研究者詳細 - 荒井　規允

論文 - 荒井　規允

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Predicting molecular ordering in a binary liquid crystal using machine learning

T Inokuchi, R Okamoto, N Arai

Liquid Crystals, 1-11 （Liquid Crystals） 47 （ 3 ） 438 - 448 2019年

研究論文（学術雑誌）, 共著, 査読有り, ISSN 0267-8292

© 2019, © 2019 Informa UK Limited, trading as Taylor & Francis Group. Machine learning is a category of AI technology that is utilized in the product development cycle in numerous industries. It was reported that machine learning can be applied to predict the chemical properties of functional materials, for example, the self-assembly of surfactant solutions (Nanoscale, 2018, 10, 16013) and the chemical reactions of copper nanoparticles (ACS Energy Lett., 2018, 3, 2983). A liquid crystal (LC) molecule is a representative functional material. Monodisperse systems have been targeted in many theoretical studies; however, the resulting products usually have a polydisperse distribution. It has been reported in several studies that the properties exhibited by polydisperse systems are different from those observed in monodisperse systems. In this study, we focus on the physical properties of polydisperse systems i.e. the ratio of binary LC molecules on the phase transition temperature and the possibility of predicting the physical properties of the system using machine learning. A relatively high prediction accuracy was obtained using machine learning. This study demonstrates that machine learning can be utilized to predict the phase transition temperature of polydispersed LC systems. The results of this study will contribute to the further development of material science and molecular design via the application of machine learning.

散逸粒子動力学（DPD）法を用いたソフトマターの分子シミュレーション

荒井規允

可視化情報学会誌（社団法人可視化情報学会） 39 （ 154 ） 19 - 25 2019年

研究論文（研究会，シンポジウム資料等）, 単著, 査読有り, ISSN 0916-4731

近年，コンピュータシミュレーション技術の発達によって，これまで取り扱うことのできなかった様々なシステムの再現，可視化が行われるようになってきた．散逸粒子動力学(DPD)法は分子シミュレーションの一種だが，原子や分子をある程度一纏めとして扱うことで，従来の分子シミュレーションよりも大きな時空間スケールの現象を再現できる．本稿では，DPD法の歴史，アルゴリズムを簡単に説明したあと，これまで筆者が対象としてきたいくつかのソフトマター材料(界面活性剤，ナノ粒子，液晶，高分子膜・生体膜)に対するDPDシミュレーションについて紹介する．

Water permeation in polymeric membranes: Mechanism and synthetic strategy for water-inhibiting functional polymers

Araki Y., Kobayashi Y., Kawaguchi T., Kaneko T., Arai N.

Journal of Membrane Science （Journal of Membrane Science） 564 184 - 192 2018年10月

研究論文（学術雑誌）, 単著, 査読有り, ISSN 03767388

© 2018 Elsevier B.V. The prediction and control of penetration in a polymeric membrane is of critical importance in green chemistry and energy technology, including gas separation, water purification, and desalination. We performed molecular simulations of water transport through a polymeric membrane to clarify the key factors that dominate water permeation. The effects of additives and chemical interaction (solubility) on water inhibition were investigated. We found that additives reduce water permeability into the membrane. Upon incorporation of the additive, strength of coordination of water molecules near the membrane surface increases. Thus, the penetration frequency of water molecules into the membrane decreases. It is suggested that the local environment near the membrane surface plays a significant role in controlling water permeability. In order to gain deeper insights into the polymer design, we discussed the chemical interaction (solubility) parameter change between polymer chains and additives. Using a repulsive chemical species of a polymer chain for additives can lead to higher water inhibition. The ability to control water permeability into the membrane by polymer design can be exploited for applications in water separation technology.

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Multiscale prediction of functional self-assembled materials using machine learning: High-performance surfactant molecules

Inokuchi T., Li N., Morohoshi K., Arai N.

