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Ryo Tamura


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Publications
•  Paper (Peer-reviewed)
•  Proceedings
•  Book, Review



Paper (Peer-reviewed)

57. Kosuke Minami, Gaku Imamura, Ryo Tamura, Kota Shiba, and Genki Yoshikawa,
"Recent Advances in Nanomechanical Membrane-Type Surface Stress Sensors towards Artificial Olfaction",
Biosensors 12, 762 (2022). [mdpi]
DOI: 10.3390/bios12090762

56. Masato Sumita, Kei Terayama, Ryo Tamura, and Koji Tsuda
"QCforever: A Quantum Chemistry Wrapper for Everyone to Use in Black-Box Optimization",
Journal of Chemical Information and Modeling (2022). [ACS]
DOI: 10.1021/acs.jcim.2c00812

55. Yuichi Motoyama, Ryo Tamura, Kazuyoshi Yoshimi, Kei Terayama, Tsuyoshi Ueno, and Koji Tsuda
"Bayesian optimization package: PHYSBO",
Computer Physics Communications 278, 108405 (2022). [Elsevier]
DOI: 10.1016/j.cpc.2022.108405

54. Ryo Tamura, Guillaume Deffrennes, Kwangsik Han, Taichi Abe, Haruhiko Morito, Yasuyuki Nakamura, Masanobu Naito, Ryoji Katsube, Yoshitaro Nose, and Kei Terayama,
"Machine-learning-based phase diagram construction for high-throughput batch experiments",
Science and Technology of Advanced Materials: Methods 2, 153-161 (2022). [Taylor & Francis]
DOI: 10.1080/27660400.2022.2076548

53. Takehiro Fujita, Kei Terayama, Masato Sumita, Ryo Tamura, Yasuyuki Nakamura, Masanobu Naito, and Koji Tsuda,
"Understanding the evolution of a de novo molecule generator via characteristic functional group monitoring",
Science and Technology of Advanced Materials 23, 352-360 (2022). [Taylor & Francis]
DOI: 10.1080/14686996.2022.2075240

52. Syun Izawa, Koki Kitai, Shu Tanaka, Ryo Tamura, and Koji Tsuda,
"Continuous black-box optimization with an Ising machine and random subspace coding",
Physical Review Research 4, 023062 (2022). [APS]
DOI: 10.1103/PhysRevResearch.4.023062

51. Akira Takahashi, Yu Kumagai, Hirotaka Aoki, Ryo Tamura, and Fumiyasu Oba,
"Adaptive sampling methods via machine learning for materials screening",
Science and Technology of Advanced Materials: Methods 2, 55-66 (2022). [Taylor & Francis]
DOI: 10.1080/27660400.2022.2039573

50. Jiawen Li, Jinzhe Zhang, Ryo Tamura, and Koji Tsuda,
"Self-learning entropic population annealing for interpretable materials design",
Digital Discovery 1, 295–302 (2022). [RSC]
DOI: 10.1039/D1DD00043H





49. Masato Sumita, Kei Terayama, Naoya Suzuki, Shinsuke Ishihara, Ryo Tamura, Mandeep K. Chahal, Daniel T. Payne, Kazuki Yoshizoe, and Koji Tsuda,
"De novo creation of a naked eye–detectable fluorescent molecule based on quantum chemical computation and machine learning",
Science Advances 8, eabj3906 (2022). [AAAS]
DOI: 10.1126/sciadv.abj3906

48. Guillaume Deffrennes, Kei Terayama, Taichi Abe, and Ryo Tamura,
"A machine learning–based classification approach for phase diagram prediction",
Materials & Design 215, 110497 (2022). [Elsevier]
DOI: 10.1016/j.matdes.2022.110497

47. Ryo Tamura, Momo Matsuda, Jianbo Lin, Yasunori Futamura, Tetsuya Sakurai, and Tsuyoshi Miyazaki,
"Structural analysis based on unsupervised learning: Search for a characteristic low-dimensional space by local structures in atomistic simulations",
Physical Review B 105, 075107 (2022). [APS]
DOI: 10.1103/PhysRevB.105.075107

