Adaptive plasticity of auxetic Kirigami hydrogel fabricated from anisotropic swelling of cellulose nanofiber film.

Hydrogels are flexible materials that typically accommodate elongation with positive Poisson's ratios. Auxetic property, i.e.

Analytical model of critical buckling transition for smectic liquid crystal based on the viscoelastic scaling of coarse-grained molecular dynamics.

The buckling transition of smectic liquid crystals (LCs) is important not only as fundamental physics but also for the rational design of devices to make use of their optical and mechanical properties. However, there exists a huge gap between the specific knowledge and universal analytical formulation. We have conducted coarse-grained molecular dynamics (CGMD) simulations with the force field optimized for the description of buckling phenomena including topological defects to link the molecular nature and continuum formulation.

Swelling-based gelation of wet cellulose nanopaper evaluated by single particle tracking.

Nanopapers fabricated from cellulose nanofibers (CNFs) drastically swell to form hydrogels when they are in contact with water. This gelation makes contrast with conventional papers that simply deform without drastic volume increase. While the volume increase is qualitatively obvious from the macroscopic visual inspection, its quantitative understanding is nontrivial because of the difficulty in the detection of the boundary between the nanopaper hydrogel and the residual or extra water.

Resilient Mechanical Metamaterial Based on Cellulose Nanopaper with Kirigami Structure.

Nanopapers fabricated from cellulose nanofibers (CNFs) are flexible for bending while they are rather stiff against stretching, which is a common feature shared by conventional paper-based materials in contrast with typical elastomers. Cellulose nanopapers have therefore been expected to be adopted in flexible device applications, but their lack of stretching flexibility can be a bottleneck for specific situations. The high stretching flexibility of nanopapers can effectively be realized by the implementation of Kirigami structures, but there has never been discussion on the mechanical resilience where stretching is not a single event.

Derivation of coarse-grained force fields for buckling-induced topological defects of liquid crystals.

Microscopic details of buckling-induced topological defects are required for molecular design of smectic liquid crystals to control buckling instability of the layers. In this study, we present a multiobjective optimization method to derive the coarse-grained (CG) force fields with sufficiently precise buckling characteristics including the molecular details for molecular dynamics (MD) simulations. We perform CGMD simulations of buckling deformation at sample points in the CG force field parameter space, from which the response surfaces of objective functions such as the scalar orientational order parameters, critical angles of layer collapse, and radial distribution functions are estimated.

Partial structural order of gel-forming material detected as multimodal subdiffusion by logarithmic measure.

Fibrous nanomaterials suspended in liquid form gel structures when the binding sites between the components reach sufficient number densities. Cellulose nanofibers (CNFs) are one of such nanomaterials, and transparent papers are fabricated by drying their aqueous dispersions. It is therefore important to characterize the wet state, but the specific fluorescent marker molecules are not available for arbitrary CNFs.

Spatio-temporally controlled suppression of the coffee-ring phenomenon by cellulose nanofibers.

Sessile droplets of colloidal dispersions tend to exhibit the coffee-ring phenomenon in the drying process. The suspended particles are transported especially at the final stage of the drying process, which is called the rush hour. Conventional inkjet printers require the ink liquid to have a sufficiently low viscosity for inkjet discharge, but such liquids tend to be subject to the coffee-ring effect.

Fundamentals of the logarithmic measure for revealing multimodal diffusion.

We develop a theoretical foundation for a time-series analysis method suitable for revealing the spectrum of diffusion coefficients in mixed Brownian systems, for which no prior knowledge of particle distinction is required. This method is directly relevant for particle tracking in biological systems, in which diffusion processes are often nonuniform. We transform Brownian data onto the logarithmic domain, in which the coefficients for individual modes of diffusion appear as distinct spectral peaks in the probability density.

Spatiotemporal Dynamics of Laser-Induced Molecular Crystal Precursors Visualized by Particle Image Diffusometry.

We have succeeded in label-free visualization of spatiotemporal dynamics of laser-induced crystal precursors in aqueous solutions. The tracking-free evaluation of the diffusion-coefficient field for the observation domain with tens of micrometers on a side from microscopy movie data is realized by particle image diffusometry (PID). PID revealed the time fluctuation of coverage composition with the nonuniform space distribution of diffusion coefficients by the prenucleation clusters.

Soft trapping lasts longer: Dwell time of a Brownian particle varied by potential shape.

It is often regarded that the dwell time (or residence time, escape time, trapping duration) of trapped Brownian particles is described by the multiplication of two separate factors, i.e., the diffusive traveling time of the trapping domain size without taking into account the trapping force, and the stochastic event of overcoming the trapping energy by thermal one instantaneously.

Characterization of aqueous cellulose nanofiber dispersions from microscopy movie data of Brownian particles by trajectory analysis.

Cellulose nanofibers (CNFs) are promising for various applications such as substrates of flexible devices and reinforcement materials. Most of these applications require control of the drying process of the aqueous CNF dispersions. However, the existing reports examine the surface of dried materials because scanning electron microscopy (SEM) and atomic force microscopy (AFM) are not compatible with either the wet conditions or structure inside the materials.

Estimation of diffusive states from single-particle trajectory in heterogeneous medium using machine-learning methods.

We propose a novel approach to analyze random walks in heterogeneous medium using a hybrid machine-learning method based on a gamma mixture and a hidden Markov model. A gamma mixture and a hidden Markov model respectively provide the number and the most probable sequence of diffusive states from the time series position data of particles/molecules obtained by single-particle/molecule tracking (SPT/SMT) method. We evaluate the performance of our proposed method for numerically generated trajectories.

Negative thermophoresis of nanoparticles interacting with fluids through a purely-repulsive potential.

