Publications

  1. Lauren Takahashi, Taku Yamada, Hidekazu Okamoto, Keisuke Takahashi*
    Unveiling the relation between multiple chemical products and process conditions for trichloroethylene and perchloroethylene production via catalysis network analysis
    Catal. Sci. Technol. (2024) 14 (17), 4927-4938,

  2. Naotoshi Miyasaka, Fernando Gracia-Escobar, Keisuke Takahashi
    Automatic Identification of X-ray Absorption Fine Structure Spectra via Machine Learning
    J. Phys. Chem. C (2024), 128, 42, 17921–17927

  3. Tomoya Tashiro, Hajime Suzuki, Keisuke Takahashi*
    High-throughput calculation for screening of Formamidinium Halide Perovskite for Solar Cells
    Phys. Chem. Chem. Phys. (2024), 26 (19), 14440-14447

  4. Fernando Escober, Toshiaki Taniike, Keisuke Takahashi*
    MonteCat MonteCat - A Basin-hopping-inspired Catalyst Descriptor Search algorithm for Regression Models
    J. Chem. Inf. Model. (2024), 64, 5, 1512–1521

  5. Hajime Suzuki, Keisuke Takahashi*
    Theoretical Investigation of Cyanographene and Cyanographite for Potential Sodium Ion Battery
    Adv. Eng. Mater. (2024), 26 (7), 2301907

  6. Toshiaki Taniike, Aya Fujiwara, Sunao Nakanowatari, Fernando García-Escobar, Keisuke Takahashi
    Automatic feature engineering for catalyst design using small data without prior knowledge of target catalysis
    Comm. Chem. (2024), 7 (1), 11

  7. Yoshiki Hasukawa, Mikael Kuwahara, Lauren Takahashi, Keisuke Takahashi*
    Development of graphical user interface for design of experiments via Gaussian process regression and its case study
    STAM Methods. (2024), 4 (1), 2300252

  8. Mikael Kuwahara, Yu Harabuchi, Satoshi Maeda, Jun Fujima, Keisuke Takahashi*
    Searching chemical action and network (SCAN): an interactive chemical reaction path network platform
    Dig. Dis. (2023), 2 (4), 1104-1111

  9. Yuka Tsuchimura, Hiroshi Yoshida, Masato Machida, Shun Nishimura, Keisuke Takahashi, Junya Ohyama
    Investigation of the Active-Site Structure of Cu-CHA Catalysts for the Direct Oxidation of Methane to Methanol Using In Situ UV–Vis Spectroscopy
    Energy & Fuels. (2023), 6, 108–111

  10. Keisuke Takahashi*, Lauren Takahashi
    Toward the Golden Age of Materials Informatics: Perspective and Opportunities
    J. Phys. Chem. Lett. (2023), 14, 20, 4726–4733

  11. Hajime Suzuki, Keisuke Takahashi*
    2 Dimensional Dodecagonal Nitride and Graphenylene via First Principle Calculations
    ChemPhyChem. (2023), e202300115

  12. Fernando Garcia-Escobar, Shun Nishimura, Keisuke Takahashi*
    Data-Driven Design and Understanding of Noble Metal-Based Water–Gas Shift Catalysts from Literature Data
    J. Phys. Chem. C, (2023), 127, 13, 6152–6166

  13. Shun Nishimura, Xinyue Li, Junya Ohyama, Keisuke Takahashi*
    Leveraging Machine Learning Engineering to Uncover Insights in Heterogeneous Catalyst Design for Oxidative Coupling of Methane
    Catal. Sci. Technol (2023), 13, 4646-4655

  14. Fumiya Nishino, Hiroshi Yoshida, Masato Machida, Shun Nishimuraa Keisuke Takahashi, Junya Ohyama
    Indirect Design of OCM Catalysts through Machine Learning of Catalyst Surface Oxygen Species
    Catal. Sci. Technol (2023), In Press

  15. Toshiaki Taniike, Keisuke Takahashi*
    The value of negative results in data-driven catalysis research
    Nat. Catal. (2023), 6, 108–111

