Global Mapping of Equilibrium and Transition Structures on Potential Energy Surfaces by the Scaled Hypersphere Search Method: Applications to ab Initio Surfaces of Formaldehyde and Propyne Molecules

Effects of the chain length of nonaromatic epoxy resins on thermomechanical and optical properties: experiments, and ab initio and molecular dynamics simulations

Epoxy resin has been extensively used in the field of advanced electronic materials as an adhesive and encapsulant owing to its excellent material properties. However, recently, there has been a demand for further improvement in heat resistance, high transparency, environmental resistance, and enhanced handling properties for high-brightness light-emitting diodes. Conventional aromatic epoxy resins lack light resistance; therefore, a colorless and transparent epoxy resin without aromatic rings is desirable. In this study, tris(2,3-epoxypropyl) isocyanurate (TEPIC) was used as a nonaromatic epoxy resin, and three types of TEPIC with different side-chain lengths were prepared. The ultraviolet (UV)-visible absorption properties of TEPIC were evaluated using time-dependent density functional theory, and the practicality of the numerical prediction of light resistance was verified. TEPIC yields a UV absorbance spectrum with a lower intensity than those of conventional aromatic epoxy resins, suggesting that TEPIC is expected to have high light resistance. In addition, their thermomechanical properties and the influence of molecular structure were evaluated using both molecular dynamics (MD) simulations and experiments. The MD simulation and experimental results were in good agreement, indicating that the long side chains of TEPIC suppress triaxial deformation-induced failure and improve ductility instead of decreasing strength and stiffness. In addition, the longer side chains form a dense molecular structure with less free volume. These results indicate that numerical approaches can be used to predict various properties of epoxy resins and interpret them from the molecular structure. Accordingly, these approaches can be used to aid the material development process.

Temperature effects on the branching dynamics in the model ambimodal (6 + 4)/(4 + 2) intramolecular cycloaddition reaction

C14H20 (tetradecapentaene) is a simple model system exhibiting post transition-state behavior, wherein both the (6 + 4) and (4 + 2) cycloaddition products are formed from one ambimocal transition state structure. We studied the bifurcation dynamics starting from the two ambimodal transition state structures, the chair-form and boat-form, using the quasi-classical trajectory, classical molecular dynamics, and ring-polymer molecular dynamics methods on the parameter-optimized semiempirical GFN2-xTB potential energy surface. It was found that the calculated branching fractions differ between the chair-form and boat-form due to the different nature in the IRC pathways. We also investigated the effects of temperature on bifurcation dynamics and found that, at higher temperatures, trajectories stay longer in the intermediate region of the potential energy surface.

Observation of the Infrared-Induced Structural Change in the Microscopic Hydrogen Bond Network of Phenol-Methanol Cluster Cations in a Cold-Ion Trap

To gain insight into microscopic hydrogen bond networks, we measured ultraviolet photodissociation (UVPD) spectra of the phenol-methanol 1:3 cluster cation, [PhOH(MeOH)3]+ trapped in a variable temperature ion trap. At low temperatures, an isomer with a ring-type hydrogen bond structure dominates, whereas at higher temperatures the chain-type isomers become dominant due to the flexibility of their hydrogen bond structures. We also found a clear temperature dependence of the spectral features, such as band position and width. In addition to the above measurement, we observed the infrared (IR) induced isomerization of [PhOH(MeOH)3]+ to study the dynamical aspects of hydrogen bond networks. We succeeded in observing IR-induced isomerization from the ring to chain forms of [PhOH(MeOH)3]+ at low temperature. The isomerization was clearly identified as a change in the UVPD spectra. The time evolution of the UVPD spectra after IR excitation indicated that the IR-induced isomerization occurs within a nanosecond. The chain-type isomers produced by the IR-induced isomerization are then converted back to the ring-type form by collisions with cold He buffer gas in the trap. This backward isomerization proceeds with a time constant of 100 μs under our experimental conditions. In this study, we evaluated the temperatures of the chain isomers during the backward isomerization on the basis of the spectral features.

Reproducing Reaction Mechanisms with Machine-Learning Models Trained on a Large-Scale Mechanistic Dataset

Mechanistic understanding of organic reactions can facilitate reaction development, impurity prediction, and in principle, reaction discovery. While several machine learning models have sought to address the task of predicting reaction products, their extension to predicting reaction mechanisms has been impeded by the lack of a corresponding mechanistic dataset. In this study, we construct such a dataset by imputing intermediates between experimentally reported reactants and products using expert reaction templates and train several machine learning models on the resulting dataset of 5,184,184 elementary steps. We explore the performance and capabilities of these models, focusing on their ability to predict reaction pathways and recapitulate the roles of catalysts and reagents. Additionally, we demonstrate the potential of mechanistic models in predicting impurities, often overlooked by conventional models. We conclude by evaluating the generalizability of mechanistic models to new reaction types, revealing challenges related to dataset diversity, consecutive predictions, and violations of atom conservation.

