Published papers

© 2018 by the authors. Licensee MDPI, Basel, Switzerland. Monte Carlo simulations of chiral liquid-crystals, represented by a simple coarse-grained chiral Gay–Berne model, were performed to investigate the effect of central longitudinal dipole interactions on phase behavior. A systematic analysis of the structural properties and phase behavior of both achiral and chiral systems, with dipole interactions, reveals differing effects; strong dipole interactions enhance the formation of layered structures; however, chiral interactions may prevent the formation of such phases under certain conditions. We also observed a short-ranged smectic structure within the cholesteric phases with strong dipole interactions. This constitutes possible evidence of presmectic ordering and/or the existence of chiral line liquid phases, which have previously been observed in X-ray experiments to occur between the smectic twisted grain boundary and cholesteric phases. These results provide a systematic understanding of how the phase behavior of chiral liquid-crystals changes when alterations are made to the strength of dipole interactions.

© 2018 Author(s). Studies on homogeneous nucleation have been conducted for decades, but a large gap between experiment and theory persists when evaluating the nucleation rate because the classical nucleation theory (CNT) with all its modifications still cannot fully incorporate the kinetics of homogeneous nucleation. Recent large-scale molecular dynamics (MD) simulations on homogeneous nucleation estimated a nucleation rate around the same order of magnitude as that obtained in experiments. This immensely improved agreement between experiment and theory is exciting because MD can provide detailed information on molecular trajectories. Therefore, a better understanding of the kinetics of homogeneous nucleation can now be obtained. In this study, large-scale MD simulations on homogeneous nucleation were performed. Through kinetic analysis of the simulation results, the nucleation rate, free energy barrier, and critical cluster size were found. Although the nucleation rates directly obtained from the simulations differed from those calculated from the CNT by 8-13 orders of magnitude, when the parameters calculated from the molecular trajectories were substituted into the classical theory, the discrepancy between the nucleation rates decreased to within an order of magnitude. This proves that the fundamental formulation of the theoretical equation is physically sound. We also calculated the cluster formation free energy and confirmed that the free energy barrier decreases with increasing supersaturation ratio. The estimated barrier height was twice that determined by theory, whereas the critical cluster size showed very good agreement between simulation and theory.

© 2018 American Chemical Society. Recent experiments have found hexadecyl-trimethyl-ammonium bromide (CTAB) to have superior ice nucleation inhibition properties [J. Phys. Chem. B 121, 6580]. The mechanism of how the inhibition takes place remains unclear. Therefore, molecular dynamics was used to simulate ice crystallization of a water/CTAB/ice system. The ice crystallization rate for a pure water system was compared for the basal [0001], first prism [1010], and secondary prism plane [1120], where the basal plane grew the slowest followed by the first prism plane. When CTAB was added to the ice-liquid water system, crystallization was clearly impeded. Even when ice starts growing away from the CTAB molecule, the hydrophilic head would at some point protrude and get caught in the water/ice interface. Once the head of the CTAB was encapsulated in the advancing interface, the hydrophobic body would wriggle around and disrupt the formation of hydrogen bond networks that are essential for ice growth. When the interface clears the length of the body of the CTAB molecule, ice crystallization resumes at its normal pace. In summary, the inhibition of ice growth is a combination of the hydrophilic head acting as an anchor and the dynamic motion of the hydrophobic tail hindering stable hydrogen bonding for ice growth.

Copyright © 2018, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved. Molecular dynamics (MD) is a powerful computational method for simulating molecular behavior. Deep neural networks provide a novel method of generating MD data efficiently, but there is no architecture that mitigates the well-known exposure bias accumulated by multi-step generations. In this paper, we propose a multi-step time series generator using a deep neural network based on Wasserstein generative adversarial nets. Instead of sparse real data, our model evolves a latent variable z that is densely distributed in a low-dimensional space. This novel framework successfully mitigates the exposure bias. Moreover, our model can evolve part of the system (Feature extraction) with any time step (Step skip), which accelerates the efficient generation of MD data. The applicability of this model is evaluated through three different systems: harmonic oscillator, bulk water, and polymer melts. The experimental results demonstrate that our model can generate time series of the MD data with sufficient accuracy to calculate the physical and important dynamical statistics.

