研究者詳細 - 荒井　規允

Tail unsaturation is a standard design lever in emulsifier formulation, yet its coverage-dependent link to oil–water interfacial tension remains incomplete. Here we combine pendant-drop tensiometry with atomistic molecular dynamics (MD) using the mechanical (pressure-tensor) route to establish a quantitative structure–property for two monoglycerides that differ only in tail chemistry: monopalmitin (saturated) and monoolein (cis-unsaturated) at the triolein–saline interface. Experiments show that the unsaturated analogue lowers interfacial tension more effectively across comparable surface coverages. MD reproduces the coverage-resolved trends and attributes the difference to packing frustration from the cis double bond, which yields more disordered/fluid monolayers, greater interfacial thickness, enhanced headgroup hydration (higher hydrogen-bond occupancy and larger solvent-accessible surface area), and reduced short-range lateral order relative to the saturated analogue. These results establish a coverage-resolved structure–property linking tail chemistry to interfacial organization and to macroscopic interfacial tension, providing practical guidance for selecting and blending glyceride-based emulsifiers under formulation-relevant conditions.

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Phase Transition and Ternary Alloying Synergistically Boosting Magnetic Field Response for Methanol Oxidation Reaction on L10-FeCrPt Nanochains

Q Mo, R Liu, F Meng, Y Juan, J Li, S Wang, N Arai, J Liu, W Wang

Applied Catalysis B: Environment and Energy, 126475 387 2026年

ISSN 0926-3373

Designing magnetic materials with a strong response to external magnetic field is pivotal for enhancing electrocatalytic reactions in energy conversion and storage systems. Although significant progress has been made in spin catalysts for hydrogen and oxygen electrocatalytic reactions, the development of spin catalysts for small organic molecule reactions is still insufficient, which greatly hinders the exploration of the effect of magnetic fields on the electrochemical reaction. Herein, we propose a synergistic strategy combining ternary alloying and phase transition to construct L1<inf>0</inf>-FeCrPt intermetallic nanochains, which exhibit exceptional structural stability and a significantly boosted magnetic field response. After alloying Cr into FePt and transforming from the face-centered cubic (FCC) phase to the L1<inf>0</inf> phase through coating-assisted annealing, the activity of L1<inf>0</inf>-FeCrPt for the methanol oxidation reaction was enhanced by up to 41 % under a magnetic field of 8000 Oe, surpassing the enhancements of only 13 % and 30 % achieved by FCC FeCrPt and L1<inf>0</inf>-FePt, respectively. Based on the linear relation between the activation energy and the magnetic field, the magnetic moment parameter (M) is proposed to evaluate the magnetic response. The M value of L1<inf>0</inf>-FeCrPt reaches 46839 emu/g, which is 2.7 times that of L1<inf>0</inf>-FePt. DFT calculations indicate that the reaction barrier of L1<inf>0</inf>-FeCrPt is significantly reduced because the external magnetic field can facilitate the adsorption of CO, the breaking of O-H bonds, and the addition of OH* species. This study provides an efficient method for designing spin catalysts with high magnetic field response through ternary alloying and phase engineering.

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Ni–OH promoted water dissociation on Pt/Ni dual active sites for accelerated alkaline hydrogen evolution

S Li, T Xia, Y Zhao, L Wang, F Meng, N Arai, H Guo, R Wang

Materials Chemistry Frontiers 10 (9), 1487-1496 10 （ 9 ） 1487 - 1496 2026年

Although Pt–M (M = transition metal) catalysts are indispensable for the hydrogen evolution reaction (HER), the key function and operative mechanism of M that extend beyond the electronic modulation of Pt remain poorly defined. To address this gap, we synthesized three-dimensional PtNi multibranched nanostructures (PtNi MBNs) incorporating dual active sites. In situ spectroscopic analyses reveal that Ni sites directly facilitate water dissociation through the generation of Ni–OH species, thereby producing ample H* intermediates that mitigate the hydrogen scarcity in alkaline electrolytes and subsequently enhance the formation of Pt–H bonds. Molecular dynamics simulations further confirm strong spontaneous bonding between Ni and O at the atomic scale, underscoring the critical role of Ni in driving water dissociation and stabilizing Ni–OH bonds. Such Pt/Ni dual-active-site mechanism endows the PtNi MBNs with exceptional performance in 1 M KOH, delivering an ultralow overpotential of 9.29 mV at 10 mA cm−2 (35.2 mV lower than Pt/C) and a high mass activity of 9.30 A mg<inf>Pt</inf>−1 at −70 mV (3.63 times that of Pt/C). Characterization after cycling confirmed that PtNi MBNs exhibit excellent structural stability and electrochemical stability. This study advances the fundamental understanding beyond single site catalytic mechanisms and offers new insights for accelerating HER kinetics in alkaline electrolytes.

