arXiv subjects

Isao Tanaka

Publications and source records attributed to Isao Tanaka.

At least 37 records · Page 2Linked to original sources

arXiv2020

Derivative structure enumeration using binary decision diagram

A derivative structure is a nonequivalent substitutional atomic configuration derived from a given primitive cell. The enumeration of derivative structures plays an essential role in searching for the ground states in multicomponent systems. However, it is computationally hard to enumerate derivative structures if the number of derivative structures of a target system becomes huge. In the present study, we introduce a novel compact data structure of the zero-suppressed binary decision diagram (ZDD) to enumerate derivative structures much more efficiently. The present study shows its simple applications to the enumeration of structures derived from the face-centered cubic and hexagonal close-packed lattices in binary, ternary, and quaternary systems. The present ZDD-based procedure should significantly contribute not only to various computational approaches based on the derivative structures but also to a wide range of combinatorial issues in physics and materials science.

physics.comp-ph↗

arXiv2020

Phonon structure of titanium under shear deformation along $\{10\bar{1}2\}$ twinning mode

We investigated phonon behavior of hexagonal close packed titanium under homogeneous shear deformation corresponding to the $\{10\bar{1}2\}$ twinning mode using first-principles calculation and phonon calculation. By this deformation, we found that a phonon mode located at a point on Brillouin zone boundary is drastically soften increasing the shear and finally it triggers a spontaneous structural transition by breaking the crystal symmetry toward twin from parent.

cond-mat.mtrl-sci↗

arXiv2019

Growth of superconducting Sm(O,F)BiS2 single crystals

Superconducting Sm(O,F)BiS2 single crystals were successfully grown using KI-KCl flux. The obtained single crystals were flat-shaped and their size was 500um. The structure and composition of the obtained single crystals were obtained using X-ray diffraction and X-ray spectroscopy. The lattice constants of the obtained Sm(O,F)BiS2 single crystals were evaluated to be a = 3.9672(4) A and c = 13.417(6) A, while their F/(O + F) molar ratio was approximately 0.17. The superconducting transition temperature of the obtained Sm(O,F)BiS2 single crystals was 4.8 K. This was different from the reported Sm(O,F)BiS2 with no superconducting transition above 2 K. The superconducting anisotropies of the upper critical field and effective mass model of the obtained Sm(O,F)BiS2 single crystals were estimated to be approximately 26 and 10, respectively.

cond-mat.supr-con↗

arXiv2019

Growth and characterization of (La,Ce)OBiS2 single crystals

(La,Ce)OBiS2 single crystals are successfully grown using CsCl flux. The obtained single crystals have a plate-like shape with a size of 0.5-2.0 mm and a well-developed ab-plane. The thickness of the crystals increases with a decrease in the Ce content. The (La,Ce)OBiS2 single crystals exhibit superconducting properties. Moreover, the superconducting transition temperature increases with an increase in the Ce content. The obtained (La,Ce)OBiS2 single crystals exhibit a tetragonal structure and the valence state of Ce in the crystals is determined to be mixed with Ce3+ and Ce4+ based on X-ray absorption fine structure spectroscopy.

physics.app-ph↗

arXiv2019

Vibrational Effects in X-ray Absorption Spectra of 2D Layered Materials

With the examples of the C $K$-edge in graphite and the B $K$-edge in hexagonal BN, we demonstrate the impact of vibrational coupling and lattice distortions on the X-ray absorption near-edge structure (XANES) in 2D layered materials. Theoretical XANES spectra are obtained by solving the Bethe-Salpeter equation of many-body perturbation theory, including excitonic effects through the correlated motion of core-hole and excited electron. We show that accounting for zero-point motion is important for the interpretation and understanding of the measured X-ray absorption fine structure in both materials, in particular for describing the $σ^*$-peak structure.

