Fast simulation for multi-photon, atomic-ensemble quantum model of linear optical systems addressing the curse of dimensionality.

Photons are elementary particles of light in quantum mechanics, whose dynamics can be difficult to gain detailed insights, especially in complex systems. Simulation is a promising tool to resolve this issue, but it must address the curse of dimensionality, namely, that the number of bases increases exponentially in the number of photons. Here we mitigate this dimensionality scaling by focusing on optical systems composed of linear optical objects, modeled as an ensemble of two-level atoms. We decompose the time evolutionary operator on multiple photons into a group of time evolution operators acting on a single photon. Since the dimension of a single-photon time evolution operator is exponentially smaller than that of a multi-photon one in the number of photons, the decomposition enables the multi-photon simulations to be performed at a much lower computational cost. We apply this method to basic single- and multi-photon phenomena, such as Hong-Ou-Mandel interference and violation of the Bell-CHSH inequality, and confirm that the calculated properties are quantitatively comparable to the experimental results. Furthermore, our method visualizes the spatial propagation of photons hence provides insights that aid experiment designs for quantum-enabled technologies.

Accurate Multiscale Simulation of Frictional Interfaces by Quantum Mechanics/Green's Function Molecular Dynamics.

Understanding frictional phenomena is a fascinating fundamental problem with huge potential impact on energy saving. Such an understanding requires monitoring what happens at the sliding buried interface, which is almost inaccessible by experiments. Simulations represent powerful tools in this context, yet a methodological step forward is needed to fully capture the multiscale nature of the frictional phenomena. Here, we present a multiscale approach based on linked ab initio and Green's function molecular dynamics, which is above the state-of-the-art techniques used in computational tribology as it allows for a realistic description of both the interfacial chemistry and energy dissipation due to bulk phonons in nonequilibrium conditions. By considering a technologically relevant system composed of two diamond surfaces with different degrees of passivation, we show that the presented method can be used not only for monitoring in real-time tribolochemical phenomena such as the tribologically induced surface graphitization and passivation effects but also for estimating realistic friction coefficients. This opens the way to in silico experiments of tribology to test materials to reduce friction prior to that in real labs.

Fast evaluation technique for the shear viscosity and ionic conductivity of electrolyte solutions.

With the growing need to obtain ideal materials for various applications, there is an increasing interest in computational methods to rapidly and accurately search for materials. Molecular dynamics simulation is one of the successful methods used to investigate liquid electrolytes with high transport properties applied in lithium-ion batteries. However, further reduction in computational cost is required to find a novel material with the desired properties from a large number of combinations. In this study, we demonstrate an effective fast evaluation technique for shear viscosity and ionic conductivity by molecular dynamics simulation for an exhaustive search of electrolyte materials with high transport properties. The proposed model was combined with a short-time correlation function of the stress tensor and empirical relationships to address the issues of inefficient and uncertain evaluation by conventional molecular dynamics methods. Because we focus on liquid electrolytes consisting of organic solvents and lithium salts, our model requires dissociation ratio and effective diffusion size of lithium salts. Our method is applied to search for the compositional combinations of electrolytes with superior transport properties even at low temperatures. These results correlate well with experimental results.

Synthesis and Ion-Transport Properties of EuKGe2O6-, Ca3Fe2Ge3O12-, and BaCu2Ge2O7-Type Oxide-Ion Conductors.

EuKGe2O6-, Ca3Fe2Ge3O12-, and BaCu2Ge2O7-type germanates are synthesized by a conventional solid-state method and characterized to reveal their oxide-ion-conducting properties. Materials of the EuKGe2O6 group exhibit oxide-ion conductivity (e.g., 4.6 × 10-3 S/cm at 973 K for Eu0.8Ca0.2KGe2O6-δ) and transport numbers above 96%, whereas materials of the Ca3Fe2Ge3O12 and BaCu2Ge2O7 groups exhibit mixed electron-/oxide-ion conduction. Conduction involves oxide-ion vacancies in the EuKGe2O6 group, interstitial oxide ions in the Ca3Fe2Ge3O12 group, and both oxide-ion vacancies and interstitial oxide ions in the BaCu2Ge2O7 group. The doping-induced formation of impurity phases decreases the amount of oxide-ion carriers relative to the expected values.