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In Silico Prediction of Multicomponent Functional Material Formulations via Machine Learning Coupled with Molecular Simulation: A Case Study on Cleansing Foam Formulations

M Hamaguchi, T Yokoyama, H Miwake, R Nakatake, N Arai

Industrial & Engineering Chemistry Research 65 （ 5 ） 2466 - 2478 2026年

ISSN 0888-5885

Multi-ingredient cleansing foams pose a combinatorial design challenge because many component ratios must be experimentally screened. We integrate DPD-derived descriptors with machine learning to enable prescreening and prioritization of formulations, thereby reducing exploratory batches and accelerating design cycles while maintaining a traceable physical rationale. The modeling descriptors─the hydrophilic fraction (f<inf>HI</inf>) and the solubility parameter contrast (Δδ) defined relative to the polyethylene glycol thresholds─probe amphiphilicity, while DPD-derived potential energy and pressure summarize mesoscale self-assembly. Using 430 historical recipes, we benchmark nested cross-validation under three generalization regimes: Points Out (random formulations), Mixtures Out (novel combinations of known ingredients), and Compounds Out (novel raw ingredients; polyols, including humectants and amphiphilic derivatives, in this data set). To prevent leakage, all preprocessing (imputation and scaling) is fit strictly on training folds only, and identical outer-CV partitions are held across feature conditions to enable paired comparisons. Incorporating modeling and simulation descriptors improves mean R2 from 0.665 to 0.716 (Points Out) and from 0.420 to 0.573 (Mixtures Out), and raises Compounds Out R2 from 0.023 to 0.341. Paired difference tests with HC3-robust OLS and Holm correction confirm statistically significant gains─small to moderate for Points Out and moderate to large for Mixtures and Compounds Out. Among algorithms, tree-based ensembles outperform linear, kernel, and neural baselines, reflecting nonlinear composition–property relations. This workflow operationalizes AI-assisted formulation design by triaging candidate recipes prior to wet-lab screening, enabling faster decision-making and tangible experimental savings while retaining physical interpretability via DPD-derived descriptors. Compounds out results apply only to polyols in the present data set; generalization beyond polyols is out-of-scope and will require larger, more diverse data sets and transfer learning.

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General reverse mapping of phase-separating polymers—Bridge from DPD to atomistic MD for star-polymer assemblies

N Osato, A Yamaguchi, N Arai

Chemical Physics Letters, 142655 887 2026年

ISSN 00092614

Polymer self-assembly is inherently multiscale: coarse-grained (CG) simulations capture mesoscale organization, whereas all-atom (AA) molecular dynamics resolves local interactions. We present ANY-RM, a fast and straightforward reverse-mapping method that reconstructs AA star-polymer structures from a dissipative particle dynamics configuration by converting bead coordinates into a concentration-distribution field and placing atoms to satisfy local composition constraints. The AA models retain CG phase separation while restoring atomistic detail. Static structure agrees across scales. Our method enables the investigation of both large-scale organization and detailed molecular interactions, offering a comprehensive understanding of polymer self-assembly across multiple scales.