Theoretical Analysis of Coordination Geometries in Transition Metal-Histidine Complexes Using Quantum Chemical Calculations

A theoretical investigation utilizing density functional theory (DFT) calculations was conducted to explore the coordination complexes formed between histidine (His) ligands and various divalent transition metal ions (Mn2+, Fe2+, Co2+, Ni2+, Cu2+, and Zn2+). Conformational exploration of the His ligand was initially performed to assess its stability upon coordination. Both 1:1 and 1:2 of metal-to-ligand complexes were scrutinized to elucidate their structural features and the relative stability of the complexes. This study examined the ability of His to act as a bidentate or tridentate coordinating ligand, along with the differences in coordination geometry when solvent effects were incorporated. The reduced density gradient (RDG) analysis and local electron attachment energy (LEAE) analysis were employed to elucidate the interaction planes and the nucleophilic and electrophilic properties. The electronic properties were analyzed through electrostatic potential (ESP) maps and natural population analysis (NPA) of atomic charge distributions. This computational study provides valuable insights into the diverse coordination modes of His and its interactions with divalent transition metal ions, contributing to a better understanding of the role of this amino acid ligand in the formation of transition metal complexes. The findings can aid in the design and construction of self-assembled structures involving His-metal coordination.

Quantum Chemical Investigation into the Structural Analysis and Calculated Raman Spectra of Amylose Modeled with Linked Glucose Molecules

This study presents a quantum chemical investigation into the structural analysis and calculated Raman spectra of modeled amylose with varying units of linked glucose molecules. We systematically examined the rotation of hydroxymethyl groups and intramolecular hydrogen bonds within these amylose models. Our study found that as the number of linked glucose units increases, the linear structure becomes more complex, resulting in curled, cyclic, or helical structures facilitated by establishing various intramolecular interactions. The hydroxymethyl groups were confirmed to form interactions with oxygen atoms and with hydroxymethyl and hydroxyl groups from adjacent rings in the molecular structures. We identified distinct peaks and selected specific bands applicable in various analytical contexts by comparing their calculated Raman spectra. Representative vibrational modes within selected regions were identified across the different lengths of amylose models, serving as characteristic signatures for linear and more coiled structural conformations. Our findings contribute to a deeper understanding of amylose structures and spectroscopic signatures, with implications for theoretical studies and potential applications. This work provides valuable reference points for the detailed assignment of Raman peaks of amylose structure, facilitating their application in broader research on carbohydrate structures and their associated spectroscopic properties.

Proton Transfer Processes in 2-Butenenitrile Dimer Cation Studied by Mass-Selective Infrared Spectroscopy

2-Butenenitrile (2-Bu) is a recently discovered crucial interstellar molecule. Herein, an abnormal NH band was observed in the infrared spectrum of the 2-Bu dimer cation, suggestive of a proton transfer reaction within the cluster. Through a comprehensive theoretical analysis of the IR spectrum of (2-Bu)2+, we discovered not only the formation of a new C-N bond through the attachment of one 2-Bu to another but also the occurrence of a proton transfer reaction in the cluster. This proton was identified as originating from the methyl group of the attaching 2-Bu in the cluster based on the analysis of IR spectra of (2-Bu)+ and [2-Bu-acrylonitrile (AN)]+. Furthermore, the detailed reaction process of this ion-molecule reaction is examined with theoretical calculation. This finding contributes significantly to our deeper understanding of ion-molecule reactions in the gas phase and the formation of nitrogen-containing prebiotic molecules in the interstellar medium.

Theoretical Study of the Thermal Rate Coefficients of the H3+ + C2H4 Reaction: Dynamics Study on a Full-Dimensional Potential Energy Surface

Ion-molecular reactions play a significant role in molecular evolution within the interstellar medium. In this study, the entrance channel reaction, H3+ + C2H4 → H2 + C2H5+, was investigated using classical molecular dynamic (classical MD) and ring polymer molecular dynamic (RPMD) simulation techniques. We developed an analytical potential energy surface function with a permutationally invariant polynomial basis, specifically employing the monomial symmetrized approach. Our dynamic simulations reproduced the rate coefficient of 300 K for H3+ + C2H4 → H2 + C2H5+, aligning reasonably well with the values in the kinetic database commonly utilized in astrochemistry. The thermal rate coefficients obtained using both the classical MD and RPMD techniques exhibited an increase from 100 K to 300 K as the temperature rose. Additionally, we analyzed the excess energy distribution of the C2H5+ fragment with respect to temperature to investigate the indirect reaction pathway of C2H5+ → H2 + C2H3+. This result suggests that the indirect reaction pathway of C2H5+ → H2 + C2H3+ holds minor significance, although the distribution highly depends on the collisional temperature.

Infrared Spectroscopy of Neutral and Cationic Benzonitrile-Methanol Binary Clusters in Supersonic Jets

The formation of nitrogen-containing organic interstellar molecules is of great importance to reveal chemical processes and the origin of life on Earth. Benzonitrile (BN) is one of the simplest nitrogen-containing aromatic molecules in the interstellar medium (ISM) that has been detected in recent years. Methanol (CH3OH) exists widely in interstellar space with high reactivity. Herein, we measured the infrared (IR) spectra of neutral and cationic BN-CH3OH clusters by vacuum ultraviolet (VUV) photoionization combined with time-of-flight mass spectrometry. Combining IR spectra with the density functional theory calculations, we reveal that the BN-CH3OH intends to form a cyclic H-bonded structure in neutral clusters. However, after the ionization of BN-CH3OH clusters, proton-shared N···H···O and N···H···C structures are confirmed to form between BN and CH3OH, with the minor coexistence of H-bond and O-π structures. The formation of the proton-shared structure expands our knowledge of the evolution of the life-related nitrogen-containing molecules in the universe and provides a possible pathway to the further study of biorelevant aromatic organic macromolecules.

