論文

Conventional molecular geometry searches on a potential energy surface (PES) utilize energy gradients from quantum chemical calculations. However, replacing energy calculations with noisy quantum computer measurements generates errors in the energies, which makes geometry optimization using the energy gradient difficult. One gradient-free optimization method that can potentially solve this problem is Bayesian optimization (BO). To use BO in geometry search, an acquisition function (AF), which involves an objective variable, must be defined suitably. In this study, we propose a strategy for geometry searches using BO and examine the appropriate AFs to explore two critical structures: the global minimum (GM) on the singlet ground state (S0) and the most stable conical intersection (CI) point between S0 and the singlet excited state. We applied our strategy to two molecules and located the GM and the most stable CI geometries with high accuracy for both molecules. We also succeeded in the geometry searches even when artificial random noises were added to the energies to simulate geometry optimization using noisy quantum computer measurements.

The exploration of minimum energy crossing points (MEXs) between potential energy surfaces (PESs) is essential for understanding nonradiative decay mechanisms and plays a key role in the design of photofunctional materials. In lanthanide (Ln3+) complexes, however, the presence of open-shell 4fN electrons leads to quasi-degenerate electronic states, making MEX searches particularly challenging. To describe the PESs of 4f-5d or charge-transfer excited states (i.e., 4fN−1X excited states) of Ln3+ complexes, we propose a new approximation, the ion energy shift (IES) method. In this approach, the 4fN−1X excited state is represented using density functional theory (DFT) with the large-core relativistic effective core potential (RECP) for Ln4+, which has a higher formal charge than the actual ion (Ln3+), and the PES is shifted to reproduce the target excitation energy. In this study, we validate the IES method against the multiconfigurational wavefunction results and apply it to elucidate the origin of the different excited-state lifetimes of hydrated Ce3+ complexes with and without coordination of a carboxylate ligand.

Proton-coupled electron transfer (PCET) and hydrogen atom transfer (HAT) reactions of the phenoxyl/phenol couple are studied theoretically by using wave function theory (WFT) as well as DFT methods. At the complete active space self-consistent field (CASSCF) level, geometry optimization is found to give two transition states (TSs); one is the PCET type with two benzene rings being nearly coplanar, and the other is the HAT type with two benzene rings taking a stacking structure. Geometry optimization at the (semilocal) DFT level, on the other hand, is found to give only one transition state (i.e., the PCET-type one) and fail to obtain the stacking TS structure. By comparing various levels of theories (including long-range corrected DFT functionals), we demonstrate that the Hartree-Fock exchange at long range plays a critical role in obtaining the sufficient stacking stabilization of the present open-shell system, and that the sole addition of empirical dispersion correction to semilocal DFT functionals may not be adequate for describing such a stacking interaction. Next, we investigate the solvent effect on the PCET and HAT TS thus obtained using the reference interaction site model self-consistent field (RISM-SCF) method. The results suggest that the free energy barrier increases with increasing polarity of the solvent, and that the solvent effects are stronger for the PCET TS than the stacking HAT TS pathway. The reason for this is discussed based on the dipole moment of different TS structures in solution.

In biomembranes a variety of antioxidants work to suppress oxidative damage. Vitamin E and ubiquinol are among the most important lipid-soluble antioxidants, which trap lipid peroxyl radicals directly or work cooperatively in the regeneration of vitamin E radicals by ubiquinol. Here, we investigate the latter regeneration reaction by using variational transition-state theory with multidimensional tunneling corrections. The result shows that the system forms a compact H-bonded complex by significantly rearranging the donor and acceptor moieties, which leads to a rather narrow potential barrier for H transfer and a very large tunneling effect with a transmission coefficient >4000. In accord with experiment, the Arrhenius activation energy is found to be very small (∼1 kcal/mol), which is interpreted here in terms of mean tunneling energy through the barrier. Regarding the electronic structure, we demonstrate that the present reaction proceeds via a proton-coupled electron transfer (PCET) mechanism and suggest that the PCET character also contributes to the large tunneling effect by sharpening the potential barrier. Finally, a systematic comparison is made among relevant reactions and it is indicated that the antioxidant defense of biomembranes may benefit rather significantly from quantum tunneling to enhance the reaction efficiency.