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Enhanced Premelting at the Ice–Rubber Interface Using All-Atom Molecular Dynamics Simulation

T Kojima, I Yasuda, T Sato, N Arai, K Yasuoka

Langmuir 42 （ 3 ） 2454 - 2461 2026年

ISSN 07437463

The ice–rubber interface is critical in applications such as tires and shoe outsoles, yet its molecular tribology remains unclear. Using all-atom molecular dynamics simulations, we studied premelting layers at the basal face of ice in contact with styrene–butadiene rubber from 254 to 269 K. Despite its hydrophobicity, rubber enhanced the structural disorder of interfacial water, promoting premelting. In contrast, water mobility was suppressed by confinement from polymer chains, leading to glassy dynamics distinct from that of the ice–vapor interface. Near the melting point, rubber chains became more flexible and penetrated the premelting layer, forming a mixed rubber–water region that couples the dynamics of both components. These results suggest that nanoscale roughness and morphology of hydrophobic polymers disrupt ice hydrogen-bond networks, thereby enhancing premelting. Our findings provide molecular-level insight into ice slipperiness and inform the design of polymer materials with controlled ice adhesion and friction.

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Degree of polymerization controls bound/free water balance and water-holding in multifunctional amphiphilic polymer esters

YM Anda, NH Yamazaki, K Yoshioka, F Meng, T Saida, K Oyama, N Arai

Colloids and Surfaces A: Physicochemical and Engineering Aspects, 139858 737 2026年

ISSN 0927-7757

Moisture retention is a key determinant of sensory performance and stability in emulsified formulations, yet the molecular basis of water-holding in amphiphilic polymer esters used in cosmetics remains insufficiently elucidated. In this study, two compounds with different degrees of polymerization were synthesized from Polyglyceryl-2 Dipolyhydroxystearate (L -PD and S-PD), a water-in-oil emulsifier widely used in cosmetics. Hydrate formation revealed that L -PD exhibited a water-holding capability of 434 %, compared to 152 % for S-PD, with distinct hydrate structures. Based on the hypothesis that this difference in water-holding capability was due to differences in the degree of polymerization, the water-holding mechanism was investigated using both in vitro and in silico approaches. Experimental results showed that water in L -PD hydrates existed as both bound and free water, whereas S-PD hydrates contained predominantly free water. Simulations showed that differences in the degree of polymerization resulted in variations in the types of polymer configurations that could be adopted during water-holding. A higher degree of polymerization was found to favor polymer configurations with stronger affinity for water, promoting bound-water formation and enhancing the water-holding capability. This combined experimental and computational approach provides novel insights into the water-holding mechanism and is expected to aid the design of high-performance moisturizing materials for cosmetic applications.

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Application of AI in Tablet Development: An Integrated Machine Learning Framework for Pre-Formulation Property Prediction

M Hamaguchi, T Adachi, N Arai

Pharmaceutics 18 (4), 452 18 （ 4 ） 2026年

ISSN 1999-4923

Background/Objectives: Tablet development requires simultaneous optimization of multiple quality attributes under limited experimental budgets, yet formulation–property relationships are highly nonlinear in mixture systems. To support pre-formulation decision-making prior to extensive tablet prototyping, this study proposes an AI framework that organizes formulation and process data together with raw-material property records into a reusable database, and enriches conventional composition/process features with physically motivated mixture descriptors derived from raw-material properties and formulation/process settings. Methods: Mixture-level scalar descriptors are constructed by composition-weighted aggregation of material properties, and particle size distribution (PSD) is incorporated via a compact set of summary statistics computed from composition-weighted mixture PSDs. Three feature sets are compared: (i) Materials + Processes (MP), (ii) MP with scalar Descriptors (MPD), and (iii) MPD with PSD summaries (MPDD). Five target properties are modeled: hardness, disintegration time, flow function, cohesion, and thickness. We train and evaluate Random Forest, Extra Trees Regressor, Lasso, Partial Least Squares, Support Vector Regression, and a multi-branch neural network that processes the three feature blocks separately and concatenates them for prediction. For interpolation assessment, repeated Train/Dev/Test splitting (5:3:2) across multiple random seeds is used, and the effect of feature augmentation is quantified by paired RMSE improvements with bootstrap confidence intervals and paired Wilcoxon signed-rank tests. To assess robustness under practical formulation updates, rolling-origin time-series splits are employed and Applicability Domain indicators are computed to characterize out-of-distribution coverage. Results: Across interpolation evaluations, mixture-descriptor augmentation (MPD/MPDD) improves hardness and disintegration time in most settings, whereas gains for flow function are smaller and cohesion/thickness show mixed effects under limited sample sizes. Conclusions: Under extrapolation-oriented evaluation, the descriptors can improve hardness but may degrade disintegration-time prediction under covariate shift, emphasizing the need for careful descriptor selection and dimensionality control when deploying pre-formulation predictors.

