Yusuke Noda

Geometry dependence of electronic and energetic properties of one-dimensional peanut-shaped fullerene polymers.

In the present study, we investigate different types of 1D peanut-shaped fullerene polymers (PSFPs) using density functional theory to understand the electronic states and the energetic stability of curved carbon nanomaterials. We generated 53 different models of the 1D PSFPs by means of the generalized Stone-Wales transformations and performed structural optimization for each model. Band structures of the 1D PSFPs exhibit either metallic or semiconducting property according to the geometrical structures. We find that the energetic stability of the 1D PSFPs depends on the geometry: the more octagon and pentagon-octagon pairs (heptagons and hexagon-heptagon pairs) in their geometrical structures, the more stable (unstable) the 1D PSFPs.

Tomonaga-Luttinger liquid theory for metallic fullurene polymers

We investigate the low energy behavior of local density of states in metallic

Tunable Seebeck Coefficient in Monolayer Graphene Under Periodic Potentials

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A general representation scheme for crystalline solids based on Voronoi-tessellation real feature values and atomic property data

polymers theoretically. The multichannel bosonization method is applied to electronic band structures evaluated from first-principles calculation, by which the effects of electronic correlation and nanoscale corrugation in the atomic configuration are fully taken into account. We obtain a closed-form expression for the power-law anomalies in the local density of states, which successfully describes the experimental observation on the

Crystal Structure and Band-Gap Engineering of a Semiconducting Coordination Polymer Consisting of Copper(I) Bromide and a Bridging Acceptor Ligand

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Research Update: Ca doping effect on the Li-ion conductivity in NASICON-type solid electrolyte LiZr2(PO4)3: A first-principles molecular dynamics study

polymers in a quantitative manner. An important implication from the closed-form solution is the existence of an experimentally unobserved crossover at nearly a hundred milli-electron volts, beyond which the power-law exponent of the

Weakly spin-dependent band structures of antiferromagnetic perovskite LaMO3 (M = Cr, Mn, Fe)

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Momentum-dependent band spin splitting in semiconducting MnO 2

polymers should change significantly.

Phenomenological Kinetics of the Carbonation Reaction of Lithium Hydroxide Monohydrate: Role of Surface Product Layer and Possible Existence of a Liquid Phase

The effect of the superlattice potential on the Seebeck coefficient tensor of graphene sheet is theoretically investigated. Strong anisotropy of the Seebeck coefficient tensor is observed. The origin of the anisotropy can be attributed to the modification of the dispersion relation in the vicinity of the Dirac point. Our finding shows that the magnitude of the Seebeck coefficient of graphene can be flexibly changed under a superlattice potential.

Momentum-dependent band spin splitting in semiconducting MnO2: a density functional calculation

Abstract Increasing attention has been paid to materials informatics approaches that promise efficient and fast discovery and optimization of functional inorganic materials. Technical breakthrough is urgently requested to advance this field and efforts have been made in the development of materials descriptors to encode or represent characteristics of crystalline solids, such as chemical composition, crystal structure, electronic structure, etc. We propose a general representation scheme for crystalline solids that lifts restrictions on atom ordering, cell periodicity, and system cell size based on structural descriptors of directly binned Voronoi-tessellation real feature values and atomic/chemical descriptors based on the electronegativity of elements in the crystal. Comparison was made vs. radial distribution function (RDF) feature vector, in terms of predictive accuracy on density functional theory (DFT) material properties: cohesive energy (CE), density (d), electronic band gap (BG), and decomposition energy (Ed). It was confirmed that the proposed feature vector from Voronoi real value binning generally outperforms the RDF-based one for the prediction of aforementioned properties. Together with electronegativity-based features, Voronoi-tessellation features from a given crystal structure that are derived from second-nearest neighbor information contribute significantly towards prediction.