Probing the dynamics and bottleneck of the key atmospheric SO2 oxidation reaction by the hydroxyl radical.

SO2 (Sulfur dioxide) is the major precursor to the production of sulfuric acid (H2SO4), contributing to acid rain and atmospheric aerosols. Sulfuric acid formed from SO2 generates light-reflecting sulfate aerosol particles in the atmosphere. This property has prompted recent geoengineering proposals to inject sulfuric acid or its precursors into the Earth's atmosphere to increase the planetary albedo to counteract global warming. SO2 oxidation in the atmosphere by the hydroxyl radical HO to form HOSO2 is a key rate-limiting step in the mechanism for forming acid rain. However, the dynamics of the HO + SO2 → HOSO2 reaction and its slow rate in the atmosphere are poorly understood to date. Herein, we use photoelectron spectroscopy of cryogenically cooled HOSO2- anion to access the neutral HOSO2 radical near the transition state of the HO + SO2 reaction. Spectroscopic and dynamic calculations are conducted on the first ab initio-based full-dimensional potential energy surface to interpret the photoelectron spectra of HOSO2- and to probe the dynamics of the HO + SO2 reaction. In addition to the finding of a unique pre-reaction complex (HO⋯SO2) directly connected to the transition state, dynamic calculations reveal that the accessible phase space for the HO + SO2 → HOSO2 reaction is extremely narrow, forming a key reaction bottleneck and slowing the reaction rate in the atmosphere, despite the low reaction barrier. This study underlines the importance of understanding the full multidimensional potential energy surface to elucidate the dynamics of complex bimolecular reactions involving polyatomic reactants.

Machine Learning of Reactive Potentials.

In the past two decades, machine learning potentials (MLPs) have driven significant developments in chemical, biological, and material sciences. The construction and training of MLPs enable fast and accurate simulations and analysis of thermodynamic and kinetic properties. This review focuses on the application of MLPs to reaction systems with consideration of bond breaking and formation. We review the development of MLP models, primarily with neural network and kernel-based algorithms, and recent applications of reactive MLPs (RMLPs) to systems at different scales. We show how RMLPs are constructed, how they speed up the calculation of reactive dynamics, and how they facilitate the study of reaction trajectories, reaction rates, free energy calculations, and many other calculations. Different data sampling strategies applied in building RMLPs are also discussed with a focus on how to collect structures for rare events and how to further improve their performance with active learning.

Dynamical Reweighting for Biased Rare Event Simulations.

Dynamical reweighting techniques aim to recover the correct molecular dynamics from a simulation at a modified potential energy surface. They are important for unbiasing enhanced sampling simulations of molecular rare events. Here, we review the theoretical frameworks of dynamical reweighting for modified potentials. Based on an overview of kinetic models with increasing level of detail, we discuss techniques to reweight two-state dynamics, multistate dynamics, and path integrals. We explore the natural link to transition path sampling and how the effect of nonequilibrium forces can be reweighted. We end by providing an outlook on how dynamical reweighting integrates with techniques for optimizing collective variables and with modern potential energy surfaces.

Cuts through the manifold of molecular H2O potential energy surfaces in liquid water at ambient conditions.

The fluctuating hydrogen bridge bonded network of liquid water at ambient conditions entails a varied ensemble of the underlying constituting H2O molecular moieties. This is mirrored in a manifold of the H2O molecular potentials. Subnatural line width resonant inelastic X-ray scattering allowed us to quantify the manifold of molecular potential energy surfaces along the H2O symmetric normal mode and the local asymmetric O-H bond coordinate up to 1 and 1.5 Å, respectively. The comparison of the single H2O molecular potentials and spectroscopic signatures with the ambient conditions liquid phase H2O molecular potentials is done on various levels. In the gas phase, first principles, Morse potentials, and stepwise harmonic potential reconstruction have been employed and benchmarked. In the liquid phase the determination of the potential energy manifold along the local asymmetric O-H bond coordinate from resonant inelastic X-ray scattering via the bound state oxygen 1s to [Formula: see text] resonance is treated within these frameworks. The potential energy surface manifold along the symmetric stretch from resonant inelastic X-ray scattering via the oxygen 1s to [Formula: see text] resonance is based on stepwise harmonic reconstruction. We find in liquid water at ambient conditions H2O molecular potentials ranging from the weak interaction limit to strongly distorted potentials which are put into perspective to established parameters, i.e., intermolecular O-H, H-H, and O-O correlation lengths from neutron scattering.

