Kaoru Kimura
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View article: Starrydata: from published plots to shared materials data
Starrydata: from published plots to shared materials data Open
We have developed the Starrydata2 web system, an open, web-based database for collecting and organizing experimental material property data from the literature. It assists users worldwide in extracting and sharing curve data from plot imag…
View article: Comprehensive experimental datasets of quasicrystals and their approximants
Comprehensive experimental datasets of quasicrystals and their approximants Open
Quasicrystals are solid-state materials that typically exhibit unique symmetries, such as icosahedral or decagonal diffraction symmetry. They were first discovered in 1984. Over the past four decades of quasicrystal research, around 100 st…
View article: CSD 2287687: Experimental Crystal Structure Determination
CSD 2287687: Experimental Crystal Structure Determination Open
An entry from the Inorganic Crystal Structure Database, the world’s repository for inorganic crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely availabl…
View article: CSD 2287686: Experimental Crystal Structure Determination
CSD 2287686: Experimental Crystal Structure Determination Open
An entry from the Inorganic Crystal Structure Database, the world’s repository for inorganic crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely availabl…
View article: CSD 2287688: Experimental Crystal Structure Determination
CSD 2287688: Experimental Crystal Structure Determination Open
An entry from the Inorganic Crystal Structure Database, the world’s repository for inorganic crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely availabl…
View article: Phase Equilibria in Aluminium–Ruthenium–Silicon System near 1200 Kelvin
Phase Equilibria in Aluminium–Ruthenium–Silicon System near 1200 Kelvin Open
A narrow-gap semiconductor with a complex crystal structure was recently discovered in the Al–Ru–Si system. To determine the homogeneity range of the semiconductor phase and further discover new phases, phase equilibria in the Al–Ru–Si sys…
View article: Deep Learning Enables Rapid Identification of a New Quasicrystal from Multiphase Powder Diffraction Patterns
Deep Learning Enables Rapid Identification of a New Quasicrystal from Multiphase Powder Diffraction Patterns Open
Since the discovery of the quasicrystal, approximately 100 stable quasicrystals are identified. To date, the existence of quasicrystals is verified using transmission electron microscopy; however, this technique requires significantly more…
View article: CSD 2297115: Experimental Crystal Structure Determination
CSD 2297115: Experimental Crystal Structure Determination Open
An entry from the Inorganic Crystal Structure Database, the world’s repository for inorganic crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely availabl…
View article: Crystal structures of five compounds in the aluminium–ruthenium–silicon system
Crystal structures of five compounds in the aluminium–ruthenium–silicon system Open
Single crystals of five compounds with approximate compositions ∼Ru 16 (Al 0.78 Si 0.22 ) 47 , (I), ∼Ru 9 (Al 0.70 Si 0.30 ) 32 , (II), ∼Ru 10 (Al 0.67 Si 0.33 ) 41 , (III), ∼Ru(Al 0.57 Si 0.43 ) 5 , (IV), and ∼Ru 2 (Al 0.46 Si 0.54 ) 9 , …
View article: CSD 2297119: Experimental Crystal Structure Determination
CSD 2297119: Experimental Crystal Structure Determination Open
An entry from the Inorganic Crystal Structure Database, the world’s repository for inorganic crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely availabl…
View article: Quasicrystals predicted and discovered by machine learning
Quasicrystals predicted and discovered by machine learning Open
Quasicrystals represent a class of ordered materials that have diffraction symmetry forbidden in periodic crystals. Since the first discovery of quasicrystals in 1984, approximately 100 thermodynamically stable quasicrystals have been synt…
View article: Atomic diffusion due to hyperatomic fluctuation for quasicrystals
Atomic diffusion due to hyperatomic fluctuation for quasicrystals Open
A quasicrystal is an ordered but non-periodic structure understood as a projection from a higher dimensional periodic structure. Some physical properties of quasicrystals are different from those of conventional solids. An anomalous increa…
View article: Machine Learning to Predict Quasicrystals from Chemical Compositions (Adv. Mater. 36/2021)
Machine Learning to Predict Quasicrystals from Chemical Compositions (Adv. Mater. 36/2021) Open
Quasicrystals In article number 2102507, Kaoru Kimura, Ryo Yoshida, and co-workers demonstrate that machine-learning algorithms can predict the chemical composition of new quasicrystals. Furthermore, analyzing the input–output relationship…
View article: Exploration of new quasicrystals and approximants by using machine learning
Exploration of new quasicrystals and approximants by using machine learning Open
Very recently, Liu et.al. proposed a machine learning (ML) approach to distinguishing quasicrystals (QCs) and related approximants (ACs) from ordinary crystals.[1] They built a supervised ML model that classifies any given chemical composi…
View article: Machine Learning to Predict Quasicrystals from Chemical Compositions
Machine Learning to Predict Quasicrystals from Chemical Compositions Open
Quasicrystals have emerged as the third class of solid‐state materials, distinguished from periodic crystals and amorphous solids, which have long‐range order without periodicity exhibiting rotational symmetries that are disallowed for per…
View article: Bonding Heterogeneity in Mixed-Anion Compounds Realizes Ultralow Lattice Thermal Conductivity
Bonding Heterogeneity in Mixed-Anion Compounds Realizes Ultralow Lattice Thermal Conductivity Open
Crystalline materials with intrinsically low lattice thermal conductivity ( κ lat ) pave the way towards high performance in various energy applications, including thermoelectrics. Here we demonstrate a strategy to realize ultralow κ lat u…
View article: Bonding Heterogeneity in Mixed-Anion Compounds Realizes Ultralow Lattice Thermal Conductivity
Bonding Heterogeneity in Mixed-Anion Compounds Realizes Ultralow Lattice Thermal Conductivity Open
Crystalline materials with intrinsically low lattice thermal conductivity (κlat) pave the way towards high performance in various energy applications, including thermoelectrics. Here we demonstrate a strategy to realize ultralow κlat using…
View article: PREFACE
PREFACE Open
The discovery of quasicrystals, with high symmetry impossible for three-dimensional periodic crystals, has brought about a paradigm shift in crystallography and has completely changed the definition of crystals that have been accepted for …
View article: Possibility of Semiconducting Electronic Structure on Al–Pd–Co 1/1 Cubic Quasicrystalline Approximant
Possibility of Semiconducting Electronic Structure on Al–Pd–Co 1/1 Cubic Quasicrystalline Approximant Open
Search for high-order semiconducting quasicrystalline approximants can play an essential role in finding clues to the discovery of semiconducting quasicrystals. According to the previous theoretical work, a model of Al–Pd–Co 1/1 cubic quas…
View article: Interband Contribution to Thermoelectric Properties of Al–Cu–Ir Quasicrystalline Approximant
Interband Contribution to Thermoelectric Properties of Al–Cu–Ir Quasicrystalline Approximant Open
Thermoelectric properties of quasicrystalline approximants have been reasonably described by the semiclassical Boltzmann transport theory under the empirical constant-diffusivity approximation. To investigate why the approximation could pr…