46. Wei-Hsun Hu, Ta-Te Chen, Ryo Tamura, Kei Terayama, Siqian Wang, Ikumu Watanabe, and Masanobu Naito,
"Topological alternation from structurally adaptable to mechanically stable crosslinked polymer",
Science and Technology of Advanced Materials 23, 66-75 (2022). [Taylor & Francis]
DOI: 10.1080/14686996.2021.2025426

45. Xiaolin Sun, Ryo Tamura, Masato Sumita, Kenichi Mori, Kei Terayama, and Koji Tsuda,
"Integrating Incompatible Assay Data Sets with Deep Preference Learning",
ACS Medicinal Chemistry Letters 13, 70-75 (2022). [ACS]
DOI: 10.1021/acsmedchemlett.1c00439

44. Kei Terayama, Kwangsik Han, Ryoji Katsube, Ikuo Ohnuma, Taichi Abe, Yoshitaro Nose, and Ryo Tamura,
"Acceleration of phase diagram construction by machine learning incorporating Gibbs’ phase rule",
Scripta Materialia 208, 114335 (2022). [Elsevier]
DOI: 10.1016/j.scriptamat.2021.114335

43. Ryo Tamura, Yuki Takei, Shinichiro Imai, Maki Nakahara, Satoshi Shibata, Takashi Nakanishi, and Masahiko Demura,
"Experimental design for the highly accurate prediction of material properties using descriptors obtained by measurement",
Science and Technology of Advanced Materials: Methods 1, 152-161 (2021). [Taylor & Francis]
DOI: 10.1080/27660400.2021.1963641
This topic was reported in press release from NIMS (October 25, 2021) [Link] .
This paper was selected as STAM:Methods Editor's Choice.
The introduction of this research is reported in asia research news [Link] and EurekAlert [Link] .







42. Katsushige Inada, Hiroshi Kojima, Yukiko Cho-Isoda, Ryo Tamura, Gaku Imamura, Kosuke Minami, Takahiro Nemoto, and Genki Yoshikawa,
"Statistical Evaluation of Total Expiratory Breath Samples Collected throughout a Year: Reproducibility and Applicability toward Olfactory Sensor-Based Breath Diagnostics",
Sensors 21, 4742 (2021). [mdpi]
DOI: 10.3390/s21144742

41. Hanxiao Xu, Koki Kitai, Kosuke Minami, Makito Nakatsu, Genki Yoshikawa, Koji Tsuda, Kota Shiba, and Ryo Tamura,
"Determination of quasi-primary odors by endpoint detection",
Scientific Reports 11, 12070 (2021). [Springer Nature]
DOI: 10.1038/s41598-021-91210-6
This topic was reported in press release from NIMS (June 21, 2021) [Link] .





40. Kei Terayama, Masato Sumita, Ryo Tamura, and Koji Tsuda,
"Black-Box Optimization for Automated Discovery",
Accounts of Chemical Research 54, 1334-1346 (2021). [ACS]
DOI: 10.1021/acs.accounts.0c00713

39. Hongxin Wang, Han Zhang, Bo Da, Dabao Lu, Ryo Tamura, Kenta Goto, Ikumu Watanabe, Daisuke Fujita, Nobutaka Hanagata, Junko Kano, Tomoki Nakagawa, and Masayuki Noguchi,
"Mechanomics Biomarker for Cancer Cells Unidentifiable through Morphology and Elastic Modulus",
Nano Letters 21, 1538–1545 (2021). [ACS]
DOI: 10.1021/acs.nanolett.1c00003

38. Ryo Tamura, Toshio Osada, Kazumi Minagawa, Takuma Kohata, Masashi Hirosawa, Koji Tsuda, and Kyoko Kawagishi,
"Machine learning-driven optimization in powder manufacturing of Ni-Co based superalloy",
Materials & Design 198, 109290 (2021). [Elsevier]
DOI: 10.1016/j.matdes.2020.109290
This topic was reported in press release from NIMS (November 30, 2020) [Link] .