Self-Learning Molecular Design for High Lithium-Ion Conductive Ionic Liquids using Maze Game.

A self-learning artificial intelligence system for an autonomous molecular search was recently utilized in place of laborious material development processes by humans. In this approach, because the evaluation of unsuitable or unrealistic candidates considerably decreases the search efficiency, prior knowledge of the chemistry and engineering requirements should be embedded into the molecular-generative algorithm. However, when using naive rule-based restrictions, one must implement the complex rule logic into the code each time, depending on the materials and potential applications. Herein, we propose a molecular-generative method using a maze game to control the allowable constituent fragments of molecules, which improves the flexibility and consistency to implement the rules. We performed an autonomous search for optimized cation structures of high Li-ion conductive ionic liquids evaluated by molecular dynamics simulations, in its practically reasonable scope defined by the maze game. From the search, we discover that acyl ammonium cations are favorable for high Li-ion conductivity because of the high association between the cations and Li ions. These results broaden our existing insight owing to the ability to explore beyond our practical experiences.

Search for high-capacity oxygen storage materials by materials informatics.

Oxygen storage materials (OSMs), such as pyrochlore type CeO2-ZrO2 (p-CZ), are used as a catalyst support for three-way catalysts in automotive emission control systems. They have oxygen storage capacity (OSC), which is the ability to release and store oxygen reversibly by the fluctuation of cation oxidation states depending on the reducing or oxidizing atmosphere. In this study, we explore high-capacity OSMs by using materials informatics (MI) combining experiments, first-principles calculations, and machine learning (ML). To generate training data for the ML model, the OSC values of 60 metal oxides were measured from the amount of CO2 produced under alternating flow gas between oxidizing (O2) and reducing (CO) conditions at 973, 773, and 573 K. Descriptors were computed by atomic properties and first-principles calculations on each oxide. The support vector machine regression model was trained to predict the OSC at each temperature. The features describing OSC were automatically selected using grid search to achieve practical cross validation performance. The features related to the stability of the oxygen atoms in the crystal and the crystal structure itself such as cohesive energy are highly correlated with OSC. The present model predicts the OSC of 1300 existing oxides. Based on its high predictive power for OSC and synthesizability, we focused on Cu3Nb2O8. We synthesized this material and experimentally confirmed that Cu3Nb2O8 showed a higher OSC than conventional OSM p-CZ. This MI scheme can significantly accelerate the development of new OSMs.

A Universal 3D Voxel Descriptor for Solid-State Material Informatics with Deep Convolutional Neural Networks.

Material informatics (MI) is a promising approach to liberate us from the time-consuming Edisonian (trial and error) process for material discoveries, driven by machine-learning algorithms. Several descriptors, which are encoded material features to feed computers, were proposed in the last few decades. Especially to solid systems, however, their insufficient representations of three dimensionality of field quantities such as electron distributions and local potentials have critically hindered broad and practical successes of the solid-state MI. We develop a simple, generic 3D voxel descriptor that compacts any field quantities, in such a suitable way to implement convolutional neural networks (CNNs). We examine the 3D voxel descriptor encoded from the electron distribution by a regression test with 680 oxides data. The present scheme outperforms other existing descriptors in the prediction of Hartree energies that are significantly relevant to the long-wavelength distribution of the valence electrons. The results indicate that this scheme can forecast any functionals of field quantities just by learning sufficient amount of data, if there is an explicit correlation between the target properties and field quantities. This 3D descriptor opens a way to import prominent CNNs-based algorithms of supervised, semi-supervised and reinforcement learnings into the solid-state MI.

Nanotribological Characterization of Lubricants between Smooth Iron Surfaces.