Effect of inorganic material surface chemistry on structures and fracture behaviours of epoxy resin

The mechanisms underlying the influence of the surface chemistry of inorganic materials on polymer structures and fracture behaviours near adhesive interfaces are not fully understood. This study demonstrates the first clear and direct evidence that molecular surface segregation and cross-linking of epoxy resin are driven by intermolecular forces at the inorganic surfaces alone, which can be linked directly to adhesive failure mechanisms. We prepare adhesive interfaces between epoxy resin and silicon substrates with varying surface chemistries (OH and H terminations) with a smoothness below 1 nm, which have different adhesive strengths by ~13 %. The epoxy resins within sub-nanometre distance from the surfaces with different chemistries exhibit distinct amine-to-epoxy ratios, cross-linked network structures, and adhesion energies. The OH- and H-terminated interfaces exhibit cohesive failure and interfacial delamination, respectively. The substrate surface chemistry impacts the cross-linked structures of the epoxy resins within several nanometres of the interfaces and the adsorption structures of molecules at the interfaces, which result in different fracture behaviours and adhesive strengths.

Dissipative Particle Dynamics Simulation for Reaction-Induced Phase Separation of Thermoset/Thermoplastic Blends

Reaction-induced phase separation occurs during the curing reaction when a thermoplastic resin is dissolved in a thermoset resin, which enables toughening of the thermoset resin. As resin properties vary significantly depending on the morphology of the phase-separated structure, controlling the morphology formation is of critical importance. Reaction-induced phase separation is a phenomenon that ranges from the chemical reaction scale to the mesoscale dynamics of polymer molecules. In this study, we performed curing simulations using dissipative particle dynamics (DPD) coupled with a reaction model to reproduce reaction-induced phase separation. The curing reaction properties of the thermoset resin were determined by ab initio quantum chemical calculations, and the DPD parameters were determined by all-atom molecular dynamics simulations. This enabled mesoscopic simulations, including reactions that reflect the intrinsic material properties. The effects of the thermoplastic resin concentration, molecular weight, and curing conditions on the phase-separation morphology were evaluated, and the cure shrinkage and stiffness of each cured resin were confirmed to be consistent with the experimental trends. Furthermore, the local strain field under tensile deformation was visualized, and the inhomogeneous strain field caused by the phase-separated structures of two resins with different stiffnesses was revealed. These results can aid in understanding the toughening properties of thermoplastic additives at the molecular level.

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 of Flexible Tripeptide-Ni(II) Ion-Mediated Supramolecular Fragments and Comparative Analysis of Tripeptide Complexes with Various Metal(II) Ions

An automated conformational search method was employed to efficiently determine the stable conformers and weak hydrogen bonds of a flexible tripeptide coordinated with a solitary metal(II) ion in an aqueous environment. Quantum chemical calculations were performed to investigate the tendency of octahedral coordination formation between different metal(II) ions and various coordination models (ammonia molecule, chelate molecule, and flexible tripeptide). The octahedral coordination was analyzed by decomposing it into tridentate, bidentate, and monodentate coordination model complexes to assess their formation propensities and conformational properties. Additionally, population analysis, including electrostatic potential mapping and natural population analysis, was performed to identify the unique properties of the Ni(II) ion in forming octahedral coordination in crystals and to explore the potential of other metal(II) ions for self-assembling novel coordination configurations in peptide-metal compounds. Two common hydrogen bonding interactions were examined by using artificial forces to facilitate dissociation or reinforcement.

Possible Roles of Transition Metal Cations in the Formation of Interstellar Benzene via Catalytic Acetylene Cyclotrimerization

Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous interstellar molecules. However, the formation mechanisms of PAHs and even the simplest cyclic aromatic hydrocarbon, benzene, are not yet fully understood. Recently, we reported the statistical and dynamical properties in the reaction mechanism of Fe+-catalyzed acetylene cyclotrimerization, whereby three acetylene molecules are directly converted to benzene. In this study, we extended our previous work and explored the possible role of the complex of other 3d transition metal cations, TM+ (TM = Sc, Ti, Mn, Co, and Ni), as a catalyst in acetylene cyclotrimerization. Potential energy profiles for bare TM+-catalyst (TM = Sc and Ti), for TM+NC--catalyst (TM = Sc, Ti, Mn, Co, and Ni), and for TM+-(H2O)8-catalyst (TM = Sc and Ti) systems were obtained using quantum chemistry calculations, including the density functional theory levels. The calculation results show that the scandium and titanium cations act as efficient catalysts in acetylene cyclotrimerization and that reactants, which contain an isolated acetylene and (C2H2)2 bound to a bare (ligated) TM cation (TM = Sc and Ti), can be converted into a benzene-metal-cation product complex without an entrance barrier. We found that the number of electrons in the 3d orbitals of the transition metal cation significantly contributes to the catalytic efficiency in the acetylene cyclotrimerization process. On-the-fly Born-Oppenheimer molecular dynamics (BOMD) simulations of the Ti+-NC- and Ti+-(H2O)8 complexes were also performed to comprehensively understand the nuclear dynamics of the reactions. The computational results suggest that interstellar benzene can be produced via acetylene cyclotrimerization reactions catalyzed by transition metal cation complexes.