We propose a method for computing a melting point on the basis of the Gibbs free energy difference between the solid and liquid phases. The free energy difference is calculated from the average pressure obtained by performing a standard NVT simulation with a solid-liquid two-phase configuration. The method is validated by the melting point calculations of argon and benzene systems. In addition, the method is applied to a mannitol system, and the more reliable melting point than the previous estimate is successfully predicted. These results demonstrate that this method is very simple and useful to calculate melting points.

Despite strong electrostatic repulsion, like-charged ions in aqueous solution can effectively attract each other via ion–water interactions. In this paper we investigate such an effective interaction of like-charged ions in water by using the 3D-RISM-SCF method (i.e., electronic structure theory combined with three-dimensional integral equation theory for molecular solvents). Free energy profiles are calculated at the CCSD(T) level for a series of molecular ions including guanidinium (Gdm+), alkyl-substituted ammonium, and aromatic amine cations. Polarizable continuum model (PCM) and mean-field QM/MM free energy calculations are also performed for comparison. The results show that the stability of like-charged ion pairs in aqueous solution is determined by a very subtle balance between interionic interactions (including dispersion and π-stacking interactions) and ionic solvation/hydrophobic effects and that the Gdm+ ion has a rather favorable character for like-charge association among all the cations studied. Furthermore, we investigate the like-charge pairing in Arg-Ala-Arg and Lys-Ala-Lys tripeptides in water and show that the Arg-Arg pair has a contact free-energy minimum of about −6 kcal/mol. This result indicates that arginine pairing observed on protein surfaces and interfaces is stabilized considerably by solvation effects.

Sugar alcohols are one promising candidate for phase-change materials (PCMs) in energy industrial societies because of their large thermal storage capacity. In this paper, we investigate the melting point and enthalpy of fusion related to the thermal storage of six-carbon sugar alcohols (galactitol, mannitol, sorbitol, and iditol) by molecular dynamics simulations and elucidate physical principles required for new PCM design. The computational melting points and enthalpies of fusion reproduce the experimental trend qualitatively. On the basis of the energy decomposition analysis we find that their enthalpies of fusion originate mainly from the decrease in the number and strength of intermolecular hydrogen bonds upon melting. Furthermore, we examine the origin of the difference of enthalpy of fusion between the four isomers. The results show that the larger enthalpy of fusion of galactitol and mannitol comes from their stable solid phases associated with the absence of notable repulsive electrostatic interaction between oxygen atoms in the molecule. In accordance with these results and an additional statistical survey, we propose the 3-fold guideline for developing new sugar alcohol like PCMs with larger thermal storage: (1) linear elongation of a carbon backbone, (2) separated distribution of OH groups, and (3) even numbers of carbon atoms.

Thermal storage, a technology that enables us to control thermal energy, makes it possible to reuse a huge amount of waste heat, and materials with the ability to treat larger thermal energy are in high demand for energy-saving societies. Sugar alcohols are now one promising candidate for phase change materials (PCMs) because of their large thermal storage density. In this study, we computationally design experimentally unknown non-natural sugar alcohols and predict their thermal storage density as a basic step toward the development of new high performance PCMs. The non-natural sugar alcohol molecules are constructed in silico in accordance with the previously suggested molecular design guidelines: linear elongation of a carbon backbone, separated distribution of OH groups, and even numbers of carbon atoms. Their crystal structures are then predicted using the random search method and first-principles calculations. Our molecular simulation results clearly demonstrate that the non-natural sugar alcohols have potential ability to have thermal storage density up to ∼450–500 kJ/kg, which is significantly larger than the maximum thermal storage density of the present known organic PCMs (∼350 kJ/kg). This computational study suggests that, even in the case of H-bonded molecular crystals where the electrostatic energy contributes mainly to thermal storage density, the molecular distortion and van der Waals energies are also important factors to increase thermal storage density. In addition, the comparison between the three eight-carbon non-natural sugar alcohol isomers indicates that the selection of preferable isomers is also essential for large thermal storage density.