Potential energy surfaces and dynamic properties via ab initio composite and density functional approaches.

Vibrational spectroscopy enables critical insight into the structural and dynamic properties of molecules. Presently, the majority of theoretical approaches to spectroscopy employ wavefunction-based ab initio or density functional methods that rely on the harmonic approximation. This approximation breaks down for large molecules with strongly anharmonic bonds or for molecules with large internuclear separations. An alternative to these methods involves generating molecular anharmonic potential energy surfaces (potentials) and using them to extrapolate the vibrational frequencies. This study examines the efficacy of density functional theory (DFT) and the correlation consistent Composite Approach (ccCA) in generating anharmonic frequencies from potentials of small main group molecules. Vibrational self-consistent field Theory (VSCF) and post-VSCF methods were used to calculate the fundamental frequencies of these molecules from their potentials. Functional choice, basis set selection, and mode-coupling are also examined as factors in influencing accuracy. The absolute deviations for the calculated frequencies using potentials at the ccCA level of theory were lower than the potentials at the DFT level. With DFT resulting in bending modes that are better described than those of ccCA, a multilevel DFT:ccCA approach where DFT potentials are used for single vibrational mode potentials and ccCA is used for vibrational mode-mode couplings can be utilized for larger polyatomic systems. The frequencies obtained with this multilevel approach using VCIPSI-PT2 were closer to experimental frequencies than the scaled harmonic frequencies, indicating the success of utilizing post-VSCF methods to generate more accurate representations of computed infrared spectra.

A Q-learning method based on coarse-to-fine potential energy surface for locating transition state and reaction pathway.

Transition state (TS) on the potential energy surface (PES) plays a key role in determining the kinetics and thermodynamics of chemical reactions. Inspired by the fact that the dynamics of complex systems are always driven by rare but significant transition events, we herein propose a TS search method in accordance with the Q-learning algorithm. Appropriate reward functions are set for a given PES to optimize the reaction pathway through continuous trial and error, and then the TS can be obtained from the optimized reaction pathway. The validity of this Q-learning method with reasonable settings of Q-value table including actions, states, learning rate, greedy rate, discount rate, and so on, is exemplified in 2 two-dimensional potential functions. In the applications of the Q-learning method to two chemical reactions, it is demonstrated that the Q-learning method can predict consistent TS and reaction pathway with those by ab initio calculations. Notably, the PES must be well prepared before using the Q-learning method, and a coarse-to-fine PES scanning scheme is thus introduced to save the computational time while maintaining the accuracy of the Q-learning prediction. This work offers a simple and reliable Q-learning method to search for all possible TS and reaction pathway of a chemical reaction, which may be a new option for effectively exploring the PES in an extensive search manner.

"On-the-fly" Crystal : How to reliably and automatically characterize and construct potential energy surfaces.

In this work, the Crystal  code, developed previously by the authors to find "holes" as well as legitimate transition states in existing potential energy surface (PES) functions [JPC Lett. 11, 6468 (2020)], is retooled to perform on-the-fly "direct dynamics"-type PES explorations, as well as automatic construction of new PES functions. In all of these contexts, the chief advantage of Crystal  over other methods is its ability to globally map the PES, thereby determining the most relevant regions of configuration space quickly and reliably-even when the dimensionality is rather large. Here, Crystal  is used to generate a uniformly spaced grid of density functional theory (DFT) or ab initio points, truncated over the relevant regions, which can then be used to either: (a) hone in precisely on PES features such as minima and transition states, or; (b) create a new PES function automatically, via interpolation. Proof of concept is demonstrated via application to three molecular systems: water (H 2 O), (reduced-dimensional) methane (CH 4 ), and methylene imine (CH 2 NH).