Single-Photon Ionization Induced New Covalent Bond Formation in Acrylonitrile(AN)-Pyrrole(Py) Clusters

The formation of nitrogen-containing organic compounds is crucial for understanding chemical evolution and the origin of life in the interstellar medium (ISM). In this study, we explore whether acrylonitrile (AN) and pyrrole (Py) can form new nitrogen-containing compounds after single-photon ionization in their gaseous clusters by vacuum ultraviolet (VUV)-infrared (IR) spectroscopy and theoretical calculations. The results show that a strong linear H-bond is formed in neutral AN-Py, while cyclic or bicyclic H-bonded networks are formed in the neutral AN-Py2 cluster. It is found that the structure containing a new C-C covalent bond between two moieties in (AN-Py)+ is formed besides the formation of H-bonded structures after AN-Py is ionized by VUV light. In (AN-Py2)+ cluster cations, new C-C or C-N covalent bonds tend to be formed between two Py, with (Py)2+ as the core in the cluster. The results reveal that new covalent bonds are more likely to be formed between two Py species when AN and Py are present in the cationic clusters. These results provide spectroscopic evidence of the formation of new nitrogen-containing organic compounds from AN and Py induced by VUV, which are helpful for our understanding of the formation of diverse prebiotic molecules in interstellar space.

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.

Concertedness and Activation Energy Control by Distal Methyl Group during Ring Contraction/Expansion in Scalarane-Type Sesterterpenoid Biosynthesis

Salmahyritisol A, similan A, and hippospongide A, which are scalarane-type sesterterpenoids, feature 6/6/5/7/5 pentacyclic skeletons. Although their biosyntheses have been previously proposed to involve a unique skeletal rearrangement reaction, the detailed reaction mechanism remains unclear as none of the corresponding biosynthetic enzymes for this reaction have been reported. Herein, this skeletal rearrangement reaction was investigated using computational techniques, which revealed the following four key features: (i) the distal 24-Me substituent controls both the concertedness and activation energy of this transformation, (ii) enzymes are not responsible for the observed regioselectivity of C12-C20 bond formation, (iii) stereoselectivity is enzyme-regulated, and (iv) protonation is a key step in this skeletal rearrangement process. These new findings provide insight into the C-ring-contraction and D-ring-expansion mechanisms in scalarane-type sesterterpenoid biosyntheses.

Exploring the Quantum Chemical Energy Landscape with GNN-Guided Artificial Force

Artificial force has been proven useful to get over energy barriers and quickly search a large portion of the energy landscape. This work proposes a method based on graph neural networks to optimize the choice of transformation patterns to examine and accelerate energy landscape exploration. In open search from glutathione, the search efficiency was largely improved in comparison to random selection. We also applied transfer learning from glutathione to tuftsin, resulting in further efficiency gains.

Prediction of High-Yielding Single-Step or Cascade Pericyclic Reactions for the Synthesis of Complex Synthetic Targets

Pericyclic reactions, which involve cyclic concerted transition states without ionic or radical intermediates, have been extensively studied since their definition in the 1960s, and the famous Woodward-Hoffmann rules predict their stereoselectivity and chemoselectivity. Here, we describe the application of a fully automated reaction-path search method, that is, the artificial force induced reaction (AFIR), to trace an input compound back to reasonable starting materials through thermally allowed pericyclic reactions via product-based quantum-chemistry-aided retrosynthetic analysis (QCaRA) without using any a priori experimental knowledge. All categories of pericyclic reactions, including cycloadditions, ene reactions, group-transfer, cheletropic, electrocyclic, and sigmatropic reactions, were successfully traced back via concerted reaction pathways, and starting materials were computationally obtained with the correct stereochemistry. Furthermore, AFIR was used to predict whether the identified reaction pathway can be expected to occur in good yield relative to other possible reactions of the identified starting material. In order to showcase its practical utility, this state-of-the-art technology was also applied to the retrosynthetic analysis of a natural product with a relatively high number of atoms (52 atoms: endiandric acid C methyl ester), which was first synthesized by Nicolaou in 1982 and provided the corresponding starting polyenes with the correct stereospecificity via three pericyclic reaction cascades (one Diels-Alder reaction as well as 6π and 8π electrocyclic reactions). Moreover, not only systems that obey the Woodward-Hoffmann rules but also systems that violate these rules, such as those recently calculated by Houk, can be retrosynthesized accurately.

