactions. In this updated version, MD simulations are performed with the GFN's family of methods to systematically sample conformers for almost any systems with atomic numbers Z ≤ 86. The improved CD procedure is greatly accelerated by applying a pre-screening stage at the semiempirical GFN2-xTB level. An automatic module based on the Marcus theory and its improved version (the Wolynes theory) is designed to include single electron transfer (SET) processes into reaction pathways. The capabilities of this method are demonstrated by exploring the most possible reaction pathways of three experimentally reported reactions: the organophosphine-catalyzed trans phosphinoboration, the Fe(II) complex-mediated C(sp2)-H borylation reaction, and the SET-triggered deaminative radical cross-coupling reaction. Comprehensive reaction networks are obtained for all three reactions with reasonable computational costs. Detailed mechanisms for these reactions can account for the reported experimental facts.

Decomposition mechanism of 1,3,5-trinitro-2,4,6-trinitroaminobenzene under thermal and shock stimuli using ReaxFF molecular dynamics simulations

To obtain atomic-level insights into the decomposition behavior of 1,3,5-trinitro-2,4,6-trinitroaminobenzene (TNTNB) under different stimulations, this study applied reactive molecular dynamics simulations to illustrate the effects of thermal and shock stimuli on the TNTNB crystal. The results show that the initial decomposition of the TNTNB crystal under both thermal and shock stimuli starts with the breakage of the N-NO₂ bond. However, the C₆ ring in TNTNB undergoes structural rearrangement to form a C₃-C₅ bicyclic structure at a constant high temperature. Then, the C₃ and C₅ rings break in turn. The main final products of TNTNB under shock are N₂, CO₂, and H₂O, while NO,  N_2, H₂O and CO are formed instead at 1 atm under a constant high temperature. Pressure is the main reason for this difference. High pressure promotes the complete oxidation of the reactants.

A Reactive Molecular Dynamics Study of Chlorinated Organic Compounds. Part I: Force Field Development

This work presents a novel parametrization for the ReaxFF formalism as a means to investigate reaction processes of chlorinated organic compounds. Force field parameters cover the chemical elements C, H, O, Cl and were obtained using a novel optimization approach involving relaxed potential energy surface scans as training targets. The resulting ReaxFF parametrization shows good transferability, as demonstrated on two independent ab initio validation sets. While this first part of our two-paper series focuses on force field parametrization, we apply our parameters to the simulation of chlorinated dibenzofuran formation and decomposition processes in Part II.

A Reactive Molecular Dynamics Study of Chlorinated Organic Compounds. Part II: A ChemTraYzer Study of Chlorinated Dibenzofuran Formation and Decomposition Processes

In our two-paper series, we first present the development of ReaxFF CHOCl parameters using the recently published ParAMS parametrization tool. In this second part, we update the reactive Molecular Dynamics - Quantum Mechanics coupling scheme ChemTraYzer and combine it with our new ReaxFF parameters from Part I to study formation and decomposition processes of chlorinated dibenzofurans. We introduce a self-learning method for recovering failed transition-state searches that improves the overall ChemTraYzer transition-state search success rate by 10 percentage points to a total of 48 %. With ChemTraYzer, we automatically find and quantify more than 500 reactions using transition state theory and DFT. Among the discovered chlorinated dibenzofuran reactions are numerous reactions that are new to the literature. In three case studies, we discuss the set of reactions that are most relevant to the dibenzofuran literature: (i) bimolecular reactions of the chlorinated-dibenzofuran precursors phenoxy radical and 1,3,5-trichlorobenzene, (ii) dibenzofuran chlorination and pyrolysis, and (iii) oxidation of chlorinated dibenzofurans.

Chemoton 2.0: Autonomous Exploration of Chemical Reaction Networks

Fueled by advances in hardware and algorithm design, large-scale automated explorations of chemical reaction space have become possible. Here, we present our approach to an open-source, extensible framework for explorations of chemical reaction mechanisms based on the first-principles of quantum mechanics. It is intended to facilitate reaction network explorations for diverse chemical problems with a wide range of goals such as mechanism elucidation, reaction path optimization, retrosynthetic path validation, reagent design, and microkinetic modeling. The stringent first-principles basis of all algorithms in our framework is key for the general applicability that avoids any restrictions to specific chemical systems. Such an agile framework requires multiple specialized software components of which we present three modules in this work. The key module, Chemoton, drives the exploration of reaction networks. For the exploration itself, we introduce two new algorithms for elementary-step searches that are based on Newton trajectories. The performance of these algorithms is assessed for a variety of reactions characterized by a broad chemical diversity in terms of bonding patterns and chemical elements. Chemoton successfully recovers the vast majority of these. We provide the resulting data, including large numbers of reactions that were not included in our reference set, to be used as a starting point for further explorations and for future reference.

Spiers Memorial Lecture: theory of unimolecular reactions

One hundred years ago, at an earlier Faraday Discussion meeting, Lindemann presented a mechanism that provides the foundation for contemplating the pressure dependence of unimolecular reactions. Since that time, our...