Ab initio molecular dynamics study of intersystem crossing dynamics for MH2 (M = Si, Ge, Sn, Pb) on spin-pure and spin-mixed potential energy surfaces.

Recently, surface-hopping ab initio molecular dynamics (SH-AIMD) simulations have come to be used to discuss the mechanisms and dynamics of excited-state chemical reactions, including internal conversion and intersystem crossing. In dynamics simulations involving intersystem crossing, there are two potential energy surfaces (PESs) governing the motion of nuclei: PES in a spin-pure state and PES in a spin-mixed state. The former gives wrong results for molecular systems with large spin-orbit coupling (SOC), while the latter requires a potential gradient that includes a change in SOC at each point, making the computational cost very high. In this study, we systematically investigate the extent to which the magnitude of SOC affects the results of the spin-pure state-based dynamics simulations for the hydride MH2 (M = Si, Ge, Sn, Pb) by performing SH-AIMD simulations based on spin-pure and spin-mixed states. It is clearly shown that spin-mixed state PESs are indispensable for the dynamics simulation of intersystem crossing in systems containing elements Sn and Pb from the fifth period onward. Furthermore, in addition to the widely used Tully's fewest switches (TFS) algorithm, the Zhu-Nakamura (ZN) global switching algorithm, which is computationally less expensive, is applied to SH for comparison. The results from TFS- and ZN-SH-AIMD methods are in qualitative agreement, suggesting that the less expensive ZN-SH-AIMD can be successfully utilized to investigate the dynamics of photochemical reactions based on quantum chemical calculations.

Evolution Mechanism of Solid-Phase Catalysts During Catalytic Growth of Single-Walled Carbon Nanotubes.

Using solid nanoparticles (NPs) as catalysts is the most effective method to achieve catalytic growth of single-walled carbon nanotubes (SWCNTs) with ultrapure chirality. Until now, SWCNTs with a suitable chirality purity have not been prepared in experiments. That is, the evolution of solid NPs during the catalytic growth of SWCNTs is in contradiction with the original concept of a changeless structure. Hence, in this work, the evolution mechanism of solid cobalt NPs during the nucleation process of SWCNTs is analyzed through molecular dynamics. Similar to the experimental observations, the results show that a drastic structural fluctuation of the NPs occurs during the nucleation of SWCNTs. This structural fluctuation is caused by the fact that the elastic strain energy and surface energy of the NPs can be tuned when a carbon gradient exists between the subsurface and interior of the NP. Furthermore, such a carbon gradient can be reduced by changing the carbon feeding rate. This work not only reveals the evolution mechanism of solid catalysts during the nucleation of SWCNTs but also provides prospects for realizing solid catalysts with a changeless structure by tuning the experimental parameters.

Solvent Effect on Dative and Ionic Bond Strengths: A Unified Theory from the Potential Analysis and Valence Bond (VB) Computation.

Solvent molecules interact with a solute through various intermolecular forces. Here we employed a potential energy surface (PES) analysis to interpret the solvent-induced variations in the strengths of dative (Me3NBH3) and ionic (LiCl) bonds, which possess both ionic and covalent (neutral) characteristics. The change of a bond is driven by the gradient (force) of the solvent-solute interaction energy with respect to the focused bond length. Positive force shortens the bond length and increases the bond force constant, leading to a blue-shift of the bond stretching vibrational frequency upon solvation. Conversely, negative force elongates the bond, resulting in a reduced bond force constant and red-shift of the stretching vibrational frequency. The different responses of Me3NBH3 and LiCl to solvation are studied with valence bond (VB) theory, as Me3NBH3 and LiCl are dominated by the neutral covalent VB structure and the ionic VB structure, respectively. The dipole moment of an ionic VB structure increases along the increasing bond distance, while the dipole moment of a neutral covalent VB structure increases with the decreasing bond distance. The roles of the dominating VB structures are further examined by the geometry optimizations and frequency calculations with the block-localized wavefunction (BLW) method.

