Masanobu Nakayama

Professor

Nagoya Institute of Technology

Japan

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Professor Masanobu Nakayama holds a position at the Nagoya Institute of Technology in Japan. His research areas focus on ion transport dynamics in sodium and lithium materials, enhancing battery performance through molecular simulations and experimental studies. Recent publications include investigations into ionic conductivity in various materials and the optimization of solid electrolyte compositions.

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Collaborators (3)

Naoaki Yabuuchi

Professor

Yokohama National University

JAPAN

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Toru Asaka

Associate Professor

Nagoya Institute of Technology

JAPAN

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Naoto Tanibata

Nagoya Institute of Technology

JAPAN

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Masanobu Nakayama

Research Interests

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About

Articles (20)

A comprehensive exploration of Na+ ion transport in NaSICONs using molecular dynamics simulations

Causal Analysis of Factors for Li Ionic Conductivity in Olivine-Type LiMXO4 Materials Using LiNGAM

Designing Metastable P3-type Layered Negative Electrodes with High Na Vacancy Concentration for High-Power Sodium-Ion Batteries

Efficient optimization of atom/ion arrangements in crystalline solids using genetic algorithms and machine-learning regression

Experimental data-driven efficient exploration of the composition and process conditions of Li-rich NASICON-type solid electrolytes

Experimental study on Na+ conductivity in NaAlBr4 and atomic-scale investigation of Na+ conduction

Fast Anion Redox by Amorphization in Sodium-Ion Batteries

Multicomponentization of a super-Na ionic conductor chloride NaTaCl6, enhancing ionic conductivity and electronic resistivity

Sintering aid effect of La2Zr1.4Ta0.6O7/Li6.4La3Zr1.4Ta0.6O12 nanocomposite in garnet-type solid-state electrolyte

Transition-Metal Dependence of Anion Redox Reversibility in Amorphous Electrodes

Octahedral Tilting and Modulation Structure in Perovskite‐Related Compound La1/3NbO3

Synthesis and structural characterization of U-phase, [3Ca2Al(OH)6][Na(H2O)6(SO4)2·6H2O] layered double hydroxide

Chemical Composition Data-Driven Machine-Learning Prediction for Phase Stability and Materials Properties of Inorganic Crystalline Solids

Density Functional Theory Studies on Li Metal Electrode/Garnet-Type Li<sub>7</sub>La<sub>3</sub>Zr<sub>2</sub>O<sub>12</sub> Solid Electrolyte Interfaces for Application in All-Solid-State Batteries

Non-equilibrium molecular dynamics study on atomistic origin of grain boundary resistivity in NASICON-type Li-ion conductor

Catalytic mechanism of spinel oxides for oxidative electrolyte decomposition in Mg rechargeable batteries

Density Functional Theory and Machine Learning-Based Analyses for Improved Surface Stability of a BaTiO<sub>3</sub>-Coated LiCoO<sub>2</sub> Positive Electrode Material

Efficient Experimental Search for Discovering a Fast Li-Ion Conductor from a Perovskite-Type Li <sub>x</sub>La<sub>(1- x)/3</sub>NbO<sub>3</sub> (LLNO) Solid-State Electrolyte Using Bayesian Optimization

Exploring the diffusion mechanism of Li ions in different modulated arrangements of La<sub>(1-X)/3</sub>Li<sub>x</sub>NbO<sub>3</sub> with fitted force fields obtained via a metaheuristic algorithm

First-Principles DFT Study on Inverse Ruddlesden-Popper Tetragonal Compounds as Solid Electrolytes for All-Solid-State Li<sup>+</sup>-Ion Batteries

Collaborators (3)

Naoaki Yabuuchi

Toru Asaka

Naoto Tanibata

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