Dynamic Correlation Analysis between Stress-Strain Curve and Polymer Film Structure Using Persistent Homology.

Coarse-grained molecular dynamics (CG-MD) simulations and subsequent persistent homology (PH) analysis were performed to correlate the structure and stress-strain behavior of polymer films. During uniaxial tensile MD simulations, the first principal component of the persistence diagram obtained by principal component analysis (PCA) was in good agreement with the stress-strain curve. This indicates that PH + PCA can identify critical ring structures relevant to the dynamic changes in MD simulations without requiring any prior knowledge.

Predicting long-term trends in physical properties from short-term molecular dynamics simulations using long short-term memory.

This study proposes a novel long short-term memory (LSTM)-based model for predicting future physical properties based on partial data of molecular dynamics (MD) simulation. It extracts latent vectors from atomic coordinates of MD simulations using graph convolutional network, utilizes LSTM to learn temporal trends in latent vectors and make one-step-ahead predictions of physical properties through fully connected layers. Validating with MD simulations of Ni solid-liquid systems, the model achieved accurate one-step-ahead prediction for time variation of the potential energy during solidification and melting processes using residual connections.

Molecular Dynamics Simulation of Adhesion of Additive Molecules in Paint Materials toward Enhancement of Anticorrosion Performance.

Adsorption energies of additive molecules in paint materials on the iron oxide substrate are investigated by molecular dynamics (MD) simulations to find the key feature of adhesion, which is one of the indispensable elements for the corrosion resistance of coated materials. Both edge-on and face-on adsorptions are observed for most additive molecules such as phenylsuccinic acid and benzoic acid. On the other hand, only the edge-on adsorption is observed for the specific molecule having a benzothiazole ring due to the effect of steric conformation.

Predicting materials properties with generative models: applying generative adversarial networks for heat flux generation.

In the realm of materials science, the integration of machine learning techniques has ushered in a transformative era. This study delves into the innovative application of generative adversarial networks (GANs) for generating heat flux data, a pivotal step in predicting lattice thermal conductivity within metallic materials. Leveraging GANs, this research explores the generation of meaningful heat flux data, which has a high degree of similarity with that calculated by molecular dynamics simulations.

Free energy surface of initial cap formation in carbon nanotube growth.

Initial cap formation is an important process of carbon nanotube (CNT) growth where a hexagonal carbon network is lifted off from the catalyst surface. In this study, free energy surface (FES) of initial cap formation in the CNT growth is investigated by metadynamics simulation. A two-dimensional collective variable (CV) space is newly developed to examine the complicated formation process of the cap structure, which consists of the formation of a hexagonal carbon network and lift-off of the network from the catalyst surface.

Ultrastrong underwater adhesion on diverse substrates using non-canonical phenolic groups.

Robust underwater adhesion is challenging because a hydration layer impedes the interaction between substrates and adhesives. Phenolic adhesives inspired by marine creatures such as mussels were extensively studied, but these adhesives have not reached the adhesion strength and substrate diversity of Man-made dry adhesives. Here, we report a class of ultrastrong underwater adhesives with molecular phenolic designs extending beyond what nature has produced.

Fast-Decoding Algorithm for Electrode Processes at Electrified Interfaces by Mean-Field Kinetic Model and Bayesian Data Assimilation: An Active-Data-Mining Approach for the Efficient Search and Discovery of Electrocatalysts.

The microscopic origins of the activity and selectivity of electrocatalysts has been a long-lasting enigma since the 19th century. By applying an active-data-mining approach, employing a mean-field kinetic model and a statistical approach of Bayesian data assimilation, we demonstrate here a fast decoding to extract key properties in the kinetics of complicated electrode processes from current-potential profiles in experimental and literary data. As the proof-of-concept, kinetic parameters on the four-electron oxygen reduction reaction in the 0.

Non-classical nucleation in vapor-liquid-solid growth of monolayer WS revealed by in-situ monitoring chemical vapor deposition.

The very early nucleation stage of a transition metal dichalcogenide (TMD) was directly observed with in-situ monitoring of chemical vapor deposition and automated image analysis. Unique nucleation dynamics, such as very large critical nuclei and slow to rapid growth transitions, were observed during the vapor-liquid-solid (VLS) growth of monolayer tungsten disulfide (WS). This can be explained by two-step nucleation, also known as non-classical nucleation, in which metastable clusters are formed through the aggregation of droplets.

Bayesian Data Assimilation of Temperature Dependence of Solid-Liquid Interfacial Properties of Nickel.