Toward Ab Initio Reaction Discovery Using the Artificial Force Induced Reaction Method.

Predicting the whole process of a chemical reaction while solving kinetic equations presents an opportunity to realize an on-the-fly kinetic simulation that directly discovers chemical reactions with their product yields. Such a simulation avoids the combinatorial explosion of reaction patterns to be examined by narrowing the search space based on the kinetic analysis of the reaction path network, and would open a new paradigm beyond the conventional two-step approach, which requires a reaction path network prior to performing a kinetic simulation. The authors addressed this issue and developed a practical method by combining the artificial force induced reaction method with the rate constant matrix contraction method. Two algorithms are available for this purpose: a forward mode with reactants as the input and a backward mode with products as the input. This article first numerically verifies these modes for known reactions and then demonstrates their application to the actual reaction discovery. Finally, the challenges of this method and the prospects for ab initio reaction discovery are discussed.

Advances in the Dynamics of Adsorbate Diffusion on Metal Surfaces: Focus on Hydrogen and Oxygen.

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.

A ReaxFF Potential for Modeling Organic Matter Degradation with Oxybromine Oxidants.

Oxidation of organic matter with oxybromine oxidants is ushering in a new era of enhanced hydrocarbon recovery. While these potent reagents are being tested in laboratory and field experiments, there is a pressing demand to delineate the molecular processes governing oxidation reactions at geological depth. Here, we parameterize a ReaxFF potential to model the oxidative decompositions of aliphatic and aromatic hydrocarbons in the presence of water-NaBr solutions that contain oxybromine (BrOn)- oxidizers. Our parameterization results in a reliable empirical bond-order potential that accurately calculates bond energies, exhibiting an RMSE of ∼1.18 eV, corresponding to 1.36 % average error. Reproducing bond dissociation and binding energies from Density Functional Theory (DFT), our parameterization proves transferable to aqueous environments. This H/C/O/Na/Br ReaxFF potential accurately reproduces the oxidation pathways of small hydrocarbons with oxybromine oxidizers. This force field captures proton and oxygen transfer, C-C bond tautomerization, and cleavage, leading to ring-opening and chain fragmentation. Molecular dynamic simulations demonstrate the oxidative degradation of aromatic and aliphatic kerogen-like moieties in bulk solutions. We envision that such reactive force fields will be useful to understand better the oxidation reactions of organic matter formed in geological reservoirs for enhanced shale gas recovery and improved carbon dioxide treatments.

Temperature-Dependent Line-Broadening Effects in CO2 Caused by Ar.

This computational study of line-broadening effects is based on an accurate, analytical representation of the intermonomer potential energy surface (PES) of the CO2 ⋅ Ar van der Waals (vdW) complex. The PES is employed to compute collisional broadening coefficients for rovibrational lines of CO2 perturbed by Ar. The semiclassical computations are performed using the modified Robert-Bonamy approach, including real and imaginary terms, and the exact trajectory model. The lines investigated are in the 10001←00011, 01101←00001, 00011←00001, and 00031←00001 vibrational bands and the computations are repeated at multiple temperatures. The computed results are in good agreement with the available experimental values, validating both the intermonomer PES developed and the methodology used. For lines in the 01101←00001 band of CO2 , temperature-dependent Ar-broadening coefficients are reported for the first time. The parameters presented should prove useful, among other applications, for the accurate experimental determination of CO2 and Ar abundances in planetary atmospheres.

Novel Insecticidal Pyridylhydrazono Derivatives Identified via Scaffold Hopping and Conformation Regulation Strategies.