37. Masatomo Sumiya, Masato Sumita, Yuya Asai, Ryo Tamura, Akira Uedono, and Akitaka Yoshigoe,
"Dynamic Observation and Theoretical Analysis of Initial O2 Molecule Adsorption on Polar and m-Plane Surfaces of GaN",
The Journal of Physical Chemistry C 124, 25282-25290 (2020). [ACS]
DOI: 10.1021/acs.jpcc.0c07151

36. Ryo Tamura, Makoto Watanabe, Hiroaki Mamiya, Kota Washio, Masao Yano, Katsunori Danno, Akira Kato, and Tetsuya Shoji,
"Materials informatics approach to understand aluminum alloys",
Science and Technology of Advanced Materials 21, 540-551 (2020). [Taylor & Francis]
DOI: 10.1080/14686996.2020.1791676
This paper was selected as STAM Editor's Choice [Link] .
The introduction of this research is reported in asia research news [Link] .

35. Ryo Tamura, Koji Hukushima, Akira Matsuo, Koichi Kindo, and Masashi Hase,
"Data-driven determination of the spin Hamiltonian parameters and their uncertainties: The case of the zigzag-chain compound KCu4P3O12",
Physical Review B 101, 224435 (2020). [APS]
DOI: 10.1103/PhysRevB.101.224435

34. Kei Terayama, Masato Sumita, Ryo Tamura, Daniel T. Payne, Mandeep K. Chahal, Shinsuke Ishihara, and Koji Tsuda,
"Pushing property limits in materials discovery via boundless objective-free exploration",
Chemical Science 11, 5959-5968 (2020). [RSC]
DOI: 10.1039/d0sc00982b
This topic was reported in press release from NIMS (May 28, 2020).
The introduction of this research is reported in CHEMISTORY WORLD [Link] , RIKEN Research News [Link] .

33. Kenji Homma, Yu Liu, Masato Sumita, Ryo Tamura, Naoki Fushimi, Junichi Iwata, Koji Tsuda, and Chioko Kaneta,
"Optimization of Heterogeneous Ternary Li3PO4-Li3BO3-Li2SO4 Mixture for Li-ion Conductivity by Machine Learning",
The Journal of Physical Chemistry C 124, 12865-12870 (2020). [ACS]
DOI: 10.1021/acs.jpcc.9b11654

32. Ryoji Katsube, Kei Terayama, Ryo Tamura, and Yoshitaro Nose,
"Experimental Establishment of Phase Diagrams Guided by Uncertainty Sampling: An Application to the Deposition of Zn–Sn–P Films by Molecular Beam Epitaxy",
ACS Materials Letters 2, 571-575 (2020). [ACS]
DOI: 10.1021/acsmaterialslett.0c00104

31. Xiaolin Sun, Zhufeng Hou, Masato Sumita, Shinsuke Ishihara, Ryo Tamura, and Koji Tsuda,
"Data Integration for Accelerated Materials Design via Preference Learning",
New Journal of Physics 22, 055001 (2020). [IOP]
DOI: 10.1088/1367-2630/ab82b9

30. Koki Kitai, Jiang Guo, Shenghong Ju, Shu Tanaka, Koji Tsuda, Junichiro Shiomi, and Ryo Tamura,
"Designing metamaterials with quantum annealing and factorization machines",
Physical Review Researches 2, 013319 (2020). [APS]
DOI: 10.1103/PhysRevResearch.2.013319

29. Kei Terayama, Koji Tsuda, and Ryo Tamura,
"Efficient recommendation tool of materials by an executable file based on machine learning",
Japanese Journal of Applied Physics 58, 098001 (2019). [IOP]
DOI: 10.7567/1347-4065/ab349b

28. Masato Sumita, Ryo Tamura, Kenji Homma, Chioko Kaneta, and Koji Tsuda,
"Li-ion conductive Li3PO4-Li3BO3-Li2SO4 mixture: Prevision through density functional molecular dynamics and machine learning",
Bulletin of the Chemical Society of Japan 92, 1100-1106 (2019). [CSJ]
DOI: 10.1246/bcsj.20190041