Potential of zero charge (PZC) is essential in electrochemistry to understand physical and chemical phenomena at the interface between an electrode and a solution. A negative potential shift from the work function to the PZC has been experimentally observed in a metal/ionic liquid (IL) system, but the mechanism remains unclear and controversial. In this paper we provide valuable insight into the mechanism on the potential shift in the Au/IL (1-butyl-3-methylimidazolium bis(trifluoromethanesulfonyl)amide: [BMIM][TFSA]) system using a computational approach combining classical molecular dynamics simulations and first-principles calculations. By separately estimating some contributions to the potential shift, the shift is calculated in an easy-to-understand manner. The resultant PZC is shown to be in good agreement with the experimental one. Among the contributions, the electron redistribution at the Au/IL interface is found to provide the largest negative potential change. This indicates that the redistribution plays a crucial role in determining the potential shift of the Au electrode immersed in the IL. Detailed analyses suggest that the redistribution corresponds to the electron transfer not only from the anionic TFSA but also from the cationic BMIM molecules to the Au electrode surface. This unique observation is understood to originate from the interfacial structure where the IL molecules are in very close proximity to the electrode surface via dispersion interaction.

Computational models including electrode polarization can be essential to study electrode/electrolyte interfacial phenomena more realistically. We present here a constant-potential classical molecular dynamics simulation method based on the extended Lagrangian formulation where the fluctuating electrode atomic charges are treated as independent dynamical variables. The method is applied to a graphite/ionic liquid system for the validation and the interfacial kinetics study. While the correct adiabatic dynamics is achieved with a sufficiently small fictitious mass of charge, static properties have been shown to be almost insensitive to the fictitious mass. As for the kinetics study, electrical double layer (EDL) relaxation and ion desorption from the electrode surface are considered. We found that the polarization slows EDL relaxation greatly whereas it has little impact on the ion desorption kinetics. The findings suggest that the polarization is essential to estimate the kinetics in nonequilibrium processes, not in equilibrium.

Aqueous electrolytes have the potential to overcome some of the safety issues associated with current Li-ion batteries intended for large-scale applications such as stationary use. We recently discovered a lithium-salt dihydrate melt, viz., Li(TFSI)0.7(BETI)0.3·2H2O, which can provide a wide potential window of over 3 V; however, its reductive stability strongly depends on the electrode material. To understand the underlying mechanism, the interfacial structures on several electrodes (C, Al, and Pt) were investigated by conducting molecular dynamics simulation under the constraint of the electrode potential. The results showed that the high adsorption force on the surface of the metal electrodes is responsible for the increased water density, thus degrading the reductive stability of the electrolyte. Notably, the anion orientation on Pt at a low potential is unfavorable for the formation of a stable anion-derived solid electrolyte interphase, thus promoting hydrogen evolution. Hence, the interfacial structures that depend on the material and potential of the electrode mainly determine the reductive stability of hydrate-melt electrolytes.

Hybrid methods that combine molecular dynamics methods capable of analyzing dynamics with Monte Carlo (MC) methods that can efficiently treat thermodynamically stable states are valuable for understanding complex chemical processes in which an equilibrium state is reached through many elementary processes. The hybrid MC (HMC) method is one such promising method; however, it often fails to sample configurations properly from the canonical multimodal distribution due to the rugged potential energy surfaces. In this paper, we extend the HMC method to overcome this difficulty. The new method, which is termed potential scaling HMC (PS-HMC), makes use of an artificially modulated trajectory to propose a new configuration. The trajectory is generated from Hamilton's equations, but the potential energy surface is scaled to be gradually flattened and then recovered to the original surface, which facilitates barrier-crossing processes. We apply the PS-HMC method to three kinds of molecular processes: the thermal motion of argon particles, butane isomerization, and an atom transfer chemical reaction. These applications demonstrate that the PS-HMC method is capable of correctly constructing the canonical ensemble with a multimodal distribution. The sampling efficiency and accepted trajectories are examined to clarify the features of the PS-HMC method. Despite the potential scaling, many reactive atom transfer trajectories (elementary processes) pass through the vicinity of the minimum energy path. Furthermore, we demonstrate that the method can properly imitate the relaxation process owing to the inherent configurational continuity. By comparing the PS-HMC method with other relevant methods, we can conclude that the new method is a unique approach for studying both the dynamic and thermodynamic aspects of chemical processes.