cond-mat.mtrl-sci↗

arXiv2019

Growth and transport properties under high pressure of PrOBiS2 single crystals

PrOBiS2 single crystals were successfully grown using a KCl flux. The obtained crystals had a plate-like shape with a typical size of 0.5-1.0 mm and well-developed ab-plane. The Pr valence of the grown crystals, as determined by an X-ray absorption fine structure spectroscopy analysis, was almost trivalent. The PrOBiS2 single crystals did not exhibit superconductivity down to 0.25 K. The transport properties under high pressures up to 50 GPa ensured semiconducting behavior for 2-300 K using a diamond anvil cell.

cond-mat.supr-con↗

arXiv2019

Bulk superconductivity in La2O2M4S6-type layered oxychalcogenide La2O2Bi3Ag0.6Sn0.4S5.7Se0.3

Recently, we reported the observation of superconductivity at ~0.5 K in a La2O2M4S6-type (M: metal) layered oxychalcogenide La2O2Bi3AgS6, which is a layered compound related to the BiS2-based superconductor system but possesses a thicker Bi3AgS6-type conducting layer. In this study, we have developed the La2O2Bi3AgS6-type materials by element substitutions to increase the transition temperature (Tc) and to induce bulk nature of superconductivity. A resistivity anomaly observed at 180 K in La2O2Bi3AgS6 was systematically suppressed by Sn substitution for the Ag site. By the Sn substitution, Tc increased, and the shielding volume fraction estimated from magnetization measurements also increased. The highest Tc (= 2.3 K) and the highest shielding volume fraction (~20%) was observed for La2O2Bi3Ag0.6Sn0.4S6. The superconducting properties were further improved by Se substitutions for the S site. By the combinational substitutions of Sn and Se, bulk-superconducting phase of La2O2Bi3Ag0.6Sn0.4S5.7Se0.3 with a Tc of 3.0 K (Tconset = 3.6 K) was obtained.

cond-mat.supr-con↗

arXiv2019

Group-theoretical high-order rotational invariants for structural representations: Application to linearized machine learning interatomic potential

Many rotational invariants for crystal structure representations have been used to describe the structure-property relationship by machine learning. The machine learning interatomic potential (MLIP) is one of the applications of rotational invariants, which provides the relationship between the energy and the crystal structure. Since the MLIP requires the highest accuracy among machine learning estimations of the structure-property relationship, the enumeration of rotational invariants is useful for constructing MLIPs with the desired accuracy. In this study, we introduce high-order linearly independent rotational invariants up to the sixth order based on spherical harmonics and apply them to linearized MLIPs for elemental aluminum. A set of rotational invariants is derived by the general process of reducing the Kronecker products of irreducible representations (Irreps) for the SO(3) group using a group-theoretical projector method. A high predictive power for a wide range of structures is accomplished by using high-order invariants with low-order invariants equivalent to pair and angular structural features.

physics.comp-ph↗

arXiv2018

Growth and physical properties of Ce(O,F)Sb(S,Se)2 single crystals with site-selected chalcogen atoms

Ce(O,F)Sb(S,Se)2 single crystals were successfully grown using a CsCl/KCl flux method. The obtained crystals have a plate-like shape with the typical size of 1-2 mm and well-developed ab-plane, which enables X-ray single crystal structural analysis. The Ce(O,F)Sb(S,Se)2 crystallizes in a monoclinic space group, P21/m, with lattice parameters of a = 4.121(7) A, b = 4.109(7) A, c = 13.233(15) A, beta = 97.94(7) deg. It is composed of alternate stacking of Ce-(O,F) and Sb-SSe layers, and the Sb-SSe layer includes selective occupation of Se atoms in its in-plane site. The valence state of Ce is estimated to be Ce3+ by X-ray absorption fine spectroscopy analysis. The single crystals show an insulating behavior, and a magnetic ordering around 6 K.

cond-mat.supr-con↗

arXiv2018

Pressure-induced Insulator to Metal Transition of Mixed Valence Compound Ce(O,F)SbS$_{2}$

