arXiv subjects

Akihide Kuwabara

Publications and source records attributed to Akihide Kuwabara.

8 recordsLinked to original sources

arXiv2026

Refining hydrogen positions in α-FeOOH through combined neutron diffraction and computational techniques

The hydrogen positions and magnetic structure of goethite $α$-FeOOH, a key component of iron rust, were examined through neutron diffraction. All symmetry-allowed magnetic structures under the space group $Pnma$ with the magnetic wavevector $\vec{q}_{\rm m} = (0, 0, 0)$ r.l.u. were analysed using irreducible representation and magnetic space group approaches. The magnetic moments aligned along the $b$-axis form antiferromagnetic spin arrangements, as reproduced by first-principles calculations. Accurately determining the hydrogen positions is crucial for understanding the mechanism of catalytic reduction of CO$_2$ in $α$-FeOOH. These positions were precisely identified through diffraction and calculations, highlighting the effectiveness of using both methods for undeuterated compounds.

cond-mat.mtrl-sci↗

arXiv2023

Lattice dynamics and ferroelectric properties of the nitride perovskite ${\mathrm{LaWN}}_{3}$

Using first-principles calculations we examine the crystal structures and phase transitions of nitride perovskite LaWN$_3$. Lattice dynamics calculations indicate that the ground-state structure belongs to space group $R3c$. Two competitive phase transition pathways are identified which are characterized by symmetry-adapted distortion modes. The results suggest that $R3c$ LaWN$_3$ should be an excellent ferroelectric semiconductor: its large spontaneous polarization of around 61 $μ$C/cm$^2$ is comparable to that of PbTiO$_3$, and its band gap is about 1.72 eV. Ferroelectricity is found to result from the \emph{B}-site instability driven by hybridization between W-5$d$ and N-2$p$ orbitals. These properties make LaWN$_3$ an attractive candidate material for use in ferroelectric memory devices and photovoltaic cells.

cond-mat.mtrl-sci↗

arXiv2022

Facilitating {\it ab initio} configurational sampling of multicomponent solids using an on-lattice neural network model and active learning

We propose a scheme for {\it ab initio} configurational sampling in multicomponent crystalline solids using Behler-Parinello type neural network potentials (NNPs) in an unconventional way: the NNPs are trained to predict the energies of relaxed structures from the perfect lattice with configurational disorder instead of the usual way of training to predict energies as functions of continuous atom coordinates. An active learning scheme is employed to obtain a training set containing configurations of thermodynamic relevance. This enables bypassing of the structural relaxation procedure which is necessary when applying conventional NNP approaches to the lattice configuration problem. The idea is demonstrated on the calculation of the temperature dependence of the degree of A/B site inversion in three spinel oxides, MgAl$_2$O$_4$, ZnAl$_2$O$_4$, and MgGa$_2$O$_4$. The present scheme may serve as an alternative to cluster expansion for `difficult' systems, e.g., complex bulk or interface systems with many components and sublattices that are relevant to many technological applications today.

physics.comp-ph↗

arXiv2020

Hidden Ladder in SrMoO$_3$/SrTiO$_3$ Superlattices: Experiments and Theoretical Calculations

A double-layered perovskite oxide Sr$_3$Mo$_2$O$_7$ is considered a "hidden ladder" system with wide and narrow bands near the Fermi level, for which high-$T_{\rm c}$ superconductivity is expected. However, the difficulty in synthesis, especially in the preparation of samples without oxygen deficiency, can hinder the observation of superconductivity. In this study, we constructed a double-layer SrMoO$_3$ block through artificial superlattices with the insulating SrTiO$_3$ block, (SrMoO$_3$)$_m$/(SrTiO$_3$)$_t$ ($m = 2, 4$; $t = 4$). First-principles calculations for bilayered SrMoO$_3$ ($m = 2$) exhibit a wide-narrow band structure near the Fermi level, which bears a close resemblance to Sr$_3$Mo$_2$O$_7$. The dispersion along the $k_z$ direction is strongly suppressed by increasing the number of the SrTiO$_3$ layers, $t$. However, no superconductivity is observed down to 0.1 K. We discuss the absence of the superconductivity for the present films on the basis of results of scanning transmission electron microscopy and band structure calculations.

cond-mat.str-el↗

arXiv2018

Exploring a potential energy surface by machine learning for characterizing atomic transport

We propose a machine-learning method for evaluating the potential barrier governing atomic transport based on the preferential selection of dominant points for the atomic transport. The proposed method generates numerous random samples of the entire potential energy surface (PES) from a probabilistic Gaussian process model of the PES, which enables defining the likelihood of the dominant points. The robustness and efficiency of the method are demonstrated on a dozen model cases for proton diffusion in oxides, in comparison with a conventional nudge elastic band method.

physics.chem-ph↗

arXiv2017

On the Structural Origin of the Catalytic Properties of Inherently Strained Ultrasmall Decahedral Gold Nanoparticles

A new mechanism for reactivity of multiply twinned gold nanoparticles resulting from their inherently strained structure provides a further explanation of the surprising catalytic activity of small gold nanoparticles. Atomic defect structural studies of surface strains and quantitative analysis of atomic column displacements in the decahedral structure observed by aberration corrected transmission electron microscopy reveal an average expansion of surface nearest neighbor distances of 5.6 percent, with many strained by more than 10 percent. Density functional theory calculations of the resulting modified gold d-band states predict significantly enhanced activity for carbon monoxide oxidation. The new insights have important implications for the applications of nanoparticles in chemical process technology, including for heterogeneous catalysis.

physics.chem-ph↗

arXiv2015

A machine learning-based selective sampling procedure for identifying the low energy region in a potential energy surface: a case study on proton conduction in oxides

In this paper, we propose a selective sampling procedure to preferentially evaluate a potential energy surface (PES) in a part of the configuration space governing a physical property of interest. The proposed sampling procedure is based on a machine learning method called the Gaussian process (GP), which is used to construct a statistical model of the PES for identifying the region of interest in the configuration space. We demonstrate the efficacy of the proposed procedure for atomic diffusion and ionic conduction, specifically the proton conduction in a well-studied proton-conducting oxide, barium zirconate BaZrO3. The results of the demonstration study indicate that our procedure can efficiently identify the low-energy region characterizing the proton conduction in the host crystal lattice, and that the descriptors used for the statistical PES model have a great influence on the performance.

cond-mat.mtrl-sci↗

arXiv2012

Ferroelectricity Driven by Twisting of Silicate Tetrahedral Chains

Conventional perovskite-type ferroelectrics are based on octahedral units of oxygen, and often comprise toxic Pb to achieve robust ferroelectricity. Here, we report the ferroelectricity in a silicate-based compound, Bi2SiO5 (BSO), induced by a structural instability of the corresponding silicate tetrahedral chains. A low-energy phonon mode condenses at ~ 673 K to induce the proper ferroelectric phase transition. Polarization switching was observed in a BSO single crystal with a coercive field of 30 kV/cm and a spontaneous polarization of 0.3 microC/cm2 along a direction normal to the cleavage plane. The in-plane polarization was estimated by first principles calculations to be 23 microC/cm2. The present findings provide a new guideline for designing ferroelectric materials based on SiO4 tetrahedral units, which is ubiquitously found in natural minerals.

cond-mat.mtrl-sci↗