  16. Keisuke Takahashi*, Junya Ohyama, Shun Nishimura, Jun Fujima, Lauren Takahashi, Takeaki Uno, Toshiaki Taniike
    Catalysts informatics: paradigm shift towards data-driven catalyst design
    ChemComm. (2023), 59, 2222-2238

  17. Junya Ohyama*, Yuka Tsuchimura, Hiroshi Yoshida, Masato Machida, Shun Nishimura, Keisuke Takahashi*
    Bayesian-Optimization-Based Improvement of Cu-CHA Catalysts for Direct Partial Oxidation of CH4
    J. Phys. Chem. C (2022), 126, 46, 19660–19666

  18. Sora Ishioka, Aya Fujiwara, Sunao Nakanowatari, Lauren Takahashi, Toshiaki Taniike, Keisuke Takahashi*
    Designing Catalyst Descriptors for Machine Learning in Oxidative Coupling of Methane
    ACS Catal. (2022), 12 (19), 11541-11546

  19. Lauren Takahashi, Shigehiro Yoshida, Jun Fujima, Hiroshi Oikawa,Keisuke Takahashi*
    Unveiling the reaction pathways of hydrocarbons via experiments, computations and data science
    Phys. Chem. Chem. Phys. (2022),　24, 29841-29849

  20. Keisuke Takahashi*, Lauren Takahashi, Son Dinh Le, Takaaki Kinoshita, Shun Nishimura, and Junya Ohyama
    Synthesis of Heterogeneous Catalysts in Catalyst Informatics to Bridge Experiment and High-Throughput Calculation
    J. Am. Chem. Soc. (2022), 144, 34, 15735–15744

  21. Keisuke Takahashi*, Itsuki Miyazato, Satoshi Maeda, Lauren Takahashi
    Designing Transformer Oil Immersion Cooling Servers for Machine Learning and First Principle Calculations
    PLOS ONE (2022) 17 (5) e0266880

  22. Shun Nishimura*, Junya Ohyama, Xinyue Li, Itsuki Miyazato, Toshiaki Taniike, Keisuke Takahashi*
    Machine Learning-Aided Catalyst Modification in Oxidative Coupling of Methane via Manganese Promoter
    Ind. Eng. Chem. Res (2022) 61, 24, 8462-8469

  23. Vinit Kumar, Punit Kumar, Keisuke Takahashi, Pratibha Sharma*
    Hydrogen adsorption studies of TiFe surfaces via 3-d transition metal substitution
    Int. J. Hydrog. Energy (2022) 47 (36), 16156-16164

  24. Junya Ohyama*, Daiki Abe, Airi Hirayama, Hiroki Iwai, Yuka Tsuchimura, Kazuki Sakamoto, Momoka Irikura, Yuri Nakamura, Hiroshi Yoshida, Masato Machida, Shun Nishimura, Tomokazu Yamamoto, Syo Matsumura, Keisuke Takahashi
    Selective Oxidation of Methane to Formaldehyde over a Silica-Supported Cobalt Single-Atom Catalyst
    J. Phys. Chem. C (2022),126,4, 1785-1792

  25. Shun Nishimura, Son Dinh Le, Itsuki Miyazato, Jun Fujima, Toshiaki Taniike, Junya Ohyama, Keisuke Takahashi*
    High-throughput screening and literature data-driven machine learning-assisted investigation of multi-component La2O3-based catalysts for the oxidative coupling of methane
    Catal. Sci. Technol (2022), 12 (9), 2766-2774

  26. Junya Ohyama*, Yuka Tsuchimura, Airi Hirayama, Hiroki Iwai, Hiroshi Yoshida, Masato Machida, Shun Nishimura, Kazuo Kato, Keisuke Takahashi
    Relationships among the Catalytic Performance, Redox Activity, and Structure of Cu-CHA Catalysts for the Direct Oxidation of Methane to Methanol Investigated Using In Situ XAFS and UV–Vis Spectroscopies
    ACS Catal.(2022), 12, 2454-2462