Transport properties of Ce$_{0.85}$F0.15SbS$_{2}$ and undoped CeOSbS$_{2}$ under high pressure were investigated experimentally and theoretically. Electrical resistivity measurements of the Ce$_{0.85}$F0.15SbS$_{2}$ single crystals were performed under various high pressures using a diamond anvil cell with boron-doped diamond electrodes. The samples showed the insulator to metal transition by applying high pressure up to 30-40 GPa. On the other hand, the undoped CeOSbS$_{2}$ showed almost same transport property with the F-doped sample under high pressure. The valence state analysis using X-ray photoelectron spectroscopy revealed a simple valence state of Ce3+ in Ce$_{0.85}$F0.15SbS$_{2}$ and mixed valence state between Ce3+ and Ce4+ in undoped CeOSbS$_{2}$. The valence fluctuation in Ce carried out the comparable transport nature in the both samples. A band calculation suggests that the undoped CeOSbS$_{2}$ could be metallic under high pressure of 30 GPa in accordance with the experimental results. A superior thermoelectric property of power factor in CeOSbS$_{2}$ was estimated under high pressure around 20 GPa in comparison with that of ambient pressure.

cond-mat.mtrl-sci↗

arXiv2018

Lattice thermal conductivities of two SiO$_2$ polymorphs by first-principles calculation and phonon Boltzmann transport equation

Lattice thermal conductivities of two SiO$_2$ polymorphs, i.e., $α$-quartz (low) and $α$-cristobalite (low), were studied using first-principles anharmonic phonon calculation and linearized phonon Boltzmann transport equation. Although $α$-quartz and $α$-cristobalite have similar phonon densities of states, phonon frequency dependencies of phonon group velocities and lifetimes are dissimilar, which results in largely different anisotropies of the lattice thermal conductivities. For $α$-quartz and $α$-cristobalite, distributions of the phonon lifetimes effective to determine the lattice thermal conductivities are well described by energy and momentum conservations of three phonon scatterings weighted by phonon occupation numbers and one parameter that represents the phonon-phonon interaction strengths.

cond-mat.mtrl-sci↗

arXiv2017

Coexistence of superconductivity and charge-density wave in the quasi-one-dimensional material HfTe3

We present the first experimental evidence for metallicity, superconductivity (SC) and the co-existence of charge density waves (CDW) in the quasi-one-dimensional material HfTe3. The existence of such phenomena is a typical characteristic of the transition metal chalcogenides however, without the application of hydrostatic pressure/chemical doping, it is rare for a material to exhibit the co-existence of both states. Materials such as HfTe3 can therefore provide us with a unique insight into the relationship between these multiple ordered states. By improving on the original synthesis conditions, we have successfully synthesised single phase HfTe3 and confirmed the resultant structure by performing Rietveld refinement. Using low temperature resistivity measurements, we provide the first experimental evidence of SC at ~1.4 K as well as a resistive anomaly indicative of a CDW formation at ~82 K. By the application of hydrostatic-pressure, the resistivity anomaly shifts to higher temperature. The results show that HfTe3 is a promising new material to help study the relationship between SC and CDW.

cond-mat.supr-con↗

arXiv2017

Compositional descriptor-based recommender system accelerating the materials discovery

Structures and properties of many inorganic compounds have been collected historically. However, it only covers a very small portion of possible inorganic crystals, which implies the presence of numerous currently unknown compounds. A powerful machine-learning strategy is mandatory to discover new inorganic compounds from all chemical combinations. Herein we propose a descriptor-based recommender-system approach to estimate the relevance of chemical compositions where stable crystals can be formed [i.e., chemically relevant compositions (CRCs)]. As well as data-driven compositional similarity used in the literature, the use of compositional descriptors as a prior knowledge can accelerate the discovery of new compounds. We validate our recommender systems in two ways. Firstly, one database is used to construct a model, while another is used for the validation. Secondly, we estimate the phase stability for compounds at expected CRCs using density functional theory calculations.