By means of an initial electrochemical carbon dioxide reduction reaction (eCO2RR), both the reaction current and Faradaic efficiency of the eCO2RR on boron-doped diamond (BDD) electrodes were significantly improved. Here, this effect is referred to as the self-activation of BDD. Generally, the generation of carbon dioxide radical anions (CO2•-) is the most recognized pathway leading to the formation of hydrocarbons and oxygenated products. However, the self-activation process enabled the eCO2RR to take place at a low potential, that is, a low energy, where CO2•- is hardly produced. In this work, we found that unidentate carbonate and carboxylic groups were identified as intermediates during self-activation. Increasing the amount of these intermediates via the self-activation process enhances the performance of eCO2RR. We further evaluated this effect in long-term experiments using a CO2 electrolyzer for formic acid production and found that the electrical-to-chemical energy conversion efficiency reached 50.2% after the BDD self-activation process.

The ground and excited state calculations at key geometries, such as the Frank–Condon (FC) and the conical intersection (CI) geometries, are essential for understanding photophysical properties. To compute these geometries on noisy intermediate-scale quantum devices, we proposed a strategy that combined a chemistry-inspired spin-restricted ansatz and a new excited state calculation method called the variational quantum eigensolver under automatically-adjusted constraints (VQE/AC). Unlike the conventional excited state calculation method, called the variational quantum deflation, the VQE/AC does not require the pre-determination of constraint weights and has the potential to describe smooth potential energy surfaces. To validate this strategy, we performed the excited state calculations at the FC and CI geometries of ethylene and phenol blue at the complete active space self-consistent field (CASSCF) level of theory, and found that the energy errors were at most 2 kcal mol−1 even on the ibm_kawasaki device.

The structural and dynamical properties of water can be greatly altered by the anisotropic interfacial environment. Here, we study the intermolecular vibration and relaxation dynamics of a water film and a water droplet on a graphene surface based on low-frequency Raman spectra calculated from molecular dynamics simulations. The calculated Raman spectra of the interfacial water systems show a weakened libration peak and an enhanced intermolecular hydrogen bond (HB) stretching peak compared to the spectrum of bulk water, which are attributed to softened orientation motion. We also find that the collective polarizability relaxation in the droplet is much slower than that in the film and bulk, which is completely different from the collective dipole relaxation. The slow relaxation is due to a positive correlation between the induced polarizabilities of distinct molecules caused by the global and anisotropic structural fluctuations of the water droplet. Furthermore, we find that the two-dimensional HB network by the orientation-ordered interfacial water molecules leads to different intermolecular vibration dynamics between the parallel and perpendicular components. The present theoretical study demonstrates that low-frequency Raman spectroscopy can reveal the anisotropic and finite effects on the intermolecular dynamics of the water film and droplet.

Cyclometalated iridium(III) complexes have been used in various optical materials, including organic light-emitting diodes (OLEDs) and photocatalysts, and a deeper understanding and prediction of their luminescence quantum yields (LQYs) greatly aid in accelerating material design. In this study, we integrated density functional theory (DFT) calculations with machine learning (ML) techniques to extract factors controlling LQY. Although a substantial data set of Ir(III) complexes and their LQYs is indispensable for constructing accurate ML models to predict LQYs, generating this type of data set is challenging due to the complexities associated with ab initio calculations of LQYs. To address this issue, we investigated the nonradiative decay process of nine Ir(III) complexes emitting blue to green, each exhibiting varying experimental LQYs, by using DFT calculations. For all nine complexes, the quenching process was induced by the rotation of the single bond in one of the ligands, which converted the six-coordinate structure to the five-coordinate structure. Since the decay mechanism was common for the nine Ir(III) complexes, parameters correlated with LQYs could be used as objective variables instead of LQYs. Based on this idea, we collected a data set featuring Ir(III) complexes and the energy differences between their six- and five-coordinate triplet structures, which correlated with LQYs. We also constructed ML models using the calculated LQYs as the objective variables with the parameters from the ground-state calculations as explanatory variables. The analyses of the constructed model revealed that the LUMO energy of the ligand made the most significant negative contribution to LQY. This suggests that the potential energy surface of the metal-to-ligand charge transfer (MLCT) excited state, which stabilizes the six-coordinate structure, is reduced by decreasing the energy of the unoccupied orbitals.

