Transition State Search Research Articles

Stereocontrolled Synthesis of C20S-C26 and C20R-C26 Fragments of Amphidinolide L.

Amphidinolide L is a cytotoxic macrolide isolated from marine symbiotic dinoflagellates of the genus Amphidinium. While its planar structure and the absolute stereochemistry of the C21-C26 part have been determined, six stereocenters have remained unassigned. Aiming at structure determination, we have developed a synthetic route to the C20S-C26 and C20R-C26 fragments via the Li-mediated stereocontrolled aldol reaction. Two aldehydes, 16 with the C22-hydroxy group and 19 with the C22-TES ether, were synthesized from lactone 4. The aldol reactions using the Li-enolate of 4-methyl-2-pentanone in THF provided the C20S-C26 fragment 20 from 16 and a 1:3.5 mixture of the C20-C26 fragment 22 favoring the C20R-isomer. Mechanistic studies based on an extensive search of transition states in explicit solvents indicated that the C20S-isomer would be generated via a tri-solvated transition state, while the C20R-isomer would be formed via a di-solvated transition state. The calculation emphasizes the importance of the coordination network as a higher-order complex composed of solvent molecules, aldehyde, enolate, and Li atoms in the reaction of 16 to minimize steric interactions but maximize the stabilizing effect by the coordination of solvents. The presence of the rotationally free aldehyde in the reaction of 19 results in moderate diastereoselectivity.

Automated input structure generation for single-ended reaction path optimizations.

The exploration of a reaction network requires highly automated workflows to avoid error-prone and time-consuming manual steps. In this respect, a major bottleneck is the search for transition-state (TS) structures, which frequently fails and, therefore, makes (manual) revision necessary. In this work, we present a technique for obtaining suitable input structures for automated TS searches based on single-ended reaction path optimization algorithms, which makes subsequent TS searches via this method significantly more robust. First, possible input structures are generated based on the spatial alignment of the reactants. The appropriate orientation of reacting groups is achieved via stepwise rotations along selected torsional degrees of freedom. Second, a ranking of the obtained structures is performed according to selected geometric criteria. The main goals are to properly align the reactive atoms, to avoid hindrance within the reaction channel and to resolve steric clashes between the reactants. The developed procedure has been carefully tested on a variety of examples and provides suitable input structures for TS searches within seconds. The method is in daily use in an industrial setting.

Supplementary Information of Geometry Relaxation and Transition State Search with Quantum Machine Learning

Supplementary Information of Geometry Relaxation and Transition State Search with Quantum Machine Learning

Cover Feature: Unravelling Charge Carrier Mobility in d0‐Metal‐based Spinels (Batteries & Supercaps 7/2022)

The Cover Feature illustrates properties of the potential energy surface for charge carriers in spinel solid electrolyte and electrode materials that yield a descriptor for the ion mobility. The descriptor is based on the energetic difference between the two symmetrically different intercalation sites in these materials. This allows to predict the height of the minimum migration barrier without the need to perform numerically costly transition state searches. At the same time, it improves our understanding of ion mobility which is a critical performance parameter of batteries. More information can be found in the Research Article by H. Euchner and co-workers.

Machine Learning Screening of Efficient Ionic Liquids for Targeted Cleavage of the β-O-4 Bond of Lignin.

Lignin conversion into high value-added chemicals is of great significance for maximizing the use of renewable energy. Ionic liquids (ILs) have been widely used for targeted cleavage of the C-O bonds of lignin due to their high catalytic activity. Studying the cleavage activity of each IL is impossible and time-consuming, given the huge number of cations and anions. Currently, the mainstream approach to determining the cleavage activity of one IL is to calculate the activation barrier energy (Ea) theoretically via transition state search, a process that involves the iterative determination of an appropriate "imaginary frequency". Machine learning (ML) has been widely used for catalyst design and screening, enabling accurate mapping from specified descriptors to target properties. To avoid complicated Ea calculations and to screen potential candidates, in this study, we selected nearly 103 ILs and guaiacylglycerol-β-guaiacyl ether (GG) as the lignin model and used the ML technology to train models that can rapidly predict the cleavage activity of ILs. Taking the easily accessible bond dissociation energy (BDE) of the β-O-4 bond in GG as the target, an ML model with r > 0.93 for predicting the catalytic activity of ILs was obtained. The change tendency of the BDE is consistent with the experimental yield of guaiacol, reflecting the reliability of the ML model. Finally, [C2MIM][Tyrosine] and [C3MIM][Tyrosine] as the optimal candidates for future applications were screened out. This is a novel strategy for predicting the catalytic activity of ILs on lignin without the need to calculate complicated reaction pathways while reducing time consumption. It is anticipated that the ML model can be utilized in future practical applications for targeted cleavage of lignin.

