Published papers

Cyclodextrins (CDs) are suitable drug carriers because of their doughnut-shaped cavities with hydrophilic outer and hydrophobic inner surfaces. Temperature-responsive CD-based drug carriers are expected to be one of the most promising candidates for drug delivery systems. In this study, we performed molecular dynamics simulations of the inclusion complex of β-CD with cyclophosphamide (CP) at temperatures from 300 K to 400 K to investigate the temperature dependency of the release behaviour of CP and structural changes of β-CD in an aqueous solution. We analysed the distance between the centres of mass of β-CD and CP and the radius of gyration of β-CD. The CP molecule was released from the β-CD cavity at 400 K, whereas two different inclusion complexes, partially and completely, were observed at T < 400 K. β-CD encapsulating a CP molecule had a more spherical shape and rigidity than β-CD without a CP, and the rigidity of their inclusion complex decreased with increasing temperature. Our findings provide fundamental insights into the behaviours of the β-CD/CP complex and drug release at the molecular level and can facilitate the development of new temperature-responsive drug delivery systems with CD nanocarriers triggered by localised temperature increases using focused ultrasound.

We investigate the self-assembly of amphiphilic nanocubes into finite-sized aggregates in equilibrium and under shear, using molecular dynamics (MD) simulations and kinetic Monte Carlo (KMC) calculations.

This study investigates the self-assembly and phase transitions of cholesteric liquid crystals (CLCs) when confined in nanotubes, specifically focusing on the variations in their molecular structures. A dissipative particle dynamics method was used to investigate how the changes in helix radius ((Formula presented.)) and pitch ((Formula presented.)) affect the behaviour of the LCs. For pitches of 24, 12, and 6, the orientation order parameter ((Formula presented.)) showed distinct trends during cooling. Smaller helix radii resulted in isotropic to nematic to smectic phase transitions, whereas larger radii resulted in a novel smectic phase with spiral structures (Sm (Formula presented.)). Circumferential local-order parameters ((Formula presented.) and (Formula presented.)) were introduced to better characterise the phases, and a disordered spiral-structure phase (Sm (Formula presented.)) with local perturbations was observed. The transitions between isotropic, nematic, and smectic phases, highlighting the influence of the pitch and helix radius, were observed from the phase diagrams. Smaller pitches and radii prevented the formation of stable structures; however, specific combinations induced characteristic spiral structures in the smectic phase. These results provide new insights into the self-assembly of confined CLCs, which have potential applications in the design of photonic devices and LC-based sensors. This study advances our understanding of phase control in quasi-one-dimensional systems and highlights the importance of molecular variations in liquid crystal behaviour.

Molecular insight into the phase-separated interface formed when biodegradable polyesters and thermoplastic starch (TPS) are melt-blended is valuable for the design of composites. In this study, eight different interfaces combining four major biodegradable polyesters (PLA, PBS, PHB and PBAT) and two TPSs [unmodified TPS (nTPS) and citrate-modified TPS (cTPS)] were investigated by using molecular dynamics (MD) simulations. According to the MD simulation results, PBS, PHB and PBAT diffuse readily into the TPS and form compatible interfaces, whereas PLA is less compatible with the TPS. The results of tensile simulations show that PBS and PBAT adhere well to TPS; in particular, PBS/cTPS and PBAT/cTPS exhibit high interfacial-fracture energy (G). Both PLA and PHB blended with TPS exhibit low G because PLA is less compatible with TPS and PHB and TPS have low electrostatic interaction. The reason for the high G of PBS/cTPS and PBAT/cTPS is thought to be a combination of three factors: (i) formation of a deep compatible interface, (ii) suppression of void growth by electrostatic interactions and (iii) absorption of strain energy by a change in the conformation of the molecular chains. These three interfacial adhesion mechanisms should be considered when designing biodegradable polyester/TPS blends with good mechanical properties.

Blue phases (BPs) consist of three-dimensional self-assembled structures formed by a double-twisted columnar arrangement of liquid crystal molecules. Although their unique optical and structural properties render BPs particularly useful for applications such as liquid crystal displays, BPs typically appear in a narrow temperature range between the isotropic and nematic phases. This thermodynamic instability impedes their practical applicability. However, the simulations we present here showed that, in a quasi-one-dimensional system confined to nanospace, a phase equivalent to the BP appears and persists between the nematic and smectic phases. Confinement to a nanotube (NT) with a relatively small radius enables the BP to be maintained over a wide temperature range, whereas for an NT with a relatively larger radius, the BP appears only in a very narrow temperature range between the aforementioned phases. We additionally showed that the pitch of the BP is dependent on and can be controlled by adjusting the radius of the NTs. This finding has significant implications for the potential application of these materials in fields such as photonics and chiral separation technologies.

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.

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.

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.

Despite decades of intensive research, many questions remain on the formation and growth of the first cells on Earth. Here, we used computer simulation to compare the self-assembly process of ribonucleic acids in two environments: enclosed in a vesicle-cell membrane and in the bulk. The self-assembly was found to be more favoured in the former environment, and the origin of such a biointerface effect was identified. These results will contribute to a better understanding of the origin of life on the primitive Earth.