Nanoscale （Nanoscale） 10 （ 34 ） 16013 - 16021 2018年09月

研究論文（学術雑誌）, 共著, 査読有り, ISSN 20403364

© 2018 The Royal Society of Chemistry. Various physical properties of functional materials can be induced by controlling their chemical molecular structures. Therefore, molecular design is crucial in the fields of engineering and materials science. With its remarkable development in various fields, machine learning combined with molecular simulation has recently been found to be effective at predicting the electronic structure of materials (Nat. Commun., 2017, 8, 872 and Nat. Commun., 2017, 8, 13890). However, previous studies have used similar microscale information as input and output data for machine learning, i.e., molecular structures and electronic structures. In this study, we determined whether multiscale data can be predicted using machine learning via a self-assembly functional material system. In particular, we investigated whether machine learning can be used to predict dispersion and viscosity, as the representative physical properties of a self-assembled surfactant solution, from the chemical molecular structures of a surfactant. The results showed that relatively accurate information on these physical properties can be predicted from the molecular structure, suggesting that machine learning can be used to predict multiscale systems, such as surfactant molecules, self-assembled micelle structures, and physical properties of solutions. The results of this study will aid in further development of the application of machine learning to materials science and molecular design.

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Self-assembled morphology of tripod nanoparticle solutions: the effect of arm length and hydrophobic ratio

Bin Sazali M., Kobayashi Y., Taniguchi Y., Nakashima T., Arai N.

Molecular Systems Design and Engineering （Molecular Systems Design and Engineering） 3 （ 3 ） 572 - 580 2018年06月

研究論文（学術雑誌）, 共著, 査読有り, ISSN 2058-9689

© 2018 The Royal Society of Chemistry. We have studied the self-assembled morphologies of tripod nanoparticle solutions confined in nanoslits using dissipative particle dynamics (DPD) simulations. In the present study, composite-shaped nanoparticles, like a planar tripod model with an amphiphilic surface pattern, were also synthesized experimentally. Using the DPD results at various values of a hydrophobic ratio (HR) and arm length (AL), we create phase diagrams of the self-assembled morphologies of tripod nanoparticles. With each of the two parameters, we observe three morphologies in the tripod nanoparticle solution. Further, potential energy vs. temperature for various tripod nanoparticle solutions is compared for different self-assembled structures. Our simulations offer a guide to control the morphologies of self-assembled tripod nanoparticles, which constitute novel systems that may find applications in nanofluidic devices.

Dissipative particle dynamics simulation of the relaxation behaviour of a triblock copolymer supramolecular network

Wakimoto K., Sasaki H., Arai N.

Molecular Simulation （Molecular Simulation） 44 （ 7 ） 534 - 539 2018年05月

研究論文（学術雑誌）, 単著, 査読有り, ISSN 08927022

© 2017 Informa UK Limited, trading as Taylor & Francis Group. Since block copolymers self-assemble into various nanostructures and these are widely used in soft materials such as cosmetics and paints, these continue to be the subjects of fundamental studies that progress new technologies. ABA triblock copolymers self-organise into supramolecular networks in which crosslinked structures change upon heating and other external stimulation. Supramolecular networks that consist of ABA triblock copolymers have three components: bridges, loops and dangles. These supramolecular networks have structural regions (clusters) in which end blocks of polymer chains are aggregated and connected by the internal blocks of the polymer chains. Despite of the importance of relaxation behaviour during the measurement and control of polymer materials, the molecular-level behaviour of these systems has not been addressed. We observed pull-out phenomenon that the ends of these polymers detach from clusters, and estimated characteristic detachment times by counting the number of detachments and compared it with the time of longest relaxation in that system.

Understanding a molecular motor walking along a microtubule: an asymmetric Brownian motor driven by bubble formation with a focus on binding affinity

Hojo M., Arai N., Ebisuzaki T.

Molecular Simulation （Molecular Simulation） 44 （ 7 ） 523 - 529 2018年05月

研究論文（学術雑誌）, 単著, 査読有り, ISSN 08927022

© 2017 Informa UK Limited, trading as Taylor & Francis Group. In recent years, many studies on a molecular motor have been conducted in the fields of biorheology and nanoengineering. The molecular motor is a molecule that converts the chemical energy obtained by ATP hydrolysis into mechanical energy. Explaining this mechanism is important for nanoengineering. A kinesin, which is a type of molecular motor, has the characteristics to move on a microtubule with hand-over-hand steps. The kinesin walking behaviour is explained by the ‘asymmetric Brownian ratchet model’. Previously, we had suggested that the walking mechanism was achieved by the bubble formation in a nanosized channel surrounded by hydrophobic atoms with the transition between the two states–bubble state and liquid state. However, the walking behaviour of the model motor was different from that of a single molecule measurement of a kinesin. In this study, we constructed a new motor system focused on the asymmetric binding affinity of a motor protein and performed a model simulation using the dissipative particle dynamics method. As a result, it was observed that hand-over-hand walking depends on the transition position ratio and the transition frequency coefficient. Moreover, the efficiency of the new motor system is higher than that of the previous motor systems. The new motor model can provide a simulation guide for the design of biomimetic nanomachines.