Automated reaction mechanisms and kinetics with the nudged elastic band method-based AMK_Mountain and its description of the preliminary alkaline hydrolysis of nitrocellulose monomer.

To improve the transition state (TS) search capability in complex chemical environments, AMK_Mountain is constructed based on the automated reaction mechanisms and kinetics (AutoMeKin) package. AMK_Mountain does not distinguish the reaction type of the TSs, which is beneficial to obtaining a more comprehensive reaction mechanism. In this study, the first step of the alkaline hydrolysis process of nitrocellulose monomer was adopted as the research object, and 730 possible initial configurations are constructed and 22 TSs pass high-level calculations. Energy difference and interaction region indicator reveal that the first step of alkaline hydrolysis is mainly the combination of nitrogen-containing functional groups at the positions α and β with hydroxide anions, followed by the formation of nitric acid and the further loss of protons to form nitrate. Overall, in combination with GFN2 -xTB and ORCA, the AMK_Mountain technique provides a reliable method for the location of the TSs in complex environments.

Conformational Sampling for Transition State Searches on a Computational Budget.

Transition state searches are the basis for computationally characterizing reaction mechanisms, making them a pivotal tool in myriad chemical applications. Nevertheless, common search algorithms are sensitive to reaction conformations, and the conformational spaces of even medium-sized reacting systems are too complex to explore with brute force. Here, we show that it is possible to train a classifier to learn the features of reaction conformers that conduce successful transition state searches, such that optimal conformers can be down-selected before incurring the cost of a high-level transition state search. The efficacy and transferability of this approach were tested using four distinct benchmarks comprising over three hundred individual reactions. Neglecting conformer contributions led to qualitatively incorrect activation energy estimations for a broad range of reactions, whereas simple random forest classifiers reliably down-selected low-barrier reaction conformers for unseen reactions. The robust performance of these machine learning classifiers mitigates cost as a factor when implementing conformational sampling into contemporary reaction prediction workflows and opens up many avenues for further improvements as transition state data grow.

Experimental and theoretical study on N-hydroxyphthalimide and its derivatives catalyzed aerobic oxidation of cyclohexylbenzene

The liquid phase oxidation of cyclohexylbenzene (CHB) is a new green synthetic approach to cyclohexylbenzene-1-hydroperoxide (CHBHP), a key intermediate for preparing phenol and cyclohexanone. In this work, aryl-substituted (Cl and Br) derivatives of N-hydroxyphthalimide (NHPI) were synthesized and their catalytic performances for CHB oxidation were studied. In addition, geometric optimization and transition state search were performed using DFT calculations. Both experimental and theoretical studies have proven that chloro-substitution on NHPI can significantly improve its catalytic effects on the oxidation of CHB by oxygen. Compared with NHPI, CHB conversion and selectivity of CHBHP over Cl4NHPI were increased by 10.47% and 13.24%. The strategy of aryl -substituting NHPI with halogen atoms proposed in this study would provide a potential way to the development of new NHPI-based catalysts for aerobic oxidation reactions.

Investigation of Oxygen Reduction Reaction of Graphene Supported Metal-N4 Catalysts via Density Functional Theory

The high-dense metal-air batteries are difficult to commercialize on a large scale mainly because of sluggish kinetics of air electrode. The catalysts are of crucial importance for the rate of oxygen reduction reaction (ORR), among which Pt-based catalysts for ORR have shortcomings in stability and cost, and the kind of catalysts with adding C and N to transition metals receive more attention. Here we analyze catalytic performance of graphene supported transition metals-N4(M-N4@G) for ORR based on density functional theory (DFT), verifying rationality of such catalysts with five different transition metals (Pt, Fe, Co, Pd and Ni) embedded in the graphene, and demonstrating that Fe-N4@G has better ORR performance than Pt-N4@G. Moreover, a proposed mechanism of ORR (generating free *O and *OH) is explored to optimize ORR by means of transition-state search in the DFT calculation. Additionally, a novel phenomenon is observed that graphene has a strong attraction to hydrogen atoms, which is facilitated to promote hydrogen evolution reaction of graphene supported catalysts.