Insect transient receptor potential vanilloid (TRPV) channels are critical targets for insecticides. In this study, various scaffold-hopping strategies were employed in the rational design of pyridylhydrazono derivatives as potential insect TRPV channels modulators. Insecticidal bioassay demonstrated that the initial target compounds exhibited lower insecticidal activity compared to pymetrozine, with the optimal compound B3 exhibiting a mortality rate of 53.3% against Aphis craccivora at 400 mg·L-1. Conformation analysis indicated that the high energy barrier required for the transition from the lowest-energy conformation to the active conformation may be a key factor contributing to the reduced insecticidal activities of the target compounds. Further structural optimizations aimed at reducing this energy barrier through binding mode-based conformation regulation led to the identification of optimal target 4-(3'-pyridylhydrazono)pyrazol-5-one derivatives C1 and C2. These compounds exhibited reduced transition energy barriers and improved insecticidal activity, with moderate mortality rate of 66.3% and 75.7% against A. craccivora at 400 mg·L-1, respectively. These findings provide valuable insights for future research on the discovery of insect TRPV modulators and have significant implications for the development of more effective agricultural insecticides.

Multi-Level Protocol for Mechanistic Reaction Studies Using Semi-Local Fitted Potential Energy Surfaces.

In this work, we propose a multi-level protocol for routine theoretical studies of chemical reaction mechanisms. The initial reaction paths of our investigated systems are sampled using the Nudged Elastic Band (NEB) method driven by a cheap electronic structure method. Forces recalculated at the more accurate electronic structure theory for a set of points on the path are fitted with a machine learning technique (in our case symmetric gradient domain machine learning or sGDML) to produce a semi-local reactive potential energy surface (PES), embracing reactants, products and transition state (TS) regions. This approach has been successfully applied to a unimolecular (Bergman cyclization of enediyne) and a bimolecular (SN2 substitution) reaction. In particular, we demonstrate that with only 50 to 150 energy-force evaluations with the accurate reference methods (here complete-active-space self-consistent field, CASSCF, and coupled-cluster singles and doubles, CCSD) it is possible to construct a semi-local PES giving qualitative agreement for stationary-point geometries, intrinsic reaction coordinates and barriers. Furthermore, we find a qualitative agreement in vibrational frequencies and reaction rate coefficients. The key aspect of the method's performance is its multi-level nature, which not only saves computational effort but also allows extracting meaningful information along the reaction path, characterized by zero gradients in all but one direction. Agnostic to the nature of the TS and computationally economic, the protocol can be readily automated and routinely used for mechanistic reaction studies.

A Globally Accurate Neural Network Potential Energy Surface and Quantum Dynamics Studies on Be+(2S) + H2/D2 → BeH+/BeD+ + H/D Reactions.

Chemical reactions between Be+ ions and H2 molecules have significance in the fields of ultracold chemistry and astrophysics, but the corresponding dynamics studies on the ground-state reaction have not been reported because of the lack of a global potential energy surface (PES). Herein, a globally accurate ground-state BeH2+ PES is constructed using the neural network model based on 18,657 ab initio points calculated by the multi-reference configuration interaction method with the aug-cc-PVQZ basis set. On the newly constructed PES, the state-to-state quantum dynamics calculations of the Be+(2S) + H2(v0 = 0; j0 = 0) and Be+(2S) + D2(v0 = 0; j0 = 0) reactions are performed using the time-dependent wave packet method. The calculated results suggest that the two reactions are dominated by the complex-forming mechanism and the direct abstraction process at relatively low and high collision energies, respectively, and the isotope substitution has little effect on the reaction dynamics characteristics. The new PES can be used to further study the reaction dynamics of the BeH2+ system, such as the effects of rovibrational excitations and alignment of reactant molecules, and the present dynamics data could provide an important reference for further experimental studies at a finer level.

Effects of Chalcogen Atoms on Excited-State Double-Proton Transfer Behavior for 3,6-bis(4,5-Dihydroxyoxazo-2-yl)benzene-1,2-diol Derivatives: A Computational Investigation.