We investigate translocation dynamics of a vesicle cell under collision with a Janus or a homogeneous hydrophobic/hydrophilic nanoparticle. To this end, we perform dissipative particle dynamics simulation by setting the nanoparticle with different initial velocities, different chemical patterns of the surface for the nanoparticle, and different orientations (for the Janus nanoparticle). Particular attention is given to translocation dynamics, in-cell water discharge, and the late-stage morphologies of the vesicle/nanoparticle system after the collision. We observe three late-stage states for the Janus nanoparticle, and four late-stage states for the homogeneous nanoparticles. We find that the late-stage state and the associated dynamical pathway not only depend on the relative velocity but also on the chemical pattern of the nanoparticle surface, as well as on the orientation of the incident Janus nanoparticle. We have examined the time-dependent mean radius of the vesicle, the number of in-cell water beads lost from the vesicle, as well as the collision-induced pore size on the lipid membrane during the course of collision. Our simulation provides microscopic insights into the resilience of the vesicle-cell membrane and dynamical behavior of the vesicle under the attack of a foreign nanoparticle. Knowledge and insights gained through the simulation will have implication to the drug delivery with different chemical coatings. © The Royal Society of Chemistry 2013.

In this paper, a stochastic Hamiltonian formulation (SHF) is proposed and applied to dissipative particle dynamics (DPD) simulations. As an extension of Hamiltonian dynamics to stochastic dissipative systems, the SHF provides necessary foundations and great convenience for constructing efficient numerical integrators. As a first attempt, we develop the Störmer–Verlet type of schemes based on the SHF, which are structure-preserving for deterministic Hamiltonian systems without external forces, the dissipative forces in DPD. Long-time behaviour of the schemes is shown numerically by studying the damped Kubo oscillator. In particular, the proposed schemes include the conventional Groot–Warren's modified velocity-Verlet method and a modified version of Gibson–Chen–Chynoweth as special cases. The schemes are applied to DPD simulations and analysed numerically.

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.

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.

Surfactants, as a class of soft materials, exhibit a wide variety of self-assembled structures and physical properties due to their flexible molecular design. However, exploring their full potential remains difficult due to the complexity of their behavior in multicomponent systems. This study introduces an integrated approach that combines molecular simulations and machine learning to predict the structure and performance of aqueous surfactant formulations. Using dissipative particle dynamics, we reproduced and analyzed the self-assembly behavior of over 200 formulations of cleansing agents. While the overall morphology of aggregates showed limited correlation with cleansing performance, detailed analysis revealed that the spatial distribution of weakly hydrophobic components significantly influenced the result. Based on this insight, we constructed machine learning models using molecular descriptors to predict cleansing efficiency, achieving high accuracy with an Extra Tree Regressor. Furthermore, we performed in silico formulation screening to identify promising ingredient combinations. Additionally, a separate model was developed to predict the critical packing parameter from molecular structure using deep learning, achieving high accuracy. These results demonstrate that combining simulation and machine learning offers a powerful method for understanding and designing functional surfactant systems.

We investigate the structure and rheological properties of dilute colloid-polymer mixtures at rest and under shear via molecular simulations that take into account hydrodynamic interactions. Mixtures of amphiphilic Janus colloids (JCs) and hydrophobic/amphiphilic polymers are considered for various solvent qualities and polymer concentrations. Free polymers, small polymer droplets, and hybrid aggregates coexist in mixtures with slightly hydrophobic homopolymers. As the solvent quality worsens, all polymers aggregate into small droplets, covered and stabilized by the JCs. In mixtures with amphiphilic polymers, we observe the coexistence of free polymers, purely polymeric micelles, and hybrid aggregates. At low shear rates, all mixtures exhibit a Newtonian-like response with intrinsic shear viscosities that are up to 2 times as large as of pure suspensions of nonadsorbing colloids at the same concentration. Furthermore, the mean aggregation number increases slightly due to the flow-enhanced collision of aggregates. At larger shear rates, however, the aggregates break up, the polymers align in the flow direction, and the mixtures exhibit shear-thinning. This shear-induced breakup occurs at stronger shear compared to pure JC suspensions, indicating that the adsorbed polymers reinforce the hybrid aggregates.

In bulk water, surfactant molecules can self-assemble into a variety of morphologies, including spherical, cylindrical, and worm-like micelles, bilayers and vesicles. We have studied self-assembly of surfactant molecules in water within a nanotube. We present a simulation evidence of surfactant assemblies through adjusting the water- nanotube..

A micelle is the self-assembly of surfactant molecules formed in surfactant aqueous solution. The micelle has various forms such as a threadlike, spherical, discoid, and bilayer. Particularly, the threadlike micelle has the great possibility of the application in the industry, utilizing the uniqueness in its dynamics. However, an overall understanding of the dynamics of the threadlike micelle has not been accomplished, because of the so-called "mesoscopic problem" in dynamics. In this study to clarify the multiscale dynamics in the threadlike micelles we adopted the Dissipative Particle Dynamics(DPD) simulations.