Temperature dependence of solid-liquid interfacial properties during crystal growth in nickel was investigated by ensemble Kalman filter (EnKF)-based data assimilation, in which the phase-field simulation was combined with atomic configurations of molecular dynamics (MD) simulation. Negative temperature dependence was found in the solid-liquid interfacial energy, the kinetic coefficient, and their anisotropy parameters from simultaneous estimation of four parameters. On the other hand, it is difficult to obtain a concrete value for the anisotropy parameter of solid-liquid interfacial energy since this factor is less influential for the MD simulation of crystal growth at high undercooling temperatures.

Free energy barriers from biased molecular dynamics simulations.

Atomistic simulation methods for the quantification of free energies are in wide use. These methods operate by sampling the probability density of a system along a small set of suitable collective variables (CVs), which is, in turn, expressed in the form of a free energy surface (FES). This definition of the FES can capture the relative stability of metastable states but not that of the transition state because the barrier height is not invariant to the choice of CVs.

Bayesian inference of solid-liquid interfacial properties out of equilibrium.

Solid-liquid interfacial properties out of equilibrium provide the essential information required for understanding and controlling solidification microstructures in metallic materials. However, few studies have attempted to reveal all interfacial properties out of equilibrium in detail. The present study proposes an approach for simultaneously estimating all interfacial properties in a pure metal below the melting point on the basis of the Bayesian inference theory.

Variational formulation of a quantitative phase-field model for nonisothermal solidification in a multicomponent alloy.

A variational formulation of a quantitative phase-field model is presented for nonisothermal solidification in a multicomponent alloy with two-sided asymmetric diffusion. The essential ingredient of this formulation is that the diffusion fluxes for conserved variables in both the liquid and solid are separately derived from functional derivatives of the total entropy and then these fluxes are related to each other on the basis of the local equilibrium conditions. In the present formulation, the cross-coupling terms between the phase-field and conserved variables naturally arise in the phase-field equation and diffusion equations, one of which corresponds to the antitrapping current, the phenomenological correction term in early nonvariational models.

Preferential synthesis of (6,4) single-walled carbon nanotubes by controlling oxidation degree of Co catalyst.

Chirality-selective synthesis of single-walled carbon nanotubes (SWNTs) has been a research goal for the last two decades and is still challenging due to the difficulty in controlling the atomic structure in the one-dimensional material. Here, we develop an optimized approach for controlling the chirality of species by tuning the oxidation degree of Co catalyst. Predominant synthesis of (6,4) SWNTs is realized for the first time.

Effects of CO adsorption on proton migration on a hydrated ZrO surface: an ab initio molecular dynamics study.

Hydration reactions on a carbonate-terminated cubic ZrO(110) surface were analyzed using ab initio molecular dynamics (AIMD) simulations. After hydration reactions, carbonates were still present on the surface at 500 K. However, these carbonates are very weak conjugate bases and only act as steric hindrance in proton hopping processes between acidic chemisorbed HO molecules (Zr-OH) and monodentate hydroxyl groups (Zr-OH).

Heterogeneity in homogeneous nucleation from billion-atom molecular dynamics simulation of solidification of pure metal.

Can completely homogeneous nucleation occur? Large scale molecular dynamics simulations performed on a graphics-processing-unit rich supercomputer can shed light on this long-standing issue. Here, a billion-atom molecular dynamics simulation of homogeneous nucleation from an undercooled iron melt reveals that some satellite-like small grains surrounding previously formed large grains exist in the middle of the nucleation process, which are not distributed uniformly. At the same time, grains with a twin boundary are formed by heterogeneous nucleation from the surface of the previously formed grains.

Wafer-scale fabrication and growth dynamics of suspended graphene nanoribbon arrays.

Adding a mechanical degree of freedom to the electrical and optical properties of atomically thin materials can provide an excellent platform to investigate various optoelectrical physics and devices with mechanical motion interaction. The large scale fabrication of such atomically thin materials with suspended structures remains a challenge. Here we demonstrate the wafer-scale bottom-up synthesis of suspended graphene nanoribbon arrays (over 1,000,000 graphene nanoribbons in 2 × 2 cm(2) substrate) with a very high yield (over 98%).

Variational formulation and numerical accuracy of a quantitative phase-field model for binary alloy solidification with two-sided diffusion.

We present the variational formulation of a quantitative phase-field model for isothermal low-speed solidification in a binary dilute alloy with diffusion in the solid. In the present formulation, cross-coupling terms between the phase field and composition field, including the so-called antitrapping current, naturally arise in the time evolution equations. One of the essential ingredients in the present formulation is the utilization of tensor diffusivity instead of scalar diffusivity.

Homogeneous nucleation and microstructure evolution in million-atom molecular dynamics simulation.

Homogeneous nucleation from an undercooled iron melt is investigated by the statistical sampling of million-atom molecular dynamics (MD) simulations performed on a graphics processing unit (GPU). Fifty independent instances of isothermal MD calculations with one million atoms in a quasi-two-dimensional cell over a nanosecond reveal that the nucleation rate and the incubation time of nucleation as functions of temperature have characteristic shapes with a nose at the critical temperature. This indicates that thermally activated homogeneous nucleation occurs spontaneously in MD simulations without any inducing factor, whereas most previous studies have employed factors such as pressure, surface effect, and continuous cooling to induce nucleation.

