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M

Mayu Muramatsu

keio university

16H-index
160Paper Count
959Citation Count
Published Papers 25
Publication Date
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Predicting inclusion-type internal defects in composites with complex structural shapes from experimental infrared thermography and numerical simulations: A demonstration of a machine learning approach based on graph neural networks
errComposites Part B-Engineering
IF14.2
err2026-08-06
err0
PREAI
errYuta Kojima; Julien Yvonnet; Katsuhiro Endo; Yoshihisa Harada; Mayu Muramatsu
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Tackling multiphysics problems via finite element guided physics-informed operator learning
errResults in Engineering
IF7.9
err2026-07-23
err0
errOAAI
errYusuke Yamazaki; Reza Najian Asl; Markus Apel; Mayu Muramatsu; Shahed Rezaei
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An Ising machine formulation for design updates in topology optimization of flow channels
errEngineering with Computers
IF4.9
err2026-01-14
err0
errOAAI
errYudai Suzuki; Shiori Aoki; Fabian Key; Katsuhiro Endo; Yoshiki Matsuda; Shu Tanaka; Marek Behr; Mayu Muramatsu
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Efficient evaluation of mechanical properties for two-phase materials using a direct data-driven approach
errMaterials & Design
IF7.9
err2025-10-14
err0
errOAAI
errMisato Suzuki; Mayu Muramatsu; Stefanie Reese; Erik Prume
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Development of defect localization method for perforated carbon-fiber-reinforced plastic specimens using finite element method and graph neural network
errFrontiers in Materials
IF2.9
err2025-10-01
err0
errOAAI
errKeisuke Nishioka; Yuta Kojima; Toshiya Saito; Kosuke Kawakami; Masahito Washiya; Mayu Muramatsu
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Dislocation-based crystal plasticity simulation on grain-size dependence of mechanical properties in dual-phase steels
errInternational Journal of Solids and Structures
IF3.8
err2025-08-30
err0
errOAAI
errMisato Suzuki; Kazuyuki Shizawa; Mayu Muramatsu
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Machine-learning-aided analysis of relationship between crystal defects and macroscopic mechanical properties of TWIP steel
errSCIENTIFIC REPORTS
IF3.9
err2025-04-25
err0
errOAAI
errTanaka, Marino; Sasaki, Kai; Punyafu, Jesada; Muramatsu, Mayu; Murayama, Mitsuhiro
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Transfer-learning-aided defect prediction in simply shaped CFRP specimens based on stress distribution obtained from finite element analysis and infrared stress measurement
errCOMPOSITES PART B-ENGINEERING
IF14.2
err2025-02-01
err0
errOAAI
errKojima, Yuta; Hirayama, Kenta; Endo, Katsuhiro; Harada, Yoshihisa; Muramatsu, Mayu
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Deep learning-aided inverse analysis framework to accelerate the exploration of DP steel microstructures
errMATERIALS TODAY COMMUNICATIONS
IF4.5
err2024-12-01
err0
errOAAI
errSuzuki, Misato; Shizawa, Kazuyuki; Muramatsu, Mayu
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Surrogate modeling for transient electrochemical potential analysis for SOFC using proper orthogonal decomposition
errSOLID STATE IONICS
IF3.3
err2024-10-01
err0
errOAAI
errSato, Masami; Muramatsu, Mayu; Tozato, Kenta; Moriguchi, Shuji; Kawada, Tatsuya; Terada, Kenjiro
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A finite element-based physics-informed operator learning framework for spatiotemporal partial differential equations on arbitrary domains
errENGINEERING WITH COMPUTERS
IF4.9
err2024-08-02
err1
errOAAI
errYamazaki, Yusuke; Harandi, Ali; Muramatsu, Mayu; Viardin, Alexandre; Apel, Markus; Brepols, Tim; Reese, Stefanie; Rezaei, Shahed
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Application of factorization machine with quantum annealing to hyperparameter optimization and metamodel-based optimization in granular flow simulations
errINTERNATIONAL JOURNAL FOR NUMERICAL AND ANALYTICAL METHODS IN GEOMECHANICS
IF3.6
err2024-06-25
err1
errOAAI
errXiao, Junsen; Endo, Katsuhiro; Muramatsu, Mayu; Nomura, Reika; Moriguchi, Shuji; Terada, Kenjiro
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Development of optimization method for truss structure by quantum annealing
errSCIENTIFIC REPORTS
IF3.9
err2024-06-16
err1
errOAAI
errHonda, Rio; Endo, Katsuhiro; Kaji, Taichi; Suzuki, Yudai; Matsuda, Yoshiki; Tanaka, Shu; Muramatsu, Mayu
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Fine-scale structural stability of carbon dioxide hydrate pellets under coarse-scale deformation using multi-scale coupled FEM-MD simulations
errMATERIALS TODAY COMMUNICATIONS
IF4.5
err2024-03-01
err0
errOAAI
errTerashima, Yuto Lewis; Brumby, Paul Edward; Murashima, Takahiro; Kouznetsova, Varvara; Muramatsu, Mayu
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Inverse design of polymer alloys using deep learning based on self-consistent field analysis and finite element analysis
errMATERIALS TODAY COMMUNICATIONS
IF4.5
err2023-12-01
err0
PREAI
errHiraide, Kazuya; Oya, Yutaka; Suzuki, Misato; Muramatsu, Mayu
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Heterogeneous biological membranes regulate protein partitioning via fluctuating diffusivity
errPNAS NEXUS
IF3.8
err2023-08-03
err5
errOAAI
errSakamoto, Ken; Akimoto, Takuma; Muramatsu, Mayu; Sansom, Mark S. P.; Metzler, Ralf; Yamamoto, Eiji
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A phase-field model by an Ising machine and its application to the phase-separation structure of a diblock polymer
errSCIENTIFIC REPORTS
IF3.9
err2022-06-24
err12
errOAAI
errEndo, Katsuhiro; Matsuda, Yoshiki; Tanaka, Shu; Muramatsu, Mayu
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Nanoscale defect evaluation framework combining real-time transmission electron microscopy and integrated machine learning-particle filter estimation
errSCIENTIFIC REPORTS
IF3.9
err2022-06-22
err1
errOAAI
errSasaki, K.; Muramatsu, M.; Hirayama, K.; Endo, K.; Murayama, M.
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Substitution approach for decoupled two-scale analysis of materially nonlinear composite plates
errCOMPUTERS & STRUCTURES
IF4.8
err2021-10-01
err2
errOAAI
errSato, Masami; Muramatsu, Mayu; Nishi, Shinnosuke; Kawada, Tatsuya; Terada, Kenjiro
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Application of deep learning to inverse design of phase separation structure in polymer alloy
errCOMPUTATIONAL MATERIALS SCIENCE
IF3.3
err2021-04-01
err32
errOAAI
errHiraide, Kazuya; Hirayama, Kenta; Endo, Katsuhiro; Muramatsu, Mayu
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Research Directions

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Co-authors
Cooperation Journals
M
Mark S.P. Sansom
H-index: 105 · Papers: 962
S
Satoshi Inoue
H-index: 91 · Papers: 721
R
Ralf Metzler
H-index: 88 · Papers: 584
H
Harumi Yokokawa
H-index: 58 · Papers: 469
H
Hirotaka Iwase
H-index: 55 · Papers: 449
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