27. Kei Terayama, Ryo Tamura, Yoshitaro Nose, Hidenori Hiramatsu, Hideo Hosono, Yasushi Okuno, and Koji Tsuda,
"Efficient construction method for phase diagrams using uncertainty sampling",
Physical Review Materials 3, 033802 (2019). [APS]
DOI: 10.1103/PhysRevMaterials.3.033802

26. Ryo Tamura, Jianbo Lin, and Tsuyoshi Miyazaki,
"Machine learning forces trained by Gaussian process in liquid states: Transferability to temperature and pressure",
Journal of the Physical Society of Japan 88, 044601 (2019). [JPS]
DOI: 10.7566/JPSJ.88.044601

25. Masato Sumita, Xiufeng Yang, Shinsuke Ishihara, Ryo Tamura, and Koji Tsuda,
"Hunting for organic molecules with artificial intelligence: Molecules optimized for desired excitation energies",
ACS Central Science 4, 1126-1133 (2018). [ACS]
DOI: 10.1021/acscentsci.8b00213
This topic was reported in press release from NIMS (Aug. 23, 2018).
The introduction of this research is reported in ACS Central Science First Reactions [Link] and MANA e-Bulletins [Link] .

24. Kota Shiba, Ryo Tamura, Takako Sugiyama, Yuko Kameyama, Keiko Koda, Eri Sakon, Kosuke Minami, Huynh Thien Ngo, Gaku Imamura, Koji Tsuda, and Genki Yoshikawa,
"Functional nanoparticles-coated nanomechanical sensor arrays for machine learning-based quantitative odor analysis",
ACS Sensors 3, 1592–1600 (2018). [ACS]
DOI: 10.1021/acssensors.8b00450

23. Ryo Tamura and Koji Hukushima,
"Bayesian optimization for computationally extensive probability distributions",
PLoS ONE 13, e0193785 (2018). [PLoS]
DOI: 10.1371/journal.pone.0193785

22. Ryosuke Arai, Ryo Tamura, Koji Baba, Hidehito Fukuda, Hideki Nakagome, Takenori Numazawa,
"Search for optimum refrigeration cycle on room-temperature magnetic refrigeration",
Transactions of the Japan Society of Refrigerating and Air Conditioning Engineers 34 147 (2017). [J-STAGE]
DOI: 10.11322/tjsrae.17-05_OA

21. Kota Shiba, Ryo Tamura, Gaku Imamura, and Genki Yoshikawa,
"Data-driven nanomechanical sensing: Specific information extraction from a complex system",
Scientific Reports 7, 3661 (2017). [Springer Nature]
DOI: 10.1038/s41598-017-03875-7
This topic was reported in press release from NIMS (June 20, 2017) [Link] .




20. Ryo Tamura and Koji Hukushima,
"Method for estimating spin-spin interactions from magnetization curves",
Physical Review B 95, 064407-1-8 (2017). [APS, arXiv, abstract]
DOI: 10.1103/PhysRevB.95.064407

19. Teppei Suzuki, Ryo Tamura, and Tsuyoshi Miyazaki,
"Machine learning for atomic forces in a crystalline solid: Transferability to various temperatures",
International Journal of Quantum Chemistry 117, 33–39 (2017). [Wiley, arXiv, abstract]
DOI: 10.1002/qua.25307
This research topic was chosen as Cover Image in International Journal of Quantum Chemistry.


18. Carlos Romero-Muñiz, Ryo Tamura, Shu Tanaka, and Victorino Franco,
"Applicability of scaling behavior and power laws in the analysis of the magnetocaloric effect in second-order phase transition materials",
Physical Review B 94, 134401-1-13 (2016). [APS, arXiv]
DOI: 10.1103/PhysRevB.94.134401

17. Ryosuke Arai, Ryo Tamura, Hidehito Fukuda, Jing Li, Akiko T. Saito, Saori Kaji, Hideki Nakagome, and Takenori Numazawa,
"Estimation of magnetocaloric properties by using Monte Carlo method for AMRR cycle",
IOP Conference Series: Materials Science and Engineering 101, 012118-1-8 (2015). [IOP]
DOI: 10.1088/1757-899X/101/1/012118