In this study, we conducted simulations to explore the formation of solid electrolyte interphase (SEI) films in a lithium-ion battery (LIB) system containing 1.1 M lithium hexafluorophosphate (LiPF6) and ethylene carbonate (EC) at different electric potential (EP) differences (1.0, 2.0, 3.0, and 4.0 V). Using the Red Moon (RM) method combined with the constant-EP approach, we observed a decrease in the fractional accessible volume (FAV) of the SEI films as the EP difference increased. These findings suggest that the SEI film formed at an EP difference of 4.0 V exhibits the longest lifespan. The longevity of the battery can be attributed to the increased frequency of the dimerization reaction of the reduction product of EC with this EP difference. Our observations also show that the increased EP difference results in a greater negative charge on the anode, attracting more EC molecules from the initial stages of the formation process. As a result, this increase amplifies the total number of chemical reactions within LIBs. Our study highlights the importance of the proportion of chemical reactions during the initial stages of the SEI film formation process in determining its ultimate structure and properties. Therefore, it is crucial to regulate these reactions to control the SEI film properties. This information could have an impact on the design and optimization of LIB systems and provide ways to customize the SEI film properties, improving battery performance and lifespan.

Polymer informatics, which involves applying data-driven science to polymers, has attracted considerable research interest. However, developing adequate descriptors for polymers, particularly copolymers, to facilitate machine learning (ML) models with limited datasets remains a challenge. To address this issue, we computed sets of parameters, including reaction energies and activation barriers of elementary reactions in the early stage of radical polymerization, for 2500 radical-monomer pairs derived from 50 commercially available monomers and constructed an open database named “Copolymer Descriptor Database”. Furthermore, we built ML models using our descriptors as explanatory variables and physical properties such as the reactivity ratio, monomer conversion, monomer composition ratio, and molecular weight as objective variables. These models achieved high predictive accuracy, demonstrating the potential of our descriptors to advance the field of polymer informatics.

C-Glycosyltransferases have garnered attention owing to their ability to synthesize C-glycosides with high conversion and selectivity in one-pot reactions. Their potential in rational enzyme engineering makes them valuable for the synthesis of diverse C-glycosides. However, the detailed reaction mechanism remains unclear. To address this, we investigated the C-glycosylation of phloretin catalyzed by the glycosyltransferase GgCGT in the presence of the coenzyme UDP-glucose. Using density functional theory (DFT) calculations on a cluster model, we identified the most favorable pathway for C-glycosylation. The reaction proceeds via an initial proton transfer from phloretin to UDP-glucose, followed by the nucleophilic attack of phloretin on the glucose moiety and subsequent dissociation of UDP in an SN2-like manner. The SN2 step yields a non-aromatic intermediate, which can be rapidly converted to C-glycoside even without an enzymatic environment. The key residue that facilitates the rate-determining SN2 step is His-27, which stabilizes phloretin via hydrogen bonding. Additionally, to clarify why alternative products such as O-glycosides are not formed, we also investigated the O-glycosylation pathway. Our calculations revealed that O-glycosylation was promoted by proton transfer from UDP-glucose, like C-glycosylation, but was suppressed by structural fixation due to hydrogen bonding among phloretin, glucose, and GgCGT.

C-glycosylation catalyzed by C-glycosyltransferases affords chemically robust C-glycosides, yet the mechanistic origin of the remarkable selectivity for C- over O-glycosylation remains poorly understood. In this study, we present a comprehensive QM/MM investigation of the GgCGT-catalyzed mono-C-glycosylation of phloretin using UDP-glucose, extending our previous cluster-model analysis to explicitly include the full enzymatic environment. The calculated pathway involves an initial proton transfer from phloretin to UDP-glucose, followed by an SN2-type C-glycoside bond forming step accompanied by dissociation of UDP. The activation barrier of the rate-determining SN2 step is in good agreement with the experimental estimates. Although the alternative O-glycosylation pathway exhibits a lower activation barrier, it is thermodynamically disfavored due to the instability of the O-glycosylated intermediate, which readily undergoes the reverse reaction. In contrast, the C-glycosylated intermediate is strongly stabilized, rendering C-glycosylation effectively irreversible. Structural and natural bond orbital analyses reveal that this stability originates from preservation of a planar His27-Asp122 dyad and a favorable hydrogen-bonding network involving the phosphate group. Furthermore, the C6-OH group of glucose directly stabilizes the key transition state, explaining the reduced reactivity observed experimentally with UDP-xylose. These results establish a dual catalytic strategy in C-glycosyltransferases, combining thermodynamic control for C-selectivity with transition-state stabilization for rate acceleration.