  27. Hajime Suzuki, Itsuki Miyazato, Tanveer Hussain, Fatih Ersan, Satoshi Maeda, Keisuke Takahashi*
    Designing two-dimensional dodecagonal boron nitride
    CrystEngComm (2022), 24, 471-474

  28. Thanh Nhat Nguyen, Kalaivani Seenivasan, Sunao Nakanowatari, Priyank Mohan, Thuy Phuong Nhat Tran, Shun Nishimura, Keisuke Takahashi, Toshiaki Taniike*
    Factors to influence low-temperature performance of supported Mn–Na2WO4 in oxidative coupling of methane
    Mol. Cat (2021), 516, 111976

  29. Lauren Takahashi*, Thanh Nhat Nguyen, Sunao Nakanowatari, Aya Fujiwara, Toshiaki Taniike, Keisuke Takahashi*
    Constructing catalyst knowledge networks from catalyst big data in oxidative coupling of methane for designing catalysts
    Chem. Sci (2021), 12, 12546-12555フロントカバー・Pick of the week　プレスリリース

  30. Keisuke Takahashi*, Jun Fujima, Itsuki Miyazato, Sunao Nakanowatari, Aya Fujiwara, Thanh Nhat Nguyen, Toshiaki Taniike, Lauren Takahashi
    Catalysis Gene Expression Profiling: Sequencing and Designing Catalysts
    J. Phys. Chem. Lett, (2021), 12 30 7335-7341　プレスリリース

  31. Xucheng Zhang, Yanran Li, Yiting Feng, Jia Guo, Keisuke Takahashi*, Changchun Wang
    Quick approach for optimization of monodisperse microsphere synthesis with a knowledge sharing strategy powered by machine learning
    Chem. Phys. Lett, (2021), 780 138908

  32. Sora Ishioka, Itsuki Miyazato, Lauren Takahashi, Thanh Nhat Nguyen, Toshiaki Taniike, Keisuke Takahashi*
    Unveiling gas-phase oxidative coupling of methane via data analysis
    J. Comput. Chem, (2021), 42 20 1447-1451

  33. Keisuke Takahashi*, Satoshi Maeda
    Mining hydroformylation in complex reaction network via graph theory†
    RSC Adv, (2021), 11, 23235-23240

  34. Sunao Nakanowatari, Thanh Nhat Nguyen, Hiroki Chikuma, Aya Fujiwara, Kalaivani Seenivasan, Ashutosh Thakur, Lauren Takahashi, Keisuke Takahashi, Toshiaki Taniike*
    Extraction of catalyst design heuristics from random catalyst dataset and their utilization in catalyst development for oxidative coupling of methane
    ChemCatChem, (2021), 13, 14 3262-3269

  35. Junya Ohyama*, Airi Hirayama, Yuka Tsuchimura, Nahoko Kondou, Hiroshi Yoshida, Masato Machida, Shun Nishimura, Kazuo Kato, Itsuki Miyazato, Keisuke Takahashi
    Catalytic direct oxidation of methane to methanol by redox of copper mordenite
    Catal. Sci. Technol, (2021), 11, 10 3437-3446

  36. Airi Hirayama, Yuka Tsuchimura, Hiroshi Yoshida, Masato Machida, Shun Nishimura, Kazuo Kato, Keisuke Takahashi, Keisuke Takahashi, Junya Ohyama*
    Catalytic oxidation of methane to methanol over Cu-CHA with molecular oxygen
    Catal. Sci. Technol, (2021), 11, 6217-6224

  37. J. Ohyama, A.Hirayama, N.Kondo, H. Yoshida, M. Machida, S. Nishimura, K.Hirai, I. Miyazato, Keisuke Takahashi*
    Data science assisted investigation of catalytically active copper hydrate in zeolites for direct oxidation of methane to methanol using H2O2
    Sci. Rep, (2021), 11, 2067

  38. T.N.Ngyuyen, S.Nakanowatari, T.T.P.Nhat, A.Thakur, L. Takahashi, Keisuke Takahashi*, T.Taniike
    Learning Catalyst Design Based on Bias-Free Data Set for Oxidative Coupling of Methane
    Acs Catal, (2021), 11, 1797-1809　プレスリリース