Graph-Driven Reaction Discovery: Progress, Challenges, and Future Opportunities

Graph-based descriptors, such as bond-order matrices and adjacency matrices, offer a simple and compact way of categorizing molecular structures; furthermore, such descriptors can be readily used to catalog chemical reactions (i.e., bond-making and -breaking). As such, a number of graph-based methodologies have been developed with the goal of automating the process of generating chemical reaction network models describing the possible mechanistic chemistry in a given set of reactant species. Here, we outline the evolution of these graph-based reaction discovery schemes, with particular emphasis on more recent methods incorporating graph-based methods with semiempirical and ab initio electronic structure calculations, minimum-energy path refinements, and transition state searches. Using representative examples from homogeneous catalysis and interstellar chemistry, we highlight how these schemes increasingly act as "virtual reaction vessels" for interrogating mechanistic questions. Finally, we highlight where challenges remain, including issues of chemical accuracy and calculation speeds, as well as the inherent challenge of dealing with the vast size of accessible chemical reaction space.

Successes and challenges in using machine-learned activation energies in kinetic simulations

The prediction of the thermodynamic and kinetic properties of chemical reactions is increasingly being addressed by machine-learning (ML) methods such as artificial neural networks (ANNs). While a number of recent studies have reported success in predicting chemical reaction activation energies, less attention has focused on how the accuracy of ML predictions filter through to predictions of macroscopic observables. Here, we consider the impact of the uncertainty associated with ML prediction of activation energies on observable properties of chemical reaction networks, as given by microkinetics simulations based on ML-predicted reaction rates. After training an ANN to predict activation energies given standard molecular descriptors for reactants and products alone, we performed microkinetics simulations of three different prototypical reaction networks: formamide decomposition, aldol reactions and decomposition of 3-hydroperoxypropanal. We find that the kinetic modelling predictions can be in excellent agreement with corresponding simulations performed with ab initio calculations, but this is dependent on the inherent energetic landscape of the networks. We use these simulations to suggest some guidelines for when ML-based activation energies can be reliable, and when one should take more care in applications to kinetics modelling.

Spectroscopic evidence of S∴N and S∴O hemibonds in heterodimer cations

Computational and condensed phase experimental evidence for the existence of S∴N and S∴O hemibonded structures has been reported previously, but no gas phase experimental evidence has been reported. To experimentally explore the existence of the S∴N and S∴O hemibonds in the gas phase, we recorded the infrared photodissociation action spectra of four cationic clusters: [CH₃SH-NH₃]⁺, [CH₃SCH₃-NH₃]⁺, [CH₃SCH₃-H₂O]⁺, and [CH₃OCH₃-H₂O]⁺. Combined with the calculation results, it is found that the S∴N hemibonded structure is competitive with the S⋯HN H-bonded structure, though only the latter structure is actually observed in [CH₃SH-NH₃]⁺. The spectral and theoretical results show that hemibonds can form between the second- (oxygen or nitrogen) and the third-period elements (sulfur) in the heterodimer clusters of [CH₃SCH₃-NH₃]⁺ and [CH₃SCH₃-H₂O]⁺. However, the S∴N and S∴O hemibonded structures are found competitive with the C⋯HN and CH⋯O H-bonded structures, respectively, and both the structures coexist. On the other hand, the O∴O hemibonded structure is much less stable than other hydrogen bonded (H-bonded) structures in [CH₃OCH₃-H₂O]⁺, and it shows no clear contribution to the observed spectrum. This study provides direct spectroscopic evidence for the existence of S∴N and S∴O hemibonds in the gas phase and their competition with the H-bonds, which may be also fundamentally important in biological processes.

DFT Study on the Biosynthesis of Asperterpenol and Preasperterpenoid Sesterterpenoids: Exclusion of Secondary Carbocation Intermediates and Origin of Structural Diversification

The biosynthetic pathway to asperterpenol, a sesterterpenoid featuring a 6/6/8/5 tetracyclic ring system, was proposed to involve three secondary (2°) carbocation intermediates (B, D, and I), but it remains controversial whether or not these are viable. Further, the proposed 11/6/5 tricyclic intermediate C has the same "ChemDraw" structure as an intermediate in the biosynthesis of preasperterpenoid, which has a very different 5/7/(3)6/5 pentacyclic skeleton. Here, we present a detailed scrutiny of the asperterpenol/preasperterpenoid biosynthetic pathways based on comprehensive DFT calculations.

New Tools for Taming Complex Reaction Networks: The Unimolecular Decomposition of Indole Revisited

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.

Kinetic Analysis of a Reaction Path Network Including Ambimodal Transition States: A Case Study of an Intramolecular Diels-Alder Reaction

This study proposes a methodology for the kinetic analysis of a reaction path network including ambimodal transition states (TSs), through which an ensemble of trajectories bifurcates to multiple minima in a phenomenon called dynamical bifurcation. The proposed methodology consists of three techniques: an automated reaction path search to construct a reaction path network including ambimodal TSs, an ab initio molecular dynamics simulation to evaluate the branching ratio, and the definition of rate constants incorporating this ratio. Applying the procedure to a Diels-Alder reaction, it was found that the inclusion of dynamical bifurcations is necessary to explain the experimental reaction yield of a byproduct. In addition, it was verified that the products take 10¹³ s to reach thermal equilibrium and that the experimental selectivity is determined by the dynamical bifurcations.