Self-assembly of peptide amphiphiles by vapor pressure osmometry and dissipative particle dynamics

Seki T., Arai N., Suh D., Ozawa T., Shimada T., Yasuoka K., Hotta A.

RSC Advances （RSC Advances） 8 （ 47 ） 26461 - 26468 2018年

研究論文（学術雑誌）, 共著, 査読有り, ISSN 2046-2069

© 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.

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Relationship between water permeation and flip-flop motion in a bilayer membrane

Inokuchi T., Arai N.

Physical Chemistry Chemical Physics （Physical Chemistry Chemical Physics） 20 （ 44 ） 28155 - 28161 2018年

研究論文（学術雑誌）, 共著, 査読有り, ISSN 14639076

© 2018 the Owner Societies. The lipid bilayer membrane facilitates various biological reactions and is thus an essential structure that sustains all higher forms of life. The unique local environment of the lipid bilayer plays critical roles for the diffusion of biomolecules as well as water molecules in biological reactions. Although fluctuation of the cell membrane is expected to allow for the transport of some water molecules, the flip-flop of lipid molecules corresponds to lipid transport between membrane leaflets, and is considered to be an important process to regulate the lipid composition of biological membranes. However, the relationship between these flip-flop phenomena and surrounding water molecules remains poorly understood. We hypothesized that the flip-flop is caused by water molecules permeating through the cell membrane. To test this hypothesis, we used millisecond-order coarse-grained molecular simulations (dissipative particle dynamics) to investigate the distance between water molecules and lipid molecules depending on the position of the lipid molecule. The results clearly showed that water molecules affect the flip-flop motion in the early stage, but have minimal contribution to the subsequent behavior. Moreover, based on the results of dissipative particle dynamics simulation, we computed several first-passage-time (FPT) quantities to describe the detailed dynamics of water permeation. We modeled arrangements in the middle of the flip-flop process, which were compared with the arrangement without lipid molecules. Overall, our results indicate that lipid molecules located both in perpendicular and parallel arrangements largely affect water permeation. These findings provide new insight into the detailed relationship between water permeation and the flip-flop motion.

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Janus or homogeneous nanoparticle mediated self-assembly of polymer electrolyte fuel cell membranes

Kobayashi Y., Arai N.

RSC Advances （RSC Advances） 8 （ 33 ） 18568 - 18575 2018年

研究論文（学術雑誌）, 共著, 査読有り, ISSN 2046-2069

© 2018 The Royal Society of Chemistry. The functionality of polymer electrolyte fuel cell membranes depends on the self-assembled structure of the graft polymer. To control self-assembly, nanoparticles (NPs) are often used as catalysts. Hence, we investigate the effect of hydrophilic (HI), hydrophobic (HO), and Janus nanoparticles (JNPs) for the self-assembly of graft polymers using dissipative particle dynamics (DPD) simulations. We found that the differences that appeared among the self-assembled structures of water depended on the concentration of PEFC. We also calculated the diffusion constant of water (D(H2O)) from the slopes of the time-averaged mean square displacement (MSD) curves. HI NPs had the largest effect in suppressing the diffusion of water because the HI NPs incorporated into the water particles. It was also seen that D(H2O) with various NPs gradually decreased as the number of NPs increased for three PEFC concentrations (70%, 80%, and 90%). Thus, a close correlation between the position and chemical composition of NPs in polymer electrolyte fuel cell (PEFC) membrane systems has been found. Moreover, the mean square radius of gyration 〈Rg〉 and the mean square end-to-end distance 〈R〉 was calculated to analyse the self-assembled structures of PEFC. The 〈Rg〉 and 〈R〉 increased as the concentration of PEFC was increased, with and without various NPs.