  39. L. Takahashi, J. Ohyama, S. Nishimura, Keisuke Takahashi*
    Representing the Methane Oxidation Reaction via Linking First-Principles Calculations and Experiment with Graph Theory
    J. Phys. Chem. Lett., (2021), 12, 558-568

  40. I. Miyazato, T.N.Ngyuyen, L. Takahashi, T.Taniike, Keisuke Takahashi*
    Representing Catalytic and Processing Space in Methane Oxidation Reaction via Multioutput Machine Learning
    J. Phys. Chem. Lett., (2021), 12, 808-814

  41. K. Sugiyama, T.N.Ngyuyen, S.Nakanowatari, I. Miyazato, T.Taniike, Keisuke Takahashi*
    Direct Design of Catalysts in Oxidative Coupling of Methane via High‐Throughput Experiment and Deep Learning
    ChemCatChem, (2021), 13, 952-957

  42. J. Ohyama, T.Kinoshita, E.Funada, H. Yoshida, M. Machida, S. Nishimura, T. Uno, J.Fujima, I. Miyazato, L. Takahashi, Keisuke Takahashi*
    Direct Design of Active Catalysts for Low Temperature Oxidative Coupling of Methane via Machine Learning and Data Mining
    Catal. Sci. Technol., (2021), 11, 524-530

  43. Shun Nishimura, Junya Ohyama, Takaaki Kinoshita,Son Dinh Le, Keisuke Takahashi*
    Revisiting Machine Learning Predictions for Oxidative Coupling of Methane (OCM) based on Literature Data
    ChemCatChem (2020) 12 (23), 5888-5892 フロントカバー

  44. Keisuke Takahashi*, Lauren Takahashi, Thanh Nhat Nguyen, Ashutosh Thakur, Toshiaki Taniike
    Multi-Dimensional Classification of Catalysts in Oxidative Coupling of Methane through Machine Learning and High-Throughput Data
    J. Phys. Chem. Lett (2020) 11, 16, 6819–6826

  45. Itsuki Miyazato, Tanveer Hussain, Keisuke Takahashi
    Transition of wide-band gap semiconductor h-BN(BN)/P heterostructure via single-atom-embedding
    J. Phys. Chem. C (2020) 8, 9755-9762

  46. Jun Fujima, Yuzuru Tanaka, Itsuki Miyazato, Lauren Takahashi, Jun Fujima, Keisuke Takahashi*
    Catalyst Acquisition by Data Science (CADS): a web-based catalyst informatics platform for discovering catalysts
    React. Chem. Eng. (2020) 5 (5), 903-911　プレスリリース

  47. Rafael Monteiro, Itsuki Miyazato, Keisuke Takahashi*
    Rising Sun Envelope Method: An Automatic and Accurate Peak Location Technique for XANES Measurements
    J. Phys. Chem. A (2020) 124 (9), pp 1754–1762

  48. Itsuki Miyazato, Shun Nishimura, Lauren Takahashi, Junya Ohyama, Keisuke Takahashi*
    Data-Driven Identification of the Reaction Network in Oxidative Coupling of the Methane Reaction via Experimental Data
    J. Phys. Chem. Lett (2020) 10 (2), pp 283–288

  49. Vinit Kumar,Punit Kumar,Subhasis Pati,Pratibha Sharma, Keisuke Takahashi
    Tuning the hydrogen storage properties of TiFe clusters via Zr substitution
    Energy Storage (2020) e157

  50. Keisuke Takahashi*
    First-Principles Design of Cu12shellFecore Core–Shell Clusters Assembled with K3O into Hexameric Rings: Implications for Gas-Storage Materials
    ACS Appl. Nano Mater. (2020) 3 (1),55–58

  51. Thanh Nhat Nguyen, Thuy Tran Phuong Nhat, Ken Takimoto, Ashutosh Thakur, Shun Nishimura, Junya Ohyama, Itsuki Miyazato, Lauren Takahashi, Jun Fujima, Keisuke Takahashi, Toshiaki Taniike
    High-Throughput Experimentation and