Ring-Polymer Molecular Dynamics Calculations of Thermal Rate Coefficients and Branching Ratios for the Interstellar H3+ + CO → H2 + HCO+/HOC+ Reaction and Its Deuterated Analogue

The reaction between H₃⁺ and CO is important in understanding the H₃⁺ destruction mechanism in the interstellar medium. In this work, thermal rate coefficients for the H₃⁺ + CO and D₃⁺ + CO reactions are calculated using ring-polymer molecular dynamics (RPMD) on a high-level machine-learning potential energy surface. The RPMD results agree well with the classical molecular dynamics results, where nuclear quantum effects are completely ignored, whereas the agreement between the RPMD results and the previous quasi-classical trajectory is good only at low temperatures. The calculated [HCO⁺]/[HOC⁺] product branching ratios decrease as the temperature increases, and the product branching is exclusively determined by the initial collisional orientation, which governs the formation of an ion-dipole complex, H₃⁺···CO or H₃⁺···OC, that dissociates into H₂ + HCO⁺ or H₂ + HOC⁺, respectively, via a direct mechanism. However, the contribution of the indirect mechanism via the rearrangement between H₃⁺···CO and H₃⁺···OC increases as the temperature increases, although its absolute fraction is small.

In vitro and in silico studies of potential coronavirus-specific 3C-like protease inhibitors

We investigated similar compounds to ebselen and tideglusib, which exhibit strong activity against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), using MACCS keys. Four candidate compounds were identified. One of them, phenyl-benzothiazol-3-one, showed coronavirus-specific 3C-like (3CL) protease inhibitory activity. The results indicated that a similarity score above 0.81 is a good indicator of activity for ebselen-and-tideglusib-like compounds. Subsequently, we simulated the ring-cleavage Michael reaction of ebselen at the Se center, which is responsible for its 3CL protease inhibitory activity, and determined the activation free energy of the reaction. The results showed that reaction simulation is a useful tool for estimating the activity of inhibitory compounds that undergo Michael addition reactions with the relevant cysteine S atom of 3CL proteases.

Theoretical Study on the Mechanism of Spirocyclization in Spiroviolene Biosynthesis

Spiroviolene is a spirocyclic triquinane diterpene produced by Streptomyces violens. Recently, a biosynthetic pathway that includes secondary carbocation intermediates and a complicated concerted skeletal rearrangement was proposed for spiroviolene, based upon careful labeling experiments. On the basis of density functional theory (DFT) calculations, we propose a revised pathway for spiroviolene biosynthesis, involving a multistep carbocation cascade that bypasses the formation of unstable secondary carbocations by breaking the adjacent C-C bond to form a more stable tertiary carbocation (IM3) and by Wagner-Meerwein 1,2-methyl rearrangement (IM7).

DFT Study on the Biosynthesis of Verrucosane Diterpenoids and Mangicol Sesterterpenoids: Involvement of Secondary-Carbocation-Free Reaction Cascades

Some experimental observations indicate that a sequential formation of secondary (2°) carbocations might be involved in some biosynthetic pathways, including those of verrucosane-type diterpenoids and mangicol-type sesterterpenoids, but it remains controversial whether or not such 2° cations are viable intermediates. Here, we performed comprehensive density functional theory calculations of these biosynthetic pathways. The results do not support previously proposed pathways/mechanisms: in particular, we find that none of the putative 2° carbocation intermediates is involved in either of the biosynthetic pathways. In verrucosane biosynthesis, the proposed 2° carbocations (II and IV) in the early stage are bypassed by the formation of the adjacent 3° carbocations and by unusual skeletal rearrangement reactions, and in the later stage, the putative 2° carbocation intermediates (VI, VII, and VIII) are not present as the proposed forms but as nonclassical structures between homoallyl and cyclopropylcarbinyl cations. In the mangicol biosynthesis, one of the two proposed 2° carbocations (X) is bypassed by a C-C bond-breaking reaction to generate a 3° carbocation with a C=C bond, while the other (XI) is bypassed by a strong hyperconjugative interaction leading to a nonclassical carbocation. We propose new biosynthetic pathways/mechanisms for the verrucosane-type diterpenoids and mangicol-type sesterterpenoids. These pathways are in good agreement with the findings of previous biosynthetic studies, including isotope-labeling experiments and byproducts analysis, and moreover can account for the biosynthesis of related terpenes.

AutoMeKin2021: An open-source program for automated reaction discovery

AutoMeKin2021 is an updated version of tsscds2018, a program for the automated discovery of reaction mechanisms (J. Comput. Chem. 2018, 39, 1922). This release features a number of new capabilities: rare-event molecular dynamics simulations to enhance reaction discovery, extension of the original search algorithm to study van der Waals complexes, use of chemical knowledge, a new search algorithm based on bond-order time series analysis, statistics of the chemical reaction networks, a web application to submit jobs, and other features. The source code, manual, installation instructions and the website link are available at: https://rxnkin.usc.es/index.php/AutoMeKin.