Atomistic modelling of CVD synthesis of carbon nanotubes and graphene.

We discuss the synthesis of carbon nanotubes (CNTs) and graphene by catalytic chemical vapour deposition (CCVD) and plasma-enhanced CVD (PECVD), summarising the state-of-the-art understanding of mechanisms controlling their growth rate, chiral angle, number of layers (walls), diameter, length and quality (defects), before presenting a new model for 2D nucleation of a graphene sheet from amorphous carbon on a nickel surface. Although many groups have modelled this process using a variety of techniques, we ask whether there are any complementary ideas emerging from the different proposed growth mechanisms, and whether different modelling techniques can give the same answers for a given mechanism. Subsequently, by comparing the results of tight-binding, semi-empirical molecular orbital theory and reactive bond order force field calculations, we demonstrate that graphene on crystalline Ni(111) is thermodynamically stable with respect to the corresponding amorphous metal and carbon structures.

Catalyzed growth of carbon nanotube with definable chirality by hybrid molecular dynamics-force biased Monte Carlo simulations.

Metal-catalyzed growth mechanisms of carbon nanotubes (CNTs) were studied by hybrid molecular dynamics-Monte Carlo simulations using a recently developed ReaxFF reactive force field. Using this novel approach, including relaxation effects, a CNT with definable chirality is obtained, and a step-by-step atomistic description of the nucleation process is presented. Both root and tip growth mechanisms are observed.

Phase transition in substrate-supported molybdenum nanoparticles: a molecular dynamics study.

The phase transition between liquid and solid phases of substrate-supported molybdenum nanoparticles with size ranging from 2000 to 16,000 atoms was investigated using molecular dynamics simulation. The effect of the interaction energy between the nanoparticle and the substrate on the contact angle, melting point and nucleation temperature was focused on. Unidirectional solidification and inward melting after surface melting were observed in the substrate-supported nanoparticles during cooling and heating, respectively.

A multiscale approach for modeling the early stage growth of single and multiwall carbon nanotubes produced by a metal-catalyzed synthesis process.

A parametrized mesoscale model for the early stage growth of isolated single or multiwall carbon nanotubes (CNTs) has been developed in order to investigate the effects of metal catalyst particle size and composition on CNT growth mechanism during synthesis via a substrate-supported, catalytic chemical vapor deposition process. The model is based on a coarse-grained graphene sheet, represented by a two-dimensional simply connected triangular mesh, with parameters for the surface curvature, bond stretching, carbon-carbon interaction, and carbon-catalyst interaction determined by classical molecular dynamics simulations using a bond-order potential derived from ab initio calculations. The mesoscale simulations show that the initial type of CNT growth is strongly influenced by the surface interaction energy between the graphene sheet and metal catalyst particle, rate of carbon deposition, and particle size.

A molecular dynamics study of the phase transition in bcc metal nanoparticles.

The phase transition between liquid and solid phases in body-centered cubic (bcc) metal nanoparticles of iron, chromium, molybdenum, and tungsten with size ranging from 2000 to 31,250 atoms was investigated using a molecular dynamics simulation. The nucleation from an undercooled liquid droplet was observed during cooling in all nanoparticles considered. It was found that a nucleus was generated near one side of the particle and solidification spread toward the other side the during nucleation process.

Direction control of chemical wave propagation in self-oscillating gel array.

A chemomechanical actuator utilizing a reaction-diffusion wave across gap junction was constructed toward a novel mircoconveyer by micropatterned self-oscillating gel array. Unidirectional propagation of the chemical wave of the Belousov-Zhabotinsky (BZ) reaction was induced on gel arrays. In the case of using a triangle-shaped gel as an element of the array, the chemical wave propagated from the corner side of the triangle gel to the plane side of the other gel (C-to-P) across the gap junction, whereas it propagated from the plane side to the corner side (P-to-C) in the case of the pentagonal gel array.

Generation of single-walled carbon nanotubes from alcohol and generation mechanism by molecular dynamics simulations.

Recent advances in high-purity and high-yield catalytic chemical vapor deposition (CVD) generation of single-walled carbon nanotubes (SWNTs) from alcohol are comprehensively presented and discussed on the basis of results obtained from both experimental and numerical investigations. We have uniquely adopted alcohol as a carbon feedstock, and this has resulted in high-quality, low-temperature synthesis of SWNTs. This technique can produce SWNTs even at a very low temperature of 550 degrees C, which is about 300 degrees C lower than the conventional CVD methods in which methane or acetylene is typically used.