We performed the resonance shear measurement (RSM) for evaluating the nanorheological and tribological properties of model lubricants, hexadecane and poly(α-olefin) (PAO), confined between iron surfaces. The twin-path surface forces apparatus (SFA) was used for determining the distance between the surfaces. The obtained resonance curves for the confined lubricants showed that the viscosity of the confined hexadecane and PAO increased due to liquid structuring when the surface separation (D) decreased to a value less than 24 and 20 nm, respectively. It was also determined that the iron surfaces were lubricated by the hexadecane when normal load (L) was less than 1.1 mN, while the confined hexadecane behaved almost solid-like and showed poor lubricity when L was greater than 1.1 mN. In contrast, PAO between the iron surfaces showed high lubricity even under the high load (L > 2 mN). The surface separation of hexadecane and PAO at a hard wall contact between the iron surfaces was determined to be 4.6 ± 0.5 and 5.0 ± 0.4 nm by applying the fringes of equal chromatic order (FECO) for half-transparent iron films deposited on mica surfaces as substrates. We also characterized hexadecane and PAO confined between mica surfaces for studying the effect of substrates on the confined lubricants.

Green's function nonequilibrium molecular dynamics method for solid surfaces and interfaces.

This study presents a comprehensive procedure to calculate the exact dynamic Green's function of a harmonic semi-infinite solid and the time trajectories of the atoms, in the framework of the Green's function molecular dynamics. This Green's function properly describes the energy dissipation caused by excitations of the surface phonons, and the simulated atoms serve as well-defined thermo- and barostats for the nonequilibrium surface and interface systems. Moreover, the use of the exact dynamic Green's function coupled with a fast convolution algorithm significantly improves both the accuracy and the computing speed. The presented method is applied to a diamond (001) surface, and the results demonstrate that the properties of the nonreflecting boundary, the thermal fluctuations, and the energy dissipations involving long-wavelength phonons are correctly reproduced. These distinctive performances potentially allow us to reveal the nonequilibrium phenomena in a wide spectrum of applications such as catalysis, thermal transport, fracture mechanics, mechanochemistry, and tribology.

Tunneling Desorption of Single Hydrogen on the Surface of Titanium Dioxide.

We investigated the reaction mechanism of the desorption of single hydrogen from a titanium dioxide surface excited by the tip of a scanning tunneling microscope (STM). Analysis of the desorption yield, in combination with theoretical calculations, indicates the crucial role played by the applied electric field. Instead of facilitating desorption by reducing the barrier height, the applied electric field causes a reduction in the barrier width, which, when coupled with the electron excitation induced by the STM tip, leads to the tunneling desorption of the hydrogen. A significant reduction in the desorption yield was observed when deuterium was used instead of hydrogen, providing further support for the tunneling-desorption mechanism.

Mechanism of ultra low friction of multilayer graphene studied by coarse-grained molecular simulation.

Coarse-grained Metropolis Monte Carlo Brownian Dynamics simulations are used to clarify the ultralow friction mechanism of a transfer film of multilayered graphene sheets. Each circular graphene sheet consists of 400 to 1,000,000 atoms confined between the upper and lower sliders and are allowed to move in 3 translational and 1 rotational directions due to thermal motion at 300 K. The sheet-sheet interaction energy is calculated by the sum of the pair potential of the sp2 carbons. The sliding simulations are done by moving the upper slider at a constant velocity. In the monolayer case, the friction force shows a stick-slip like curve and the average of the force is high. In the multilayer case, the friction force does not show any oscillation and the average of the force is very low. This is because the entire transfer film has an internal degree of freedom in the multilayer case and the lowest sheet of the layer is able to follow the equipotential surface of the lower slider.

First-principles calculations of hydrogen diffusion on rutile TiO2(110) surfaces.

Density functional calculations are performed to study the H-atom diffusion on titanium dioxide (110) surface in the cases of water-molecule dissociation and splitting of the adjacent hydroxyl OH pair. It is shown that, when a water molecule is adsorbed at a surface oxygen-vacancy site, a fragment H atom of the water molecule tends to diffuse toward the nearest-neighboring bridging-oxygen sites by using a straight-line or relay-point path. As the result, a pair of surface hydroxyl OH is formed on the same oxygen row. In a thermal process, on the other hand, such OH pair favorably splits only by using a relay-point path, i.e., by transferring one H atom from a bridging-oxygen site to a next-neighboring one along the same oxygen row by way of another in-plane oxygen site. We found that the latter splitting reaction is activated around room temperature.