Water Permeation and Flip-Flops Moving in Bilayer Membranes: A Dissipative Particle Dynamics Simulation

T Inokuchi, N Arai

Meeting Abstracts, 188-188 2018年

研究論文（国際会議プロシーディングス）, 共著, 査読有り

Dissipative Particle Dynamics Simulation for Clarifying Mechanism of Water Permeation in Polymeric Membranes

Y Araki, N Arai, Y Kobayashi, T Kawaguchi, T Kaneko

Meeting Abstracts, 187-187 2018年

研究論文（国際会議プロシーディングス）, 共著, 査読有り

表面官能基を有するナノ粒子の自己集合に関する分子シミュレーション

荒井規允, 小林祐生

年次大会（一般社団法人日本機械学会） 2018 （ 0 ） J0420102 2018年

研究論文（研究会，シンポジウム資料等）, 共著, 査読有り

We have performed coarse-grained molecular simulation simulations to investigate self-assembly processes and structures of functionalized nanoparticles confined in a nanoslit. The functionalized nanoparticle is decorated with some attractive areas. On the basis of the observed temperature- and concentration-dependent morphologies, we derive semiquantitative phase diagrams of the temperature. Five distinct designs of the nanoparticles are considered. We find that various self-assembled structures depending on the number of functionalized groups. The self-assembly behavior of the functionalized nanoparticles can be qualitatively predicted when the number of groups is known. Our simulation offers a theoretical guide to control morphologies of the self-assembled nanoparticles, a novel system that may find applications in nanofluidic devices or for nanopatterning.

若手研究者より研究会に期待すること

樋口祐次, 荒井規允

アンサンブル（分子シミュレーション学会） 20 （ 2 ） 102 - 104 2018年

研究論文（研究会，シンポジウム資料等）, 共著, 査読有り, ISSN 1884-6750

分子シミュレーション研究会発足20周年を記念して，「若手研究者より研究会に期待すること」をまとめたので報告する．分子シミュレーション夏の学校，分子シミュレーションスクールでアンケートを実施し，その内容をまとめて本記事を執筆した．それぞれ28人，52人から有効なご回答をいただいた．ここでは興味深い意見を中心に取り上げさせていただく．

機械学習と粗視化シミュレーションによる高性能界面活性剤の分子構造の探索

李娜, 諸星圭, 井口拓弥, 荒井規允

年次大会（一般社団法人日本機械学会） 2018 （ 0 ） J0420101 2018年

研究論文（研究会，シンポジウム資料等）, 共著, 査読有り

The success of machine learning combined with molecular simulation has been demonstrated in predicting electronic structure of materials(1)(2). A breakthrough that can aid in the design of new molecules that can be used to enhance the performance of material science. However, the prediction of physical properties of functional materials is one of the most challenging issue because of a multiscale problem across scientific disciplines in soft matter systems(3). In this study, first we used the coarse-grained molecular simulation to solve the multiscale problem. Second, we determined whether machine learning can be used to predict dispersion and viscosity, as the representative physical properties of surfactant solution, from the chemical molecular structures of a surfactant. The results showed that relatively accurate information on these physical properties can be predicted from the molecular structure, suggesting that machine learning can be used to predict multiscale systems, such as surfactant molecules, self-assembled micelle structures, and physical properties of solutions. The results will aid in further our scientific understanding and gain new insights(4).

散逸粒子動力学法を用いた界面活性剤水溶液の管内流れと自己集合に関する研究

小林祐生, 荒井規允

年次大会（一般社団法人日本機械学会） 2018 （ 0 ） J0420103 2018年

研究論文（研究会，シンポジウム資料等）, 共著, 査読有り

A self-assembly research is currently one of the most studied branches of materials chemistry, therefore, has gained a lot of attention due to a variety of potential applications in electronics, engineering, biomedical, and optical fields. So far, many previous studies have been reported to investigate the self-assembly of surfactant for developing various functional materials. In this report, we focused on the chemical nature of the wall surface as a critical parameter which can drastically change the self-assembled structure. We have studied the rheological properties of surfactant solutions in the distinct chemical nanotubes using a computer simulation. We found that the difference in the viscosity is able to obtain depending on the chemical nature of the wall surface even if systems without the surfactant molecules. With the surfactant molecules, the characteristic viscosity behaviors were observed with rich steady-state morphologies. For example, although the concentration of surfactant is the same (c = 30%), completely different viscosity behaviors were seen in hydrophilic (shear-thinning) and hydrophobic (shear-thickening) nanotubes. Our simulation offers a guide to control the rheological properties of surfactant aqueous solutions by the chemical nature of the wall surface, the effect of confinement, concentration of surfactant aqueous solution and the self-assembled structure.