cond-mat.mtrl-sci↗

arXiv2017

Linearized machine-learning interatomic potentials for non-magnetic elemental metals: Limitation of pairwise descriptors and trend of predictive power

Machine-learning interatomic potential (MLIP) has been of growing interest as a useful method to describe the energetics of systems of interest. In the present study, we examine the accuracy of linearized pairwise MLIPs and angular-dependent MLIPs for 31 elemental metals. Using all of the optimal MLIPs for 31 elemental metals, we show the robustness of the linearized frameworks, the general trend of the predictive power of MLIPs and the limitation of pairwise MLIPs. As a result, we obtain accurate MLIPs for all 31 elements using the same linearized framework. This indicates that the use of numerous descriptors is the most important practical feature for constructing MLIPs with high accuracy. An accurate MLIP can be constructed using only pairwise descriptors for most non-transition metals, whereas it is very important to consider angular-dependent descriptors when expressing interatomic interactions of transition metals.

cond-mat.mtrl-sci↗

arXiv2017

Matrix- and tensor-based recommender systems for the discovery of currently unknown inorganic compounds

Chemically relevant compositions (CRCs) and atomic arrangements of inorganic compounds have been collected as inorganic crystal structure databases. Machine-learning is a unique approach to search for currently unknown CRCs from vast candidates. Herein we propose matrix- and tensor-based recommender system approaches to predict currently unknown CRCs from database entries of CRCs. Firstly, the performance of the recommender system approaches to discover currently unknown CRCs is examined. A Tucker decomposition recommender system shows the best discovery rate of CRCs as the majority of the top 100 recommended ternary and quaternary compositions correspond to CRCs. Secondly, systematic density functional theory (DFT) calculations are performed to investigate the phase stability of the recommended currently unknown CRCs. The phase stability of the 27 compositions reveals that 23 currently unknown compounds are stable. These results indicate that the recommender system has great potential to accelerate the discovery of new compounds.

cond-mat.mtrl-sci↗

arXiv2017

Descriptors for Machine Learning of Materials Data

Descriptors, which are representations of compounds, play an essential role in machine learning of materials data. Although many representations of elements and structures of compounds are known, these representations are difficult to use as descriptors in their unchanged forms. This chapter shows how compounds in a dataset can be represented as descriptors and applied to machine-learning models for materials datasets.

cond-mat.mtrl-sci↗

arXiv2017

DynaPhoPy: A code for extracting phonon quasiparticles from molecular dynamics simulations

We have developed a computational code, DynaPhoPy, that allow us to extract the microscopic anharmonic phonon properties from molecular dynamics (MD) simulations using the normal-mode-decomposition technique as presented by Sun et al. [T. Sun, D. Zhang, R. Wentzcovitch, 2014]. Using this code we calculated the quasiparticle phonon frequencies and linewidths of crystalline silicon at different temperatures using both of first-principles and the Tersoff empirical potential approaches. In this work we show the dependence of these properties on the temperature using both approaches and compare them with reported experimental data obtained by Raman spectroscopy [M. Balkanski, R. Wallis, E. Haro, 1983 and R. Tsu, J. G. Hernandez, 1982].

cond-mat.mtrl-sci↗

arXiv2017

Conceptual and practical bases for the high accuracy of machine learning interatomic potential

Machine learning interatomic potentials (MLIPs) based on a large dataset obtained by density functional theory (DFT) calculation have been developed recently. This study gives both conceptual and practical bases for the high accuracy of MLIPs, although MLIPs have been considered to be simply an accurate black-box description of atomic energy. We also construct the most accurate MLIP of the elemental Ti ever reported using a linearized MLIP framework and many angular-dependent descriptors, which also corresponds to a generalization of the modified embedded atom method (MEAM) potential.

cond-mat.mtrl-sci↗