Noriyoshi Arai 교수

We study self-assembly and polymorphic transitions of surfactant molecules in water within a nanotube and the effect of water-nanotube interactions on the self-assembly morphologies. We present a simulation evidence of a cornucopia of polymorphic structures of surfactant assemblies--many of which have not been observed in bulk solutions--through adjusting the water-nanotube chemical interactions which range from hydrophilic to hydroneutral and to hydrophobic. The ability to control the morpholog

More than 100 micros dissipative particle dynamics simulations were carried out to investigate the spontaneous formation process of threadlike micelles from the random configuration for surfactant molecules. Stable spherical micelles were formed during the earlier stage. These spherical micelles fused to each other and grew into rodlike and threadlike micelles during the later stage. The length and radius of a micelle were estimated by tracing the backbone positions and the distance between the

A vesicle in a cell is an enclosed structure in which the interior fluid is encompassed by a lipid bilayer. Synthetic vesicles are known as the liposomes. Liposomes with a single phospholipid bilayer are called unilamellar liposomes; otherwise, they are called multilamellar liposomes or onion-like liposomes (vesicles). One prototype synthetic onion-like vesicle, namely, onion-like dendrimersomes, have been recently produced via the self-assembly of amphiphilic Janus dendrimers (Proc. Natl. Acad.

We have performed molecular simulations to investigate morphologies and the phase diagram of the self-assembled triblock Janus nanoparticle confined to nanotubes. The triblock Janus nanoparticle is decorated with two hydrophobic caps at the north and south poles with a tunable area, separated by an electrically charged middle band. On the basis of the observed pressure- and tube-radius-dependent morphologies, we derive semiquantitative phase diagrams of the axial pressure versus the ratio of the

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 u

Researchers have studied the origin of life and the process of evolution on early Earth for decades. However, we lack a comprehensive understanding of biogenesis, because there are many stages in the formation and growth of the first cell. We investigate the self-replication processes of coacervate protocells using computer simulations of single-chain lipid and phospholipid aqueous mixtures. Based on a morphological phase diagram, we develop a model of prebiotic self-replication driven by only e

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 ha

Water transport must be efficiency controlled for the future sustainability of life. Various water transport systems using carbon nanotubes have been proposed in recent years. Although these systems are more permeable than aquaporins, their water transport is passive. In this study, we successfully demonstrate an active water pump driven by simple hydrophobic interaction through computer simulation. Even in the absence of a pressure- or density-gradient, the proposed pump can actively transport

On basis of molecular simulation of confined surfactant solutions, we show that by adding chemical patterns on the inner surface of nanochannels dynamical properties of the confined surfactant solutions could be modified from shear thinning to shear thickening. To this end, we select uniformly hydrophobic and hydrophilic surfaces as well as a stripe-patterned Janus surface as three prototype confining surfaces of nanochannels. In all three nanochannels, when the surfactant solution is under rela

How do lipid molecules in membranes perform a flip-flop? The flip-flops of lipid molecules play a crucial role in the formation and flexibility of membranes. However, little has been determined about the behavior of flip-flops, either experimentally, or in molecular dynamics simulations. Here, we provide numerical results of the flip-flops of model lipid molecules in a model membrane and investigate the statistical properties, using millisecond-order coarse-grained molecular simulations (dissipa

The "asymmetric Brownian ratchet model", a variation of Feynman's ratchet and pawl system, is invoked to understand the kinesin walking behavior along a microtubule. The model system, consisting of a motor and a rail, can exhibit two distinct binding states, namely, the random Brownian state and the asymmetric potential state. When the system is transformed back and forth between the two states, the motor can be driven to "walk" in one direction. Previously, we suggested a fundamental mechanism,

Molecular dynamics (MD) simulations, which are central to drug discovery, offer detailed insights into protein-ligand interactions. However, analyzing large MD datasets remains a challenge. Current machine-learning solutions are predominantly supervised and have data labelling and standardisation issues. In this study, we adopted an unsupervised deep-learning framework, previously benchmarked for rigid proteins, to study the more flexible SARS-CoV-2 main protease (M^pro). We ran MD sim

Core–shell nanoparticles are nanosized particles that consist of a core and a shell, constructed from different metallic elements. Core–shell nanoparticles have received extensive attention, owing to their various potential applications such as paints, optical films and catalysts. Herein, we investigate the melting behaviours of different core–shell nanoparticles under continuous heating using molecular dynamics simulation. Different metallic elements were examined as core–shell and pure nanopar

The "asymmetric brownian ratchet model" is a variation of Feynman's ratchet and pawl system proposed. In this model, a system consisting of a motor and a rail has two binding states. One is the random brownian state, and the other is the asymmetric potential state. When the system is alternatively switched between these states, the motor can be driven in one direction. This model is believed to explain nanomotor behavior in biological systems. The feasibility of the model has been demonstrated u

We used machine learning to predict the self-assembly structures of amphiphilic molecules and analyzed the physical factors affecting their morphologies.