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Adsorption kinetics of small molecules on FePt metallic electrodes by classical molecular dynamics simulation

F Meng, J Liu, Q Mo, N Arai

Journal of Materials Chemistry A 2026年

ISSN 2050-7488

Understanding how long reactants remain on catalytic surfaces (adsorption time) is essential for linking interfacial dynamics to overall reaction efficiency. In complex multistep systems such as the methanol oxidation reaction (MOR), the reaction pathways and surface poisoning are strongly related to the adsorption time and molecule orientation. By employing the molecular dynamics (MD) simulation method, the methanol, sulfuric acid and water molecules on the FePt alloy exposed to (001), (100) and (111) crystal planes were studied, thereby quantitatively defining and evaluating the adsorption time. Methanol exhibits the longest adsorption time, followed by sulfuric acid and water. Molecular conformation analysis further reveals two distinct interfacial regions: a 5 Å guiding layer, where methanol molecules initially approach the surface in a C-down configuration, and a 3 Å reaction layer, where the C–O bonds reorient parallel to the surface. Facet-dependent analysis indicates that the (111) surface, with alternating Pt and Fe atoms, possesses the strongest adsorption capacity, where the adsorption time for methanol is about 18 ps longer compared to the (001) facet. These findings establish a unified framework that quantitatively connects atomic structure, adsorption time, and molecular orientation, which provides a time-resolved perspective for the rational design of FePt-based electrocatalysts.

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Effect of Propylene-Oxide Segment Length on Cleansing Performance of Detergents With Nonionic Surfactants

Osato, N; Joko, A; Ikeda, H; Arai, N

JOURNAL OF SURFACTANTS AND DETERGENTS 28 （ 6 ） 1369 - 1379 2025年07月

ISSN 1097-3958

Understanding the relationship between surfactant molecular structure and cleansing performance is essential for the rational design of high-performance detergents. In this study, we investigate the effect of propylene oxide (PO) chain length on the detergency of nonionic surfactants through a combination of experimental measurements and coarse-grained molecular simulations. Experimentally, detergency tests revealed that increasing the PO content leads to a systematic decrease in cleansing performance. Dissipative particle dynamics simulations were performed to elucidate the molecular basis of this behavior. In bulk aqueous solutions, all surfactants self-assembled into micelles, with longer PO chains resulting in slightly larger and more diffuse micellar structures. At a model dirt surface, surfactants with longer PO chains exhibited stronger adsorption and slower desorption under flow conditions compared to surfactants without PO units. These findings suggest that while PO segments enhance interfacial adsorption, excessive retention at the surface can hinder soil removal, thereby reducing overall detergency. This combined experimental and simulation approach provides molecular-level insights into designing optimized nonionic surfactants for practical cleansing applications.

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Molecular insights into the motion of oil droplets in aqueous solutions of ester- and amide-containing cationic surfactants

Ueno K., Ishiwatari Y., Sasaki K., Kojima T., Takai A., Asakura K., Arai N., Banno T.

Journal of Molecular Liquids 426 2025年05月

ISSN 01677322

The study of self-propelled motion in soft matter systems has garnered significant interest owing to its potential applications in microfluidics, soft robotics, and autonomous system design. Understanding the molecular mechanisms underlying motility is crucial for advancing these applications. This study investigates the self-propelled motion of lauronitrile oil droplets in aqueous surfactant solutions, focusing on the impact of different surfactant molecular structures on droplet dynamics. This study compares surfactants with ester and amide linkages, highlighting their critical role in modulating interfacial tension and driving Marangoni convection, a key factor behind droplet movement. Surfactants with ester linkages exhibit a high affinity for lauronitrile and rapidly adsorb at the oil–water interface, generating strong Marangoni flows and driving fast droplet motion. In contrast, amide-containing surfactants exhibit slower adsorption and weaker interactions with lauronitrile, leading to reduced or absent motion. These findings provide new insights into the molecular mechanisms underlying the self-propelled droplet behavior in non-equilibrium systems and contribute to a deeper understanding of self-organizing phenomena.

