2024

• Guillaume Deffrennes, Bengt Hallstedt, Taichi Abe, Quentin Bizot, Evelyne Fischer, Jean-Marc Joubert, Kei Terayama, Ryo Tamura. Data-driven study of the enthalpy of mixing in the liquid phase. Calphad. 87 (2024) 102745.
  DOI: 10.1016/j.calphad.2024.102745

• Ryo Tamura, Ryuichi Inaba, Mami Watanabe, Yutaro Mori, Makoto Urushihara, Kenji Yamaguchi, Shoichi Matsuda. Predicting the surface roughness of an electrodeposited copper film using a machine learning technique. Science and Technology of Advanced Materials: Methods. 4 [1] (2024) 2416889-1-2416889-8.
  DOI: 10.1080/27660400.2024.2416889

• Fumiyasu Oba, Takayuki Nagai, Ryoji Katsube, Yasuhide Mochizuki, Masatake Tsuji, Guillaume Deffrennes, Kota Hanzawa, Akitoshi Nakano, Akira Takahashi, Kei Terayama, Ryo Tamura, Hidenori Hiramatsu, Yoshitaro Nose, Hiroki Taniguchi. Theoretical and data-driven approaches to semiconductors and dielectrics: from prediction to experiment. Science and Technology of Advanced Materials. 25 [1] (2024) 2423600.
  DOI: 10.1080/14686996.2024.2423600

• Ai Koizumi, Guillaume Deffrennes, Kei Terayama, Ryo Tamura. Performance of uncertainty-based active learning for efficient approximation of black-box functions in materials science. Scientific Reports. 14 [1] (2024) 27019.
  DOI: 10.1038/s41598-024-76800-4

• Nobuya Sato, Akira Takahashi, Shin Kiyohara, Kei Terayama, Ryo Tamura, Fumiyasu Oba. Target Material Property‐Dependent Cluster Analysis of Inorganic Compounds. Advanced Intelligent Systems. 6 [12] (2024) 2400253.
  DOI: 10.1002/aisy.202400253

• Makoto Urushihara, Kenji Yamaguchi, Ryo Tamura. Black-box optimization technique for investigation of surface phase diagram. AIP Advances. 14 [12] (2024) 125008.
  DOI: 10.1063/5.0229856

• Feng Zhang, Ryo Tamura, Fanyu Zeng, Daichi Kozawa, Ryo Kitaura. Bayesian Optimization for Controlled Chemical Vapor Deposition Growth of WS2. ACS Applied Materials & Interfaces. 16 [43] (2024) 59109-59115.
  DOI: 10.1021/acsami.4c15275

• Ryosuke Shibukawa, Ryo Tamura, Koji Tsuda. Boltzmann sampling with quantum annealers via fast Stein correction. Physical Review Research. 6 [4] (2024) 043050.
  DOI: 10.1103/physrevresearch.6.043050

• Ryo Tamura, Haruhiko Morito, Guillaume Deffrennes, Masanobu Naito, Yoshitaro Nose, Taichi Abe, Kei Terayama. AIPHAD, an active learning web application for visual understanding of phase diagrams. Communications Materials. 5 [1] (2024) 139.
  DOI: 10.1038/s43246-024-00580-7

• Ryo Tamura, Kenji Nagata, Keitaro Sodeyama, Kensaku Nakamura, Toshiki Tokuhira, Satoshi Shibata, Kazuki Hammura, Hiroki Sugisawa, Masaya Kawamura, Teruki Tsurimoto, Masanobu Naito, Masahiko Demura, Takashi Nakanishi. Machine learning prediction of the mechanical properties of injection-molded polypropylene through X-ray diffraction analysis. Science and Technology of Advanced Materials. (2024) 2388016.
  DOI: 10.1080/14686996.2024.2388016

• Yota Fukui, Kosuke Minami, Kota Shiba, Genki Yoshikawa, Koji Tsuda, Ryo Tamura. Automated odor-blending with one-pot Bayesian optimization. Digital Discovery. 3 [5] (2024) 969-976.
  DOI: 10.1039/d3dd00215b

• Anh Khoa Augustin Lu, Jianbo Lin, Yasunori Futamura, Tetsuya Sakurai, Ryo Tamura, Tsuyoshi Miyazaki. Extraction of local structure differences in silica based on unsupervised learning. Physical Chemistry Chemical Physics. 26 [15] (2024) 11657-11666.
  DOI: 10.1039/d3cp06298h

• Masashi Hase, Ryo Tamura, Koji Hukushima, Shinichiro Asai, Takatsugu Masuda, Shinichi Itoh, and Andreas Dönni. Inelastic neutron scattering studies on the eight-spin zigzag-chain compound KCu4P3O12: Confirmation of the validity of a data-driven technique based on machine learning. Physical Review B 109 (2024) 094434.
  DOI: 10.1103/PhysRevB.109.094434

• Yusuke Saeki, Naoki Maki, Takahiro Nemoto, Katsushige Inada, Kosuke Minami, Ryo Tamura, Gaku Imamura, Yukiko Cho-Isoda, Shinsuke Kitazawa, Hiroshi Kojima, Genki Yoshikawa, and Yukio Sato. Lung cancer detection in perioperative patients' exhaled breath with nanomechanical sensor array. Lung Cancer 190 (2024) 107514.
  DOI: 10.1016/j.lungcan.2024.107514