Thermophoretic forces acting on nanoparticles are investigated using molecular dynamics simulation. We assume the Lennard-Jones (LJ) potential for the interaction between fluid molecules. On the other hand, the interaction between the nanoparticle and the surrounding fluid molecules are assumed to be either LJ or Weeks-Chandler-Andersen (WCA) potential, where the latter is purely-repulsive.

Suspended particle transport through constriction channel with Brownian motion.

It is well known that translocation events of a polymer or rod through pores or narrower parts of micro- and nanochannels have a stochastic nature due to the Brownian motion. However, it is not clear whether the objects of interest need to have a larger size than the entrance to exhibit the deviation from the dynamics of the surrounding fluid. We show by numerical analysis that the particle injection into the narrower part of the channel is affected by thermal fluctuation, where the particles have spherical symmetry and are smaller than the height of the constriction.

Suppressing the coffee-ring effect of colloidal droplets by dispersed cellulose nanofibers.

We report that the addition of a small amount of cellulose nanofibers (CNFs) into an aqueous dispersion of colloidal particles suppresses the coffee-ring effect when the dispersion dries on a solid substrate, as revealed by the computational analysis of experimental time-series images and by particle image velocimetry. The addition of CNFs is much more effective than the increase of colloidal particle concentration at the same weight percentage; it is also more environment friendly than the use of typical molecular surfactants. This finding is promising for the fabrication of metamaterials from colloidal dispersions and for ink printing in electronics, where CNFs can also serve as a substrate for flexible devices.

Faster Convergence of Diffusion Anisotropy Detection by Three-Step Relation of Single-Particle Trajectory.

We focus on the issue of limited number of samples in the single particle tracking (SPT) when trying to extract the diffusion anisotropy that originates from the particle asymmetry. We propose a novel evaluation technique of SPT making use of the relation of the consecutive three steps. More specifically, the trend of the angle comprised of the three positions and the displacements are plotted on a scatter diagram.

Departure of microscopic friction from macroscopic drag in molecular fluid dynamics.

Friction coefficient of the Langevin equation and drag of spherical macroscopic objects in steady flow at low Reynolds numbers are usually regarded as equivalent. We show that the microscopic friction can be different from the macroscopic drag when the mass is taken into account for particles with comparable scale to the surrounding fluid molecules. We illustrate it numerically by molecular dynamics simulation of chloride ion in water.

Coarse-grained picture of Brownian motion in water: Role of size and interaction distance range on the nature of randomness.

The Brownian motion of a particle in a fluid is often described by the linear Langevin equation, in which it is assumed that the mass of the particle is sufficiently large compared to the surrounding fluid molecules. This assumption leads to a diffusion coefficient that is independent of the particle mass. The Stokes-Einstein equation indicates that the diffusion coefficient depends solely on the particle size, but the concept of size can be ambiguous when close to the molecular scale.

Evaluation of bacterial motility from non-Gaussianity of finite-sample trajectories using the large deviation principle.

Motility of bacteria is usually recognized in the trajectory data and compared with Brownian motion, but the diffusion coefficient is insufficient to evaluate it. In this paper, we propose a method based on the large deviation principle. We show that it can be used to evaluate the non-Gaussian characteristics of model Escherichia coli motions and to distinguish combinations of the mean running duration and running speed that lead to the same diffusion coefficient.

Detection of diffusion anisotropy due to particle asymmetry from single-particle tracking of Brownian motion by the large-deviation principle.

We show that the diffusion anisotropy due to the asymmetry of the particle can be extracted from the trajectory data without the information of the particle orientation. The subject of analysis is typical in single-particle tracking (SPT) experiments, and the analysis is based on the large-deviation principle in mathematics. We consider the model system of Langevin equations in two dimensions where a particle diffusion shows anisotropy depending on a single parameter defined by the two diffusion coefficients in the perpendicular directions of the frame fixed to the particle.

Coarse-grained molecular dynamics simulations of shear-induced instabilities of lipid bilayer membranes in water.

We study shear-induced instabilities of lipid bilayers immersed in water using coarse-grained molecular dynamics simulations. The shear imposed by the flow of the water induces initially microscopic structural changes of the membrane, starting with tilting of the molecules in the direction of the shear. The tilting propagates in the spanwise direction when the shear rate exceeds a critical value and the membrane undergoes a bucklinglike deformation in the direction perpendicular to the shear.

Molecular dynamics of a water jet from a carbon nanotube.

A carbon nanotube (CNT) can be viewed as a molecular nozzle. It has a cylindrical shape of atomistic regularity, and the diameter can be even less than 1 nm. We have conducted molecular-dynamics simulations of water jet from a (6,6) CNT that confines water in a form of single-file molecular chain.

Hydrogen bond dynamics and microscopic structure of confined water inside carbon nanotubes.

We have investigated the density and temperature dependences of microscopic structure and hydrogen bond dynamics of water inside carbon nanotubes (CNTs) using molecular dynamics simulation. The CNTs are treated as rigid, and smoothly truncated extended simple point charge water model is adopted. The results show that as the overall density increases, the atomic density profiles of water inside CNTs become sharper, the peaks shift closer to the wall, and a new peak of hydrogen atomic density appears between the first (outermost) and second layer.

Flow structure of water in carbon nanotubes: poiseuille type or plug-like?

We have conducted molecular dynamics simulations of water flow in carbon nanotubes (CNTs) for (6,6) to (20,20) CNTs at a streaming velocity of 100 ms. The fluidized piston model (FPM) and the ice piston model (IPM) are employed to drive flow through the CNTs. The results show that the single-file water flow inside (6,6) CNT has a convex upward streaming velocity profile, whereas the velocity profiles in (10,10) to (20,20) CNTs are flat except near the tube wall.