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Investigating the Nanostructure Design Mechanism Behind the Hydrophobicity of the Biomimetic Surface

Meng, F; Liu, JL; Arai, N

ACS APPLIED MATERIALS & INTERFACES 17 （ 15 ） 23394 - 23404 2025年04月

ISSN 1944-8244

Wettability, a fundamental physicochemical property of functional materials that depends on their surface structure, has seen recent advances in understanding that have led to the development of superhydrophobic surfaces with applications in self-cleaning materials and antifogging coatings. Given the presence of a free energy barrier between the Cassie and Wenzel states, calculating this barrier provides a valuable means to assess surface hydrophobicity. We hypothesize that surface characteristics affect the free energy barrier between wetting states and that the determination of this barrier can be used to predict the hydrophobicity. Focused on models of a butterfly wing (striped surface) and a mosquito eye (pillared surface), this study employed many-body dissipative particle dynamics (mDPD) simulations to explore the relationship between the free energy barrier and surface roughness (height and spacing). For small-radius droplets, the height of the surface pattern predominantly influences the hydrophobicity. Conversely, for large-radius droplets, the spacing of the surface pattern is the dominant factor. Considering that the contact angle indicates static hydrophobicity, the free energy barrier is the indicator of dynamic hydrophobicity, which shows how well the surface can maintain its hydrophobicity under the impact of a droplet. This study underscores the advantages of the free energy barrier method in understanding dynamic hydrophobicity, which can be applied in evaluating high kinetic energy droplets onto surfaces, for example, automobiles, trains, and aircraft.

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Synthesis of Amorphous Graphene and Graphene Oxide Analogues

Sakuma, T; Sato, R; Yamaguchi, A; Imai, H; Arai, N; Oaki, Y

JOURNAL OF THE AMERICAN CHEMICAL SOCIETY 147 （ 13 ） 11564 - 11573 2025年04月

ISSN 0002-7863

Graphene and graphene oxide (GO) are promising two-dimensional nanomaterials. An ultimate goal is to achieve large-scale bottom-up syntheses of perfect graphene and GO. However, controlled syntheses of perfect graphitic structures still remain challenges in chemistry and materials science. Moreover, amorphous types have not received much attention. The present work shows syntheses, structures, and applications of amorphous graphene and GO analogues alternative to the ideal ones. The simultaneous multiple reactions of two conjugated monomers provide amorphous conjugated polymer networks containing low-crystalline graphitic domains and their stacking. The stacked amorphous graphene and GO are exfoliated into thin nanosheets including few-layers and monolayers. Moreover, in situ syntheses of the amorphous GO analogues are applied to obtain a reinforced plastic with high mechanical strength. The present work implies that various functional nanocarbons can be designed and synthesized by tailored combinations of conjugated monomers.

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Effects of grafting architecture of amphiphilic polymer-grafted nanoparticles on stabilization mechanisms of concentrated emulsions

Suzuki, K; Kobayashi, Y; Yamazaki, T; Tsuji, T; Arai, N

COLLOID AND INTERFACE SCIENCE COMMUNICATIONS 65 2025年03月

ISSN 2215-0382

This study explores the stabilization mechanisms of concentrated emulsions with tunable morphology using amphiphilic polymer-grafted nanoparticles (PGNPs). We employ coarse-grained molecular simulations to investigate concentrated oil-in-water emulsions stabilized by partially hydrolyzed poly(vinyl alcohol)-grafted poly(methyl methacrylate) (PMMA) particles. Two grafting architectures were examined: hydrophilic-hydrophobic (AB-type) diblock PGNPs and reverse BA-type diblock PGNPs. Our findings reveal that AB-type diblock PGNPs tend to aggregate, leading to droplet-droplet coalescence. In contrast, BA-type diblock PGNPs disperse effectively in the water phase, stabilizing robust emulsion through a space-filling mechanism. The study further demonstrates that the stability and morphology of the emulsions can be tuned by varying the number of PGNPs. Our results suggest that BA-type diblock PGNPs are more effective in stabilizing concentrated emulsions, offering insights for the design of novel emulsifiers in industrial applications.