16. Masashi Hase, Haruhiko Kuroe, Vladimir Yu. Pomjakushin, Lukas Keller, Ryo Tamura, Noriki Terada, Yoshitaka Matsushita, Andreas Dönni, and Tomoyuki Sekine,
"Magnetic structure of the spin−1/2 frustrated quasi-one-dimensional antiferromagnet Cu3Mo2O9: Appearance of a partially disordered state",
Physical Review B 92, 054425-1-7 (2015). [APS, arXiv]
DOI: 10.1103/PhysRevB.92.054425

15. Saori Toyoizumi, Hideaki Kitazawa, Yukihiko Kawamura, Hiroaki Mamiya, Noriki Terada, Ryo Tamura, Andreas Dönni, Kengo Morita, and Akira Tamaki,
"Sample dependence of giant magnetocaloric effect in a cluster-glass system Ho5Pd2",
Journal of Applied Physics 117, 17D101-1-3 (2015). [AIP]
DOI: 10.1063/1.4906296

14. Ryo Tamura, Shu Tanaka, Takahisa Ohno, and Hideaki Kitazawa,
"Magnetic ordered structure dependence of magnetic refrigeration efficiency",
Journal of Applied Physics 116, 053908-1-12 (2014). [AIP, arXiv, abstract]
DOI: 10.1063/1.4891803

13. Ryo Tamura, Takahisa Ohno, and Hideaki Kitazawa,
"A generalized magnetic refrigeration scheme",
Applied Physics Letters 104, 052415-1-4 (2014). [AIP, arXiv, abstract]
DOI: 10.1063/1.4864161
This topic was reported in press release from NIMS (March 10, 2014) [Link] .

12. Ryo Tamura, Shu Tanaka, and Naoki Kawashima,
"Phase transitions with discrete symmetry breaking in antiferromagnetic Heisenberg models on a triangular lattice",
JPS Conference Proceedings 1, 012125-1-5 (2014). [JPS, arXiv]
DOI: 10.7566/JPSCP.1.012125

11. Ryo Tamura and Shu Tanaka,
"Interlayer-interaction dependence of latent heat in the Heisenberg model on a stacked triangular lattice with competing interactions",
Physical Review E 88, 052138-1-9 (2013). [APS, arXiv, abstract]
DOI: 10.1103/PhysRevE.88.052138

10. Ryo Tamura, Shu Tanaka, and Naoki Kawashima,
"Second-order phase transition in the Heisenberg model on a triangular lattice with competing interactions",
Physical Review B 87, 214401-1-5 (2013). [APS, arXiv, abstract]
DOI: 10.1103/PhysRevB.87.214401
This research topic was chosen as Kaleidoscope in Physical Review B.



9. Shu Tanaka and Ryo Tamura,
"Network-growth rule dependence of fractal dimension of percolation cluster on square lattice",
Journal of the Physical Society of Japan 82, 053002-1-5 (2013). [JPS, arXiv]
DOI: 10.7566/JPSJ.82.053002

8. Shu Tanaka, Ryo Tamura, and Hosho Katsura,
"Entanglement spectra of the quantum hard-square model: Holographic minimal models",
Physical Review A 86, 032326-1-9 (2012). [APS, arXiv]
DOI: 10.1103/PhysRevA.86.032326

7. Ryo Tamura, Naoki Kawashima, Takafumi Yamamoto, Cedric Tassel, and Hiroshi Kageyama,
"Random fan-out state induced by site-random interlayer couplings",
Physical Review B 84, 214408-1-11 (2011). [APS, arXiv, abstract]
DOI: 10.1103/PhysRevB.84.214408
This research topic was chosen as Kaleidoscope in Physical Review B.


