Fuyuki Shimojo 研究室

主宰者：Fuyuki Shimojo

熊本大学

AI 要約（直近 5 年の研究成果）

Fuyuki Shimojo 研究室は、原子・電子レベルの挙動を計算機で調べることで、新しい機能を持つ材料や現象を理解する研究を進めています。具体的には、第一原理計算や機械学習を組み合わせた分子動力学シミュレーションなどの手法を用いて、材料の構造や性質を原子スケールで解析しています。主な研究テーマは多岐にわたります。一つは、極限環境下での材料の動作機構の解明です。例えば、高温での不揮発性メモリ、高圧下での物質の相転移、光励起による材料の急速な構造変化などを対象としています。もう一つは、触媒作用やエネルギー変換に関わる界面現象の研究で、ナノ粒子表面の電荷ダイナミクスやグラフェンなどの二次元材料の特性を調べています。さらに、強誘電体材料における電気的・機械的制御や、半導体の塑性変形機構の研究も行われています。これらの研究を通じて、研究室は計算手法の開発も積極的に進めています。従来は計算が困難だった大規模系や長時間スケールの現象に対して、機械学習を活用した高速な計算手法を開発し、原子レベルの精度を保ちながら現実的な時間で計算を実行することを実現しています。

※ AI（Claude）が、公開されている論文要旨から研究の問い・手法・主要な発見を事実情報として抽出・再構成して自動生成しています。誤りを含む可能性があるため、正確性は研究室公式情報でご確認ください。

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研究成果（52 件）

[2026] Atomic and Electronic Structures of a Cu-exchanged Zeolite A
DOI: https://doi.org/10.1380/ejssnt.2026-011
[2026] High-temperature memristors enabled by interfacial engineering
DOI: https://doi.org/10.1126/science.aeb9934
[2025] Ultrahigh energy density in high-temperature polymer dielectric reinforced by bilayer nanocoating
DOI: https://doi.org/10.1016/j.cej.2025.160613
[2025] Structural Insights into Liquid Malic and Lactic Acids from First-Principles Simulations and X-ray Diffraction
DOI: https://doi.org/10.7566/jpsj.95.014602
[2025] Bonding nature of Cu2+ in distorted tetragonal pyramidal coordination in clinoclase and callaghanite
DOI: https://doi.org/10.2465/jmps.240925
[2025] Multiscale Light-Matter Dynamics in Quantum Materials: From Electrons to Topological Superlattices
DOI: https://doi.org/10.1145/3712285.3771785
[2025] Photochemistry and Thermal Chemistry in Polymeric Ceramic Precursors
DOI: https://doi.org/10.1021/acs.jpclett.5c02429
[2025] Photoinduced Phase Transition of Diamond: A Nonadiabatic Quantum Molecular Dynamics Study
DOI: https://doi.org/10.1021/acs.jpclett.5c01332
[2025] Large-scale Molecular-dynamics Simulations of SiO2 Melt and Glass under High Pressure with Robust Machine-learning Interatomic Potentials
DOI: https://doi.org/10.5940/jcrsj.67.121
[2025] MECHANICAL PROPERTIES OF LAYERED STRUCTURE OF 1.1-nm TOBERMORITE USING AB INITIO MOLECULAR DYNAMICS SIMULATION
DOI: https://doi.org/10.14250/cement.78.18