分子シミュレーション研究会の各種データ

荒井規允, 泰岡顕治

アンサンブル（分子シミュレーション学会） 20 （ 2 ） 105 - 107 2018年

研究論文（研究会，シンポジウム資料等）, 共著, 査読有り, ISSN 1884-6750

分子シミュレーション研究会発足20周年を記念し，この20年間の研究会に関するいくつかのデータをまとめた．具体的には，研究会，討論会，夏の学校，分子シミュレーションスクール，アンサンブルに関するデータを報告する．なお各種データは，2002年までは河村雄行先生がまとめた分子シミュレーションのあゆみを参照し，その後は事務局（三上益弘先生，岡崎進先生，田中秀樹先生，泰岡）に保管されているデータを参照した．

Linkage Among Molecular Simulations for Calculate Quantitative Polymeric Properties with a Minimum Amount of Calculation

R Miwatani, KZ Takahashi, N Arai

First International Conference on 4D Materials and Systems (August 26-30, 2018) 2018年

共著, 査読有り

Self-assembly and viscosity behavior of Janus nanoparticles in nanotube flow

Y Kobayashi, N Arai

Langmuir 33 (3), 736-743 （Langmuir） 33 （ 3 ） 736 - 743 2017年

研究論文（学術雑誌）, 共著, 査読有り, ISSN 0743-7463

© 2017 American Chemical Society. Janus nanoparticles (JNPs) have received considerable attention because of their characteristic physical properties that are due to more than two distinct chemical or physical surfaces. We investigated the rheological properties of a JNP solution in the nanotubes using a computer simulation. Prediction and control of the self-assembly of colloidal nanoparticles is of critical importance in materials chemistry and engineering. Herein, we show computer simulation evidence of a new type of velocity profile and a hallmark shear-thinning behavior by confining a JNP solution to a nanotube with hydrophobic and hydrophilic wall surfaces. We derived curves of the shear rate versus the viscosity for two quasi-one-dimensional nanotube systems including diluted and concentrated volume fractions of JNP solutions. For the diluted system, under relatively low shear rates, shear-thinning behavior with a moderate slope or behavior similar to a Newtonian fluid is observed because of the clustering of JNPs. Under relatively high shear rates, the slope of shear thinning changes markedly because the self-assembled structures are rearranged. Moreover, for concentrated systems, when the nanotube wall is hydrophobic, new characteristic velocity profiles that have not been reported before are observed. Our simulation offers a guide to control the rheological properties of JNP solutions by the chemical patterns on the surfaces of nanochannels, the effect of confinement, and the self-assembled structure. (Chemical Equation Presented).

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Theory of nanobubble formation and induced force in nanochannels

N Arai, T Koishi, T Ebisuzaki

Physical Review E 96 (4), 042802 （Physical Review E） 96 （ 4 ） 042802 - 10192 2017年

研究論文（学術雑誌）, 共著, 査読有り, ISSN 2470-0045

© 2017 American Physical Society. This paper presents a fundamental theory of nanobubble formation and induced force in confined nanochannels. It is shown that nanobubble formation between hydrophobic plates can be predicted from their surface tension and geometry, with estimated values for the surface free energy and the force acting on the plates in good agreement with the results of molecular dynamics simulation and experimentation. When a bubble is formed between two plates, vertical attractive force and horizontal retract force due to the shifted plates are applied to the plates. The net force exerted on the plates is not dependent on the distance between them. The short-range force between hydrophobic surfaces due to hydrophobic interaction appears to correspond to the force estimated by our theory. We compared between experimental and theoretical values for the binding energy of a molecular motor system to validate our theory. The tendency that the binding energy increases as the size of the protein increases is consistent with the theory.

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