6. Shu Tanaka and Ryo Tamura,
"Dynamical properties of Potts model with invisible states",
Journal of Physics: Conference Series 320, 012025-1-6 (2011). [IOP, arXiv, abstract]
DOI: 10.1088/1742-6596/320/1/012025

5. Ryo Tamura and Naoki Kawashima,
Double-q order in a frustrated random spin system",
Journal of Physics: Conference Series 320, 012013-1-5 (2011). [IOP, arXiv, abstract]
DOI: 10.1088/1742-6596/320/1/012013

4. Ryo Tamura and Naoki Kawashima,
"First-order phase transition with breaking of lattice rotation symmetry in continuous-spin model on triangular lattice",
Journal of the Physical Society of Japan 80, 074008-1-10 (2011). [JPS, arXiv, abstract]
DOI: 10.1143/JPSJ.80.074008

3. Shu Tanaka, Ryo Tamura, and Naoki Kawashima,
"Phase transition of generalized ferromagnetic Potts model -- effect of invisible states --",
Journal of Physics: Conference Series 297, 012022-1-7 (2011). [IOP, arXiv, abstract]
DOI: 10.1088/1742-6596/297/1/012022

2. Ryo Tamura, Shu Tanaka, and Naoki Kawashima,
"Phase transition in Potts model with invisible states",
Progress of Theoretical Physics 124, 381-388 (2010). [JPS, arXiv, abstract]
DOI: 10.1143/PTP.124.381

1. Ryo Tamura and Naoki Kawashima,
"First-order transition to incommensurate phase with broken lattice rotation symmetry in frustrated Heisenberg model",
Journal of the Physical Society of Japan 77, 103002-1-4 (2008). [JPS, arXiv, abstract]
DOI: 10.1143/JPSJ.77.103002


Proceedings
5. Shu Tanaka, Ryo Tamura, and Hosho Katsura,
"Entanglement properties of a quantum lattice-gas model on square and triangular ladders",
Kinki University Series on Quantum Computing Volume 9, pp. 71-88 (World Scientific, 2014). [World Scientific]
DOI: 10.1142/9789814602372_0005

4. Ryo Tamura and Shu Tanaka,
"A method to change phase transition nature -- toward annealing method --",
Kinki University Series on Quantum Computing Volume 9, pp. 135-161 (World Scientific, 2014). [World Scientific, arXiv]
DOI: 10.1142/9789814602372_0009

3. Shu Tanaka and Ryo Tamura,
"Quantum annealing and quantum fluctuation effect in frustrated Ising systems",
Kinki University Series on Quantum Computing Volume 7, pp. 241-261 (World Scientific, 2012). [World Scientific, arXiv]
DOI: 10.1142/9789814425285_0011

2. Ryo Tamura, Shu Tanaka, and Naoki Kawashima,
"A method to control order of phase transition: Invisible states in discrete spin models",
Kinki University Series on Quantum Computing Volume 7, pp. 217-238 (World Scientific, 2012). [World Scientific, arXiv, abstract]
DOI: 10.1142/9789814425285_0010

1. Shu Tanaka, Ryo Tamura, Issei Sato, and Kenichi Kurihara,
"Hybrid quantum annealing for clustering problems",
Kinki University Series on Quantum Computing Volume 5, pp. 169-192 (World Scientific, 2012). [World Scientific, arXiv]
DOI: 10.1142/9789814425988_0006


Book, Review
3. Ryo Tamura and Gaku Imamura
"Machine Learning Approaches in Nanoarchitectonics",
System-Materials Nanoarchitectonics pp 319–335 (Springer, 2022). [Springer]
ISBN: 4431569111



2. Shu Tanaka, Ryo Tamura, and Bikas K. Chakrabarti,
"Quantum spin glasses, annealing and computation"
(Cambridge University Press, 2017). [CAMBRIDGE UNIVERSITY PRESS]
ISBN: 9781107113190


1. Shu Tanaka and Ryo Tamura,
"Quantum annealing: from viewpoints of statistical physics, condensed matter physics, and computational physics",
"Lectures on Quantum Computing, Thermodynamics and Statistical Physics",
Kinki University Series on Quantum Computing Volume 8, pp. 3-59 (World Scientific, 2012). [World Scientific, arXiv]
DOI: 10.1142/9789814425193_0001