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Fundamentals of Toughening Core-Shell Bioplastic Materials from a Molecular Perspective

Yamaguchi, A; Arai, S; Arai, N

ACS SUSTAINABLE CHEMISTRY & ENGINEERING 13 （ 1 ） 535 - 546 2025年01月

ISSN 2168-0485

This study analyzed the fracture behavior of poly(lactic acid) (PLA)/polybutylene succinate (PBS)/thermoplastic starch (TPS) blends featuring nanoscale-dispersed core-shell structures using molecular dynamics (MD) simulations, elucidating the toughening mechanisms at the molecular-level. Four models (PLA/TPS25, PLA/PBS/TPS5, PLA/PBS/TPS25, and PLA/PBS/TPS50) with varying core-shell structure parameters were utilized in the MD simulations. The fracture energy relationship obtained from the deformation simulation was PLA/PBS/TPS25 > PLA/PBS/TPS5 > PLA/PBS/TPS50 ≈ PLA/TPS25, which generally reproduced the experimental results of the impact test of the blends. The entire material was fractured by delamination at the TPS/PLA interface in the PLA/TPS25, and at the TPS/PBS interface in the PLA/PBS/TPS50 with the thinnest PBS shell. The PLA/PBS/TPS5 with the thickest PBS shell exhibited a reduced toughening effect due to the formation of numerous voids in the PLA matrix phase during deformation. In PLA/PBS/TPS25 with an intermediate thickness PBS shell, moderate-density voids formed during deformation, releasing strain constraints and effectively strengthening the material. The orientation hardening of PLA and PBS that occurs during deformation also contributes to the deformation energy absorption of PLA/PBS/TPS25. The molecular-level toughening mechanism elucidated in this study is anticipated to contribute to the enhancement of the properties of a wide range of bioplastics containing polysaccharides.

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分子シミュレーションと機械学習を活用した界面活性剤水溶液の構造・物性予測

荒井規允

オレオサイエンス（公益社団法人日本油化学会） 25 （ 7 ） 285 - 289 2025年

ISSN 13458949

界面活性剤はソフトマターの一種として，分子設計の自由度が高く，自己集合構造や物性に多様性を示す。しかし，それゆえ材料内部の挙動は複雑であり，その潜在能力を十分に引き出すのは容易ではない。本研究では，界面活性剤水溶液の構造と機能を予測するために，分子シミュレーションと機械学習を活用した研究例を紹介する。まず，散逸粒子動力学法を用いて200種以上のクレンジング剤処方に対する自己集合構造を再現・解析した。次に，分子記述子を特徴量とした機械学習モデルを構築し，高精度な洗浄性能予測を実現した。さらに，分子の化学構造から自己集合構造を予測する深層学習モデルを構築し，機能性界面活性剤の効率的な設計手法としての有効性を示した。

A molecular strategy for creating functional vesicles with balancing structural stability and stimuli-responsiveness

Sasaki, S; Ueno, H; Arai, N; Asakura, K; Banno, T

NANOSCALE 17 （ 11 ） 6863 - 6873 2025年

ISSN 2040-3364

Vesicles, closed bilayer structures composed of amphiphiles, have attracted considerable attention as functional materials. Structural stability and stimulus responsiveness are required for next-generation functional vesicles. However, there is a dilemma between these properties because the desired membrane structure varies in terms of structural stability and stimulus sensitivity. Herein, we propose a new approach for the development of giant vesicles (GVs) through the molecular design and synthesis of amphiphiles with or without amide linkages, forming hydrogen bonding. From the 1H NMR analysis and fluorescence spectra of environment-responsive probes, intermolecular hydrogen bonding between the amide linkages in the membrane contributed to the enhanced structural stability of the GVs. Moreover, by adding amphiphiles containing a photoresponsive azobenzene moiety to GVs composed of amphiphiles with or without amide linkages, a distinct mechanism of photoresponsive deformation was observed: the former exhibited large and irreversible deformation, while the latter showed a modest and reversible manner due to the photoisomerisation of azobenzene under ultraviolet and subsequent visible light illumination. This difference was also attributed to the membrane structure affected by intermolecular hydrogen bonding. Based on these results, the finding provides a molecular methodology for developing highly functional vesicles.

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