2023

• Ken Sakaushi, Watcharaporn Hoisang, and Ryo Tamura. Human–Machine Collaboration for Accelerated Discovery of Promising Oxygen Evolution Electrocatalysts with On-Demand Elementse. ACS Central Science 9 [12] (2023) 2216–2224.
  DOI: 10.1021/acscentsci.3c01009

• Makoto Urushihara, Masaya Karube, Kenji Yamaguchi, and Ryo Tamura. Optimization of Core-Shell Nanoparticles Using a Combination of Machine Learning and Ising Machine. Advanced Photonics Research 4 [11] (2023) 23002.
  DOI: 10.1002/adpr.202300226

• Akira Takahashi, Kei Terayama, Yu Kumagai, Ryo Tamura, and Fumiyasu Oba. Fully autonomous materials screening methodology combining first-principles calculations, machine learning and high-performance computing system. Science and Technology of Advanced Materials: Methods, 3 [1] (2023) 2261834.
  DOI: 10.1080/27660400.2023.2261834

• Hongxin Wang, Han Zhang, Ryo Tamura, Bo Da, Shimaa A. Abdellatef, Ikumu Watanabe, Nobuyuki Ishida, Daisuke Fujita, Nobutaka Hanagata, Tomoki Nakagawa, and Jun Nakanishi. Mapping stress inside living cells by atomic force microscopy in response to environmental stimuli. Science and Technology of Advanced Materials, 24 [1] (2023) 2265434.
  DOI: 10.1016/j.patter.2023.100846

• Weilin Yuan, Yusuke Hibi, Ryo Tamura, Masato Sumita, Yasuyuki Nakamura, Masanobu Naito, and Koji Tsuda. Revealing factors influencing polymer degradation with rank-based machine learning. Patterns, 4 (2023) 100846.
  DOI: 10.1080/14686996.2023.2265434

• Kei Terayama, Yamato Osaki, Takehiro Fujita, Ryo Tamura, Masanobu Naito, Koji Tsuda, Toru Matsui, and Masato Sumita. Koopmans’ Theorem-Compliant Long-Range Corrected (KTLC) Density Functional Mediated by Black-Box Optimization and Data-Driven Prediction for Organic Molecules. Journal of Chemical Theory and Computation, 19 [19] (2023) 6770-6781.
  DOI: 10.1021/acs.jctc.3c00764

• Ryo Tamura, Kei Terayama, Masato Sumita, and Koji Tsuda. Ranking Pareto optimal solutions based on projection free energy. Physical Review Materials, 7 [9] (2023) 093804.
  DOI: 10.1103/PhysRevMaterials.7.093804

• Jiawen Li, Masato Sumita, Ryo Tamura, and Koji Tsuda. Interpretable Fragment-Based Molecule Design with Self-Learning Entropic Population Annealing. Advanced Intelligent Systems. 5 [10] (2023) 230018.
  DOI: 10.1002/aisy.202300189

• Ryo Tamura, Koji Tsuda, and Shoichi Matsuda. NIMS-OS: An automation software to implement a closed loop between artificial intelligence and robotic experiments in materials science. Science and Technology of Advanced Materials: Methods. 3 [1] (2023) 2232297.
  DOI: 10.1080/27660400.2023.2232297

• Zetian Mao, Yoshiki Matsuda, Ryo Tamura, and Koji Tsuda. Chemical design with GPU-based Ising machines. Digital Discovery 2 (2023) 1098-1103.
  DOI: 10.1039/D3DD00047H

• Guillaume Deffrennes, Kei Terayama, Taichi Abe, Etsuko Ogamino, and Ryo Tamura. A framework to predict binary liquidus by combining machine learning and CALPHAD assessments. Materials & Design. 232 (2023) 112111.
  DOI: 10.1016/j.matdes.2023.112111

• Jianbo Lin, Ryo Tamura, Yasunori Futamura, Tetsuya Sakurai, and Tsuyoshi Miyazaki. Determination of hyper-parameters in the atomic descriptors for efficient and robust molecular dynamics simulations with machine learning forces. Physical Chemistry Chemical Physics. 25 [27] (2023) 17978-17986.
  DOI: 10.1039/D3CP01922E

• Andrejs Tučs, Francois Berenger, Akiko Yumoto, Ryo Tamura, Takanori Uzawa, and Koji Tsuda. Quantum Annealing Designs Nonhemolytic Antimicrobial Peptides in a Discrete Latent Space. ACS Medicinal Chemistry Letters. 14 [5] (2023) 577–582
  DOI: 10.1021/acsmedchemlett.2c00487

• Kota Shiba, Chao Zhuang, Kosuke Minami, Gaku Imamura, Ryo Tamura, Sadaki Samitsu, Takumi Idei, Genki Yoshikawa, Luyi Sun, and David A. Weitz. Visualization of Flow‐Induced Strain Using Structural Color in Channel‐Free Polydimethylsiloxane Devices. Advanced Science. 10 [1] (2023) 2204310
  DOI: 10.1002/advs.202204310