Thermoset resin curing simulation using quantum-chemical reaction path calculation and dissipative particle dynamics

Thermoset resin, which is commonly used as a matrix in carbon-fiber-reinforced plastic, requires curing procedures. We propose a curing simulation technique involving a dissipative particle dynamics (DPD) simulation, which can simulate a larger system and longer time period than those of conventional all-atom molecular dynamics (AA-MD) simulations. The proposed curing DPD simulation can represent the thermoset resin exothermic reaction process precisely by considering each reactivity according to the reaction types calculated via quantum-chemical reaction path calculations. The cure reaction process given by the curing DPD simulation agrees well with that given by a conventional curing AA-MD simulation, but with run-time and computational-resource reductions of 1/480 and 1/10 times, respectively. We also conduct reverse mapping, through which the AA-MD system can be reconstructed from the DPD system, to evaluate the structural and thermomechanical properties. The X-ray diffraction pattern and thermomechanical properties of the reconstructed system agree well with those of the systems derived from the curing AA-MD simulation and experimental setup. Therefore, a cured-resin AA-MD system can be obtained from a curing DPD simulation at an extremely low computational cost, and the thermomechanical properties can be evaluated precisely using this system. The proposed curing simulation technique can be applied in high-throughput screening for better materials properties and in large system calculations.

Simultaneously improving reaction coverage and computational cost in automated reaction prediction tasks

Automated reaction prediction has the potential to elucidate complex reaction networks for applications ranging from combustion to materials degradation, but computational cost and inconsistent reaction coverage are still obstacles to exploring deep reaction networks. Here we show that cost can be reduced and reaction coverage can be increased simultaneously by relatively straightforward modifications of the reaction enumeration, geometry initialization and transition state convergence algorithms that are common to many prediction methodologies. These components are implemented in the context of yet another reaction program (YARP), our reaction prediction package with which we report reaction discovery benchmarks for organic single-step reactions, thermal degradation of a γ-ketohydroperoxide, and competing ring-closures in a large organic molecule. Compared with recent benchmarks, YARP (re)discovers both established and unreported reaction pathways and products while simultaneously reducing the cost of reaction characterization by nearly 100-fold and increasing convergence of transition states. This combination of ultra-low cost and high reaction coverage creates opportunities to explore the reactivity of larger systems and more complex reaction networks for applications such as chemical degradation, where computational cost is a bottleneck.

High Temperature Accelerated Stone-Wales Transformation and the Threshold Temperature of IPR-C60 Formation

The Stone-Wales bond rotation isomerization of nonicosahedral C₆₀ (C_2v-C₆₀) into isolated-pentagon rule following icosahedral C₆₀ (I_h-C₆₀ or IPR-C₆₀) is a limiting step in the synthesis of I_h-C₆₀. However, extensive previous studies indicate that the potential energy barrier of the Stone-Wales bond rotation is between 6 and 8 eV, extremely high to allow for bond rotation at the temperatures used to produce fullerenes conventionally. This is also despite data indicating a possible fullerene road mechanism that necessitates low-temperature annealing. However, these previous investigations often have limiting factors, such as using the harmonic approximation to determine free energies at high temperatures or considering only the reverse I_h-C₆₀ to C_2v-C₆₀ transition as a basis. Indeed, when the difference in energy between I_h-C₆₀ and C_2v-C₆₀ is accounted for, this barrier is generally reduced by ∼1.5 eV. Thus, utilizing the recently developed density functional tight binding metadynamics (DFTB-MTD) interface, the effects of temperature on the bond rotation in the conversion of C_2v-C₆₀ to I_h-C₆₀ have been investigated. We found that Stone-Wales bond rotations are complex processes with both in-plane and out-of-plane transition states, and which transition path dominates depends on temperature. Our results clearly show that at temperatures of 2000 K, the free energy for a C_2v-C₆₀ to I_h-C₆₀ transition is only ∼4.21 eV and further reduces to ∼3.77 eV at 3000 K. This translates to transition times of ∼971 μs at 2000 K and ∼34 ns at 3000 K, indicating that defect healing is a fast process at temperatures typical of arc jet or laser ablation experiments. Conversely, below ∼2000 K, bond rotation becomes prohibitively slow, putting a lower threshold limit on the temperature of fullerene formation and subsequent annealing.

Application of Reaction Path Search Calculations to Potential Energy Surface Fits

There has been significant progress in recent years in the use of machine learning techniques to model high-dimensional reactive potential energy surfaces using large-scale data obtained from ab initio electronic structure calculations. In these methods, the strategy used to gather data becomes a key issue as the molecular size increases. In this work, we examine the applicability of the reaction path search algorithm implemented in the Global Reaction Route Mapping (GRRM) code as a data-gathering approach. The electronic energies and gradients sampled by using the GRRM calculation are directly used in potential energy surface fitting to a permutationally invariant polynomial function. This simple approach was applied to the HNS and HCNO reaction systems, and we found that the fitted potential energy surfaces reasonably reproduce the features of the electronic structure calculations used in the GRRM calculations. This suggests that the GRRM sampling scheme can be used to construct an initial potential energy surface.