The impact of the chalcogen atomic electronegativity (O, S, and Se atoms) of new organic molecules on excited-state dynamical reactions is self-evident. Inspired by this kind of distinguished photochemical characteristic, in this work, we performed a computational investigation of chalcogen-substituted 3,6-bis(4,5-dihydroxyoxazo-2-yl)benzene-1,2-diol (BDYBD) derivatives (i.e., BDYBD-O, BDYBD-S, and BDYBD-Se). In this paper, we pay close attention to characteristic BDYBD derivatives that contain intramolecular double hydrogen bonds (O1-H2···N3 and O4-H5···N6). The main goal of this study was to explore how changes in atomic electronegativity affect the way hydrogen bonds interact and how excited molecules affect transfer protons. We go into further detail in the main text of the paper. By fixing our attention to geometrical variations and infrared (IR) vibrational spectra between the S0 and S1 states, exploring hydrogen bonding behaviors using the core-valence bifurcation (CVB) index, and simulating hydrogen bonding energy (EHB) via the atom in molecule (AIM) method, we clarified the photo-induced strengthened dual hydrogen bonding interactions that facilitate the excited-state dual-proton transfer (ESDPT) behavior of BDYBD derivatives. The reorganization of charge stemming from photoexcitation further verifies the tendencies of ESDPT reactions. We relied on constructing potential energy surfaces (PESs) by adopting a restrictive optimization approach, and herein, we finally clarify the gradual ESDPT mechanism of BDYBD derivatives. Particularly, we confirm that the variation in chalcogen atomic electronegativity has a regulatory effect on the ESDPT behavior of BDYBD derivatives; that is, the lower the atomic electronegativity, the more favorable it is for the gradual ESDPT reaction.

Deciphering the Factors Controlling Hydrogen and Methyl Spillover upon Methane Dissociation on Rh/Cu(111) Single-Atom Alloy.

Spillover of adsorbed species from one active site to another is a key step in heterogeneous catalysis. However, the factors controlling this step, particularly the spillover of polyatomic species, have rarely been studied. Herein, we investigate the spillover dynamics of H* and CH3* species on a single-atom alloy surface (Rh/Cu(111)) upon the dissociative chemisorption of methane (CH4), using molecular dynamics that considers both surface phonons and electron-hole pairs. These dynamical calculations are made possible by a high-dimensional potential energy surface machine learned from density functional theory data. Our results provide compelling evidence that the H* and CH3* can spill over on the metal surface at experimental temperatures and reveal novel dynamical features involving an internal motion during diffusion for CH3*. Increasing surface temperature has a minor effect on promoting spillover, as geminate recombinative desorption becomes more prevalent. However, the poisoning of the active site can be mitigated by the frequent gaseous molecular collisions that occur under ambient pressure in real-world catalysis, which transfer energy to the trapped adsorbates. Interestingly, the bulky CH3* exhibits a significant spillover advantage over the light H* due to its larger size, which facilitates energy acquisition. These insights help to advance our understanding of spillover in heterogeneous catalysis.

A mechanistic insight for the biosynthesis of N,N-dimethyltryptamine: An ONIOM theoretical approach.

Psychoactive natural products are potent serotonergic agonists capable of modulating brain functions such as memory and cognition. These substances have shown therapeutic potential for treating various mental disorders. The fact that N,N-dimethyltryptamine (DMT) is produced endogenously in several plants and animals, including humans, makes it particularly attractive. As an amino acid-derived alkaloid, the DMT biosynthetic pathway is part of the L-tryptophan biochemical cascade and can be divided into the decarboxylation by an aromatic L-amino acid decarboxylase (AADC) for tryptamine formation and the subsequent double-methylation by the indolethylamine-N-methyltransferase (INMT) through the cofactor S-adenosyl-L-methionine (SAM), a methyl donor. Unlike the decarboxylation mechanism of L-tryptophan, the molecular details of the double methylation of tryptamine have not been elucidated. Therefore, we propose an in silico model using molecular dynamics (MD), non-covalent interaction index (NCI) and density functional theory (DFT) calculations with the ONIOM QM:MM B3LYP/6-31+G(d,p):MM/UFF level of theory. Based on the obtained energetic data, the potential energy surface (PES) indicates an SN2 mechanism profile, with the second methylation energy barrier being the rate-limiting step with δG‡=60kJ∙mol-1 larger than the previous methylation, following the NCI analysis showing more repulsive interactions for the second transition state. In addition, the hybridization information of each reaction step provides geometric details about the double-methylation.