Theoretical insights into the oxidation of elemental mercury by O2 on graphene-based Pt single-atom catalysts

Pt single-atom catalysts (SACs) exhibit good performance for oxygen activation, which plays a significant role in the oxidation of Hg0 by O2 in flue gas. Density functional theory calculations are carried out to reveal the interfacial behavior of Hg0, O2 and HgO on Pt SACs (single vacancy and 3 N doped defected graphene, Pt/SV-GN and Pt/3N-GN) and the mechanism of Hg0 oxidation by O2. The results show that the flue gas components are chemically adsorbed and bond with the Pt of the Pt SACs with adsorption energies ranging from −0.555 to −5.154 eV. Electronic structure analysis indicates that Hg0 is an electron donor and transfers 0.114–0.128 e− to the Pt SACs. Both O2 and HgO are electron acceptors and obtain 0.184–0.303 e− from the slabs. Pt/3N-GN has a higher activity than that of Pt/SV-GN for these three flue gas compositions. The significant charge transfer and orbital hybridization between the gas molecules and atomic catalysts lead to a strong interaction. Furthermore, the Pt-3C and Pt-3N states can increase the band gap compared with pristine graphene, corresponding to 0.195 and 0.129 eV, respectively. Narrow band gaps indicate easier electron excitation properties, which enhance the activity of the reaction. Through a transition states (TSs) search, the lower O2 dissociation barrier is found to correspond to the lower Hg0 oxidation barrier. Pt/3N-GN has higher catalytic oxidation performance for Hg0 in the presence of O2, with a rate determining reaction barrier of 2.016 eV. Compared to traditional selective catalytic reduction and Fe-based SACs, the Pt/3N-GN catalyst has a good oxidation reaction capability with a lower activation energy, indicating that it is a promising catalyst for the oxidation of Hg0 by O2.

Search for transition states with external forces.

It is much more difficult to find on the potential energy surface (PES) a transition state (TS) than a local minimum (LM). We propose a new methodology which makes this task much easier. Applying external forces to nuclei in a molecule we can locate on PES not just one particular TS but a number of consecutive transition states. With our approach it is possible to move over PES from one transition state to another without involving any local minima. The latter can be located in a separate step through the reaction path calculations performed for every transition state found before. Preliminary results for the 2-fluorofuran molecule illustrate the usefulness of the proposed method.

Automatic Approach to Explore the Multireaction Mechanism for Medium-Sized Bimolecular Reactions via Collision Dynamics Simulations and Transition State Searches

We develop a broadly applicable computational method for the automatic exploration of the bimolecular multireaction mechanism. The current methodology mainly involves the high-energy Born-Oppenheimer molecular dynamics (BOMD) simulation and the successive reaction pathway construction. Several computational tricks are introduced, which include the selection of the reactive regions based on the electronic structure calculations and the employment of the virtual collision dynamics simulations with the monitoring of the atomic distance before the BOMD simulation. These prescreening steps largely reduce the number of trajectories in the BOMD simulations and significantly save the computational cost. The hidden Markov model combined with the modified atomic connectivity matrix is used for the detection of reaction events in each BOMD trajectory. Starting from several geometries close to the reaction events, the further intermediate optimization and transition state searches are conducted. The proposed method allows us to build the complicated multireaction mechanism of medium-sized bimolecular systems automatically. Here, we examine the feasibility and efficiency of the current method by its performance in searching the mechanisms of two prototype reactions in environmental science, which are the penicillin G anion + H2O and penicillin G anion + OH radical reactions. The result indicates that the proposed theoretical method is a powerful protocol for the automatic search of the bimolecular reaction mechanisms for medium-sized compounds.

Study on the Growth Mechanism of Chlorocarbon Radicals on the Surface of CVD Diamond (100)

In the CH3Cl/H2 atmosphere, the adsorption process of various active chlorocarbon groups (CH2Cl, CHCl, CCl) and CH3 on the surface of clean diamond used density functional theory (DFT) calculations during CVD process. The reaction heat and activation energy of the active sites on the adsorption reconstituted surface of D-CH3 and D-CH2Cl were calculated by transition state search to explore the actual effect of the carbon chloride active group on the surface of CVD diamond (100).The results showed that the adsorption capacity of CHCl, CH2Cl and CCl on the substrate was gradually weakened and the adsorption energy of CH2Cl and CH3 was close. Both CHCl and CH2Cl could form diamond bonds with the substrate carbon atoms to directly promote the growth of the diamond coating. Since the C-Cl bond was weaker than the C-H bond, the adsorption recombination surface of CH2Cl generated an energy barrier of the active site lower than the adsorption reconstitution surface of CH3. Therefore, using CH3Cl/H2 as a gas source could effectively reduce the energy required for diamond coating growth.