Proton Transfer in Nitromethane-Ammonia Clusters under VUV Single-Photon Ionization Explored by Infrared Spectroscopy and Theoretical Calculations

It is known that the acidity and reactivity of the CH bond can be enhanced after ionization. Also, this property plays a pivotal role in proton transfer reaction and in the formation of new molecules. Herein, infrared spectroscopy and high-precision quantum chemical calculations are used to study the neutral and cationic clusters of nitromethane-ammonia (CH₃NO₂-NH₃). It is found that in the neutral cluster, CH₃NO₂ and NH₃ are mainly bonded by three intermolecular hydrogen bonds, in which electrostatic contribution plays a major role. After vacuum ultraviolet (VUV) single-photon ionization of CH₃NO₂-NH₃, the positive charge redistributes from the ionized nitrogen atom of NH₃ to the CH₃NO₂ molecule immediately. Then, the proton of CH₃NO₂ transfers to NH₃ to form a proton-transferred type structure CH₂NO₂-NH₄⁺, without any effective energy barrier, due to the positive hyperconjugation of cationic nitromethane. A closed loop of positive charge transfer takes place in the CH₃NO₂-NH₃ cluster after VUV ionization. The present work demonstrates that both the proton transfer reaction and charge transfer process have occurred in the ionized CH₃NO₂-NH₃ cluster. Moreover, it is found that the proton transfer reaction is a result of the highly acidic CH bond caused by hyperconjugation between the σ (CH) bond and π orbital.

Spectroscopic evidence of the C-N covalent bond formed between two interstellar molecules (ISM): acrylonitrile and ammonia

Acrylonitrile (AN) and ammonia (NH3) are two important nitrogen-containing interstellar molecules in outer space, especially on Titan. Herein, we measured infrared (IR) spectra of neutral and cationic AN-NH3 complexes by VUV single-photon ionization combined with time-of-flight mass spectrometry. On combining IR spectra with the theoretical calculations, we found that the molecules prefer to form a single-ring cyclic H-bonded structure in the neutral AN-NH3 and (AN)2-NH3 clusters. However, after ionization of AN-NH3 and (AN)2-NH3 clusters, a new C-N-covalent bond is confirmed to form directly between AN and NH3, without any energy barrier in the cationic complexes. Moreover, in the ionized (AN)2-NH3 cluster, the covalent C-N bond prefers to form between AN and NH3 rather than the two AN groups. These results provide spectroscopic evidence of AN forming a new molecule with NH3, induced by VUV radiation. The formation of the new C-N bond broadens our knowledge on the evolution of the prebiotic nitrogen-containing molecules in space.

Organic reactivity from mechanism to machine learning

As more data are introduced in the building of models of chemical reactivity, the mechanistic component can be reduced until 'big data' applications are reached. These methods no longer depend on underlying mechanistic hypotheses, potentially learning them implicitly through extensive data training. Reactivity models often focus on reaction barriers, but can also be trained to directly predict lab-relevant properties, such as yields or conditions. Calculations with a quantum-mechanical component are still preferred for quantitative predictions of reactivity. Although big data applications tend to be more qualitative, they have the advantage to be broadly applied to different kinds of reactions. There is a continuum of methods in between these extremes, such as methods that use quantum-derived data or descriptors in machine learning models. Here, we present an overview of the recent machine learning applications in the field of chemical reactivity from a mechanistic perspective. Starting with a summary of how reactivity questions are addressed by quantum-mechanical methods, we discuss methods that augment or replace quantum-based modelling with faster alternatives relying on machine learning.

High performance global exploration of isomers and isomerization channels on quantum chemical potential energy surface of H5 C2 NO2

High performance global exploration of isomers and isomerization channels on the quantum chemical potential energy surface (PES) is performed for H₅ C₂ NO₂ by using the scaled hypersphere search-anharmonic downward distortion following (SHS-ADDF) method. A multi-node operation, NeoGRRM, has achieved high performance exploration calculations for the large system by submitting SHS-ADDF sub-jobs into many cores in parallel and unifying the results of sub-jobs into the total lists of the main-job. Global exploration of equilibrium (EQ) and transition-state structures at the level of B3LYP/6-31G(d) gave 3210 EQs and 23278 TSs. Nine compounds were found in the low energy regions of 0-100 kJ/mol; the lowest energy compound is N-methylcarbamic acid, the second is methyl carbamate, and the third is glycine (the most fundamental amino acid). Interconversion pathways between the conformers of each of the low energy compounds were surveyed. Isomerization channels around glycine were explored in detail. The lowest energy barriers around some of the EQs turned to be negative after zero-point energy corrections. This indicates that those structures cannot exist as independent structures because they spontaneously collapse into more stable structures. The global PES search showed various interesting dissociating channels which indicate synthon reaction pathways in the reverse directions.

Geometric analysis of anharmonic downward distortion following paths

A mathematical aspect of the anharmonic downward distortion following (ADDF) path is discussed. The ADDF method is utilized as an automated reaction path search method, which can explore transition state geometries on a potential energy surface from a potential minimum. We show that the maximum number of the ADD stationary paths intersecting the potential minimum is 2^f + 1  - 2, where f denotes the degree of freedom of the system. We also show that the bifurcation of the ADD stationary path is essential to detect all the transition states connected from a given minimum. The ADDF computation is demonstrated for a H₂ O molecule in which pitchfork bifurcation is observed.