続きを表示（残り 42 件）

[2025] Intermolecular Correlations in Liquid Racemic Lactic Acid: A Comparison with Liquid L-Lactic Acid
DOI: https://doi.org/10.7566/jpsj.94.044604
[2024] Thermoelectric Grain Boundary in Monolayer MoS2
DOI: https://doi.org/10.1021/acs.jpcc.4c04339
[2024] Photoinduced Negative Differential Resistance at a Graphene/Silicon Interface: A Nonadiabatic Quantum Molecular Dynamics Study
DOI: https://doi.org/10.1021/acs.jpclett.4c02272
[2024] Thermal conductivity calculation using homogeneous non-equilibrium molecular dynamics simulation with Allegro
DOI: https://doi.org/10.1016/j.ijheatmasstransfer.2024.126106
[2024] Tracking surface charge dynamics on single nanoparticles
DOI: https://doi.org/10.1126/sciadv.adp1890
[2024] Intermolecular Correlations in Liquid Lactic Acid Based on ab initio Molecular Dynamics Simulations Combined with High-Energy X-ray Diffraction Measurements
DOI: https://doi.org/10.7566/jpsj.93.054601
[2024] Phase behavior and atomic dynamics in RbxNa1–x: insights from machine learning interatomic potentials based on ab initio molecular dynamics
DOI: https://doi.org/10.1088/1361-648x/ad9071
[2024] Catalysis in Extreme Field Environments: A Case Study of Strongly Ionized SiO2 Nanoparticle Surfaces
DOI: https://doi.org/10.1021/jacs.4c08550
[2023] Atomic and Electronic Structures on a Mordenite Zeolite
DOI: https://doi.org/10.1380/ejssnt.2023-063
[2023] Ab Initio Molecular Dynamics of the Initial Growth of Few-Layer Graphene on a Cu–Ni(111) Catalyst
DOI: https://doi.org/10.1021/acs.jpcc.3c04687
[2023] High-throughput computation and machine learning of refractive index of polymers
DOI: https://doi.org/10.1063/5.0161198
[2023] Construction of machine-learning interatomic potential under heat flux regularization and its application to power spectrum analysis for silver chalcogenides
DOI: https://doi.org/10.1016/j.cpc.2023.108920
[2023] High-throughput computation and machine learning of refractive index of polymers
DOI: https://doi.org/10.5281/zenodo.8245177
[2023] Induction and Ferroelectric Switching of Flux Closure Domains in Strained PbTiO3 with Neural Network Quantum Molecular Dynamics
DOI: https://doi.org/10.1021/acs.nanolett.3c01885
[2023] Large-scale Molecular-dynamics Simulations of SiO2 Melt under High Pressure with Robust Machine-learning Interatomic Potentials
DOI: https://doi.org/10.7566/jpsj.92.074002
[2023] Atomic and electronic structures of an Ag-containing 4A zeolite
DOI: https://doi.org/10.1016/j.micromeso.2023.112662
[2023] Efficient Training of the Machine-Learning Interatomic Potential Based on an Artificial Neural Network for Estimating the Helmholtz Free Energy of Alkali Metals
DOI: https://doi.org/10.7566/jpsj.92.054005
[2023] Large-scale Molecular-dynamics Simulations of SiO2 Melt under High Pressure with Robust Machine-learning Interatomic Potentials
[2022] Squishing Skyrmions: Symmetry-Guided Dynamic Transformation of Polar Topologies Under Compression
DOI: https://doi.org/10.1021/acs.jpclett.2c03029
[2022] Defect-free and crystallinity-preserving ductile deformation in semiconducting Ag2S
DOI: https://doi.org/10.1038/s41598-022-24004-z
[2022] Photoexcitation-Induced Nonthermal Ultrafast Loss of Long-Range Order in GeTe
DOI: https://doi.org/10.1021/acs.jpclett.2c02448
[2022] Towards computational polar-topotronics: Multiscale neural-network quantum molecular dynamics simulations of polar vortex states in SrTiO3/PbTiO3 nanowires
DOI: https://doi.org/10.3389/fnano.2022.884149
[2022] Thickness dependence of dielectric constant of alumina films based on first-principles calculations
DOI: https://doi.org/10.1063/5.0106721
[2022] Hydrogen Bonding in Liquid Ammonia
DOI: https://doi.org/10.1021/acs.jpclett.2c01608
[2022] Ab Initio Molecular–Dynamics Study of Structural and Bonding Properties of Liquid Fe–Light–Element–O Systems Under High Pressure
DOI: https://doi.org/10.3389/feart.2022.873088
[2022] Exploring far-from-equilibrium ultrafast polarization control in ferroelectric oxides with excited-state neural network quantum molecular dynamics
DOI: https://doi.org/10.1126/sciadv.abk2625
[2022] Importance of Adjusting Coefficients in Cost Function for Construction of High-Accuracy Machine-Learning Interatomic Potential
DOI: https://doi.org/10.7566/jpsj.91.045002
[2022] Thermal conductivity calculation based on Green–Kubo formula using ANN potential for β-Ag2Se
DOI: https://doi.org/10.1016/j.jpcs.2022.110580
[2022] Atomic and Electronic Structures of an Ag-Containing 4a Zeolite
DOI: https://doi.org/10.2139/ssrn.4291838
[2021] First-Principles Study of Microscopic Mechanism of High Ductility of Silver Sulfide/Selenide
[2021] Sulfurization of MoO3 in the Chemical Vapor Deposition Synthesis of MoS2 Enhanced by an H2S/H2 Mixture
DOI: https://doi.org/10.1021/acs.jpclett.0c03280
[2021] Neural network molecular dynamics of ferroelectric domain boundary
[2021] Molecular Dynamics Simulation of Shock Compression Behavior Based on First-Principles Calculation and Machine-Learning
DOI: https://doi.org/10.4131/jshpreview.31.132
[2021] Deep Well Trapping of Hot Carriers in a Hexagonal Boron Nitride Coating of Polymer Dielectrics
DOI: https://doi.org/10.1021/acsami.1c14587
[2021] Reproduction of Melting and Crystallization of Sodium by Machine-Learning Interatomic Potential Based on Artificial Neural Networks
DOI: https://doi.org/10.7566/jpsj.90.094603
[2021] Photoinduced oxygen transport in cobalt double-perovskite crystal EuBaCo2O5.39
DOI: https://doi.org/10.1016/j.apmt.2021.101167
[2021] Neural Network Quantum Molecular Dynamics, Intermediate Range Order in GeSe2, and Neutron Scattering Experiments
DOI: https://doi.org/10.1021/acs.jpclett.1c01272
[2021] Ex-NNQMD: Extreme-Scale Neural Network Quantum Molecular Dynamics
DOI: https://doi.org/10.1109/ipdpsw52791.2021.00145
[2021] Dielectric Constant of Liquid Water Determined with Neural Network Quantum Molecular Dynamics
DOI: https://doi.org/10.1103/physrevlett.126.216403
[2021] Estimating thermal conductivity of α-Ag2Se using ANN potential with Chebyshev descriptor
DOI: https://doi.org/10.1016/j.cplett.2021.138748
[2021] Ultrafast photoexcitation driven non-thermal amorphization of GeTe
[2021] Design of novel polymer-metal interfaces using first principles-informed artificial intelligence techniques

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AI 要約（直近 5 年の研究成果）

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研究成果（52 件）

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