Finding Key Factors for Efficient Water and Methanol Activation at Metals, Oxides, MXenes, and Metal/Oxide Interfaces.

Activating water and methanol is crucial in numerous catalytic, electrocatalytic, and photocatalytic reactions. Despite extensive research, the optimal active sites for water/methanol activation are yet to be unequivocally elucidated. Here, we combine transition-state searches and electronic charge analyses on various structurally different materials to identify two features of favorable O–H bond cleavage in H2O, CH3OH, and hydroxyl: (1) low barriers appear when the charge of H moieties remains approximately constant during the dissociation process, as observed on metal oxides, MXenes, and metal/oxide interfaces. Such favorable kinetics is closely related to adsorbate/substrate hydrogen bonding and is enhanced by nearly linear O–H–O angles and short O–H distances. (2) Fast dissociation is observed when the rotation of O–H bonds is facile, which is favored by weak adsorbate binding and effective orbital overlap. Interestingly, we find that the two features are energetically proportional. Finally, we find conspicuous differences between H2O/CH3OH and OH activation, which hints toward the use of carefully engineered interfaces.

Strengthening mechanism of Al/Sn interfaces: Study from experiments and first-principles calculation

The joining of aluminum using a metal of pure Sn as an interlayer or solder was investigated by reactive air soldering and vacuum diffusion bonding. The interfacial structure and mechanical property of the joints were examined. A nanometer-scale interlayer of amorphous Al2O3 dotted with nanocrystalline γ-Al2O3 was observed and identified at the Al/Sn interface by reactive air soldering. The shear strength of the joints (∼40 MPa) by reactive air soldering was higher than that (∼20 MPa) by vacuum diffusion bonding. The reaction and diffusion behaviors of oxygen dopants at the Al/Sn interface were studied through geometry optimization and a transition state search, respectively. The work of separation values of these two interfaces between Al/O-terminated or Sn/O-terminated was 6.46 and 2.83 J/m2, respectively, which were both larger than that of a Al/Sn interface (1.06 J/m2). The results indicated that oxygen atoms could strengthen the interfacial adhesion of Al/Sn. In addition, the interfacial reaction of Al and O and the formation process of Al2O3 were discussed. It has the potential to be used to realize a high-strength joint in other weak bonding systems such as solder/ceramics, through O doping in air.

Empathes: A general code for nudged elastic band transition states search

An easy and flexible interface, Empathes (Extensible Minimum PATH EStimator), that allows to perform Nudged Elastic Band calculation for the determination of transition states is presented. The code is designed to be easily modified, in order to be associated with the user's preferred calculation software, even with those which implement composite approaches. In particular, the interfaces to Gaussian and Siesta programs are discussed in details, being the former only used for testing purpose, while the latter can be productively employed for transition states search with that commonly used density functional theory software for periodic calculations. Program summaryProgram Title:EmpathesCPC Library link to program files:https://doi.org/10.17632/v525mwf3cc.1Developer's repository link:https://github.com/marberti/empathesCode Ocean capsule:https://codeocean.com/capsule/2394233Licensing provisions: GPLv3Programming language: Fortran 08Nature of problem: The search for the structure of transition states through computational methods, essentially based on Density Functional Theory, is of overwhelming importance for the determination of the elementary steps forming a reaction mechanism. Allowing to develop basic knowledge, these investigations can be used to direct experimentalists towards a more efficient realization of chemical compounds synthetic processes. In cases where it is necessary to describe the reactive system through periodic calculations, which is very common in heterogeneous catalysis, this research must be done through the use of non-analytical methods.Solution method: In case of lacking of analytical procedures, the search for the transition states associated with the elementary stages that make up chemical reactions must take place through numerical methods. The Nudged Elastic Band (NEB) approach is, together with its variants, one of the most used for this purpose. In accordance with the NEB algorithm, a chain of geometric structures, generated by interpolating between the reactant and product geometries and joined by fictitious springs, is relaxed on the minimum energy path, allowing the association of the transition state to the maximum along this path. The NEB method involves the determination of molecular energies and forces acting on the nuclei of the system, which is generally carried out through a program for electronic structure calculation. The present code is a useful general interface.

DFT transition state study of the catalyzed oxidation of methane on SnO2 surfaces

Along this research the (110), (101) (200) and (211) surfaces were chosen to be studied by considering their atomic surface density. The surfaces were studied using CASTEP for the transition state search by DFT calculations, the initial coordinates that establish the SnO2-Methane distance were obtained with Adsorption Locator, a software able to calculate adsorption configurations using Monte Carlo methods. The results show that in terms of overall energy change, surface (101) presents the most favorable configuration with an exothermic total-energy change (form CH4 on the surface to a CO and H2O molecules on the surface) of − 18.47 kcal/mol, being the worst case the CH4 on a (200) surface with an endothermic total energy-change of 128.86 kcal/mol. In terms of the TS energy, the (101) surface remains as the most favorable system with energy maximums on the TS reaction path of 99.25 kcal/mol for the dissociation and adsorption of the CH4 molecule on the surface, and a maximum of 266.42 kcal/mol for the desorption and formation of the CH4 and H2O molecules on the SnO2 surface.

Generative adversarial networks for transition state geometry prediction.

This work introduces a novel application of generative adversarial networks (GANs) for the prediction of starting geometries in transition state (TS) searches based on the geometries of reactants and products. The multi-dimensional potential energy space of a chemical reaction often complicates the location of a starting TS geometry, leading to the correct TS combining reactants and products in question. The proposed TS-GAN efficiently maps the space between reactants and products and generates reliable TS guess geometries, and it can be easily combined with any quantum chemical software package performing geometry optimizations. The TS-GAN was trained and applied to generate TS guess structures for typical chemical reactions, such as hydrogen migration, isomerization, and transition metal-catalyzed reactions. The performance of the TS-GAN was directly compared to that of classical approaches, proving its high accuracy and efficiency. The current TS-GAN can be extended to any dataset that contains sufficient chemical reactions for training. The software is freely available for training, experimentation, and prediction at https://github.com/ekraka/TS-GAN.

Structural Origins of Voltage Hysteresis in the Na-Ion Cathode P2-Na0.67[Mg0.28Mn0.72]O2: A Combined Spectroscopic and Density Functional Theory Study.

P2-layered sodium-ion battery (NIB) cathodes are a promising class of Na-ion electrode materials with high Na+ mobility and relatively high capacities. In this work, we report the structural changes that take place in P2–Na0.67[Mg0.28Mn0.72]O2. Using ex situ X-ray diffraction, Mn K-edge extended X-ray absorption fine structure, and 23Na NMR spectroscopy, we identify the bulk phase changes along the first electrochemical charge–discharge cycle—including the formation of a high-voltage “Z phase”, an intergrowth of the OP4 and O2 phases. Our ab initio transition state searches reveal that reversible Mg2+ migration in the Z phase is both kinetically and thermodynamically favorable at high voltages. We propose that Mg2+ migration is a significant contributor to the observed voltage hysteresis in Na0.67[Mg0.28Mn0.72]O2 and identify qualitative changes in the Na+ ion mobility.

Two-dimensional vermiculite carried CuCoCe catalysts for CO-SCR in the presence of O2 and H2O: Experimental and DFT calculation

Two-dimensional (2D) materials have attracted tremendous attention as denitration catalysts for the selective catalytic reduction (SCR) reaction. Here, we prepare two-dimensional (2D) vermiculite (VMT)-supported copper–cobalt–cerium catalyst (CuCoCe/2D-VMT) by the impregnation method and employed it for the CO-SCR reaction. The NO conversion utilizing CuCoCe/2D-VMT achieves 100% at 300°C with a GHSV of 102,000 h−1in the presence of 1 vol% O2 and 5 vol% H2O. CuCoCe/2D-VMT promotes the dispersion of the active metal-site species and boosts the reduction temperature, reduces the particle size gradually. Additionally, the in situ DRIFTS spectrum reflects the existence of Cu+−CO, νas (CO32−), νs (NO3−), (NO)2, νas (–OH), νas (COO–), and δ (HCO3−) intermediates on the CuCoCe/2D-VMT surface, it supports the following mechanism study. Further, in the DFT calculation, the transition state search and potential energy analysis, CuCoCe/2D-VMT possesses lower activation energy and higher energy gain compared with CuCo/2D-VMT in each potential reaction pathway. Largely, combined with in-situ DRIFTS and the transition-state analysis, the elementary reactions of CuCoCe/2D-VMT in the SCR pathways are proposed under the following harsh conditions: CO + NO + O2 + H2O. The elementary reactions mainly includes the generation of Ov, the NO + NO process, the reaction pathways of CO reacts with *O, *OH, *H (H2O) and Ov is refilled by gaseous O2. We expect this strategy to promote the development and utilization of CO-SCR catalysts and reveal a new inexpensive and highly efficient method for practical applications.