© 2019 Author(s). The nucleation process of anisotropic particles often differs from that of their spherically symmetric counterparts. Despite a large body of work on the structure of droplets of anisotropic particles, their formation process remains poorly understood. In this study, homogeneous nucleation of uniaxial anisotropic particles was studied. Through structural analysis of cluster development and the formation free energy during the nucleation stage, it was revealed that the nucleation of uniaxial particles begins from highly ordered states. There is, however, a marked decrease in orientational order within the cluster before critical nucleus size is attained. Further investigation on variations in the molecular interactions demonstrates how droplet elongation and the direction of the nematic ordering director relative to the axis of elongation can both be controlled according to the nature of the molecular anisotropy.

© 2018, Japan Society of High Pressure Science and Technology. All rights reserved. The thermodynamic and kinetic properties of clathrate hydrates have been studied for scientific interest and various potential industrial applications. This article highlights recent advances in the hydrate researches using molecular simulations with a focus on formation processes and thermodynamic properties. Subsets of molecular simulations, Molecular Dynamics (MD), Monte Carlo (MC) and ab initio MD simulations have been applied to hydrate systems and provide the fundamental insights at molecular level.

© The Royal Society of Chemistry. Peptide amphiphiles are one of the most promising materials in the biomedical field, so much effort has been devoted to characterizing the mechanism of their self-assembly and thermosensitive gelation. In this work, vapor pressure osmometry measurements were carried out to parameterize the thermosensitivity of interactions between peptide amphiphiles in an aqueous solution. The osmometry measurement verified that the peptides became more hydrophobic as temperature increased, which was quantitatively described with the Flory-Huggins χ parameter. Thereafter, a coarse-grained molecular model was used to simulate peptide amphiphiles dissolved in an aqueous solution. The temperature sensitive coarse-grained parameter aHW, which is the repulsive force between the hydrophilic head of the peptide amphiphile and water was estimated from the aforementioned experimentally obtained χ. Furthermore, the effects of concentration and temperature on the self-assembly behavior of peptide amphiphiles were quantitatively studied by dissipative particle dynamics. The simulation results revealed that aHW plays an important role in self-assembly characteristics and in the resulting microstructure of the peptide amphiphiles, which coincides with previous experimental and computational findings. The methodology in quantitatively linking the coarse-grained parameter from experiment and theory provides a sensible foundation for bridging future simulation studies with experimental work on macromolecules.

© The Royal Society of Chemistry. The mesoscopic structures of polymer electrolyte membrane (PEM) affect the performances of fuel cells. Nafion® with the Teflon® backbone has been the most widely used of all PEMs, but sulfonated poly-ether ether-ketone (SPEEK) having an aromatic backbone has drawn interest as an alternative to Nafion. In the present study, a series of dissipative particle dynamics (DPD) simulations were performed to compare Nafion and SPEEK. These PEM polymers were modeled by connected particles corresponding to the hydrophobic backbone and the hydrophilic moiety of sulfonic acid group. The water particle interacting with Nafion particles was prepared as well. The crucial interaction parameters among DPD particles were evaluated by a series of calculations based on the fragment molecular orbital (FMO) method in a non-empirical way (Okuwaki et al., J. Phys. Chem. B, 2018, 122, 338-347). Through the DPD simulations, the water and hydrophilic particles aggregated, forming cluster networks surrounded by the hydrophobic phase. The structural features of formed water clusters were investigated in detail. Furthermore, the differences in percolation behaviors between Nafion and SPEEK revealed much better connectivity among water clusters by Nafion. The present FMO-DPD simulation results were in good agreement with available experimental data.

© 2018, The Author(s). An isotropic periodic sum (IPS) is a powerful technique to reasonably calculate intermolecular interactions for wide range of molecular systems under periodic boundary conditions. A linear-combination-based IPS (LIPS) has been developed to attain computational accuracy close to an exact lattice sum, such as the Ewald sum. The algorithm of the original LIPS method has a high computational cost because it needs long-range interaction calculations in real space. This becomes a performance bottleneck for long-time molecular simulations. In this work, the combination of an LIPS and fast Fourier transform (FFT) was developed, and evaluated on homogeneous and heterogeneous molecular systems. This combinational approach of LIPS/FFT attained computational efficiency close to that of a smooth particle mesh Ewald while maintaining the same high accuracy as the original LIPS. We concluded that LIPS/FFT has great potential to extend the capability of IPS techniques for the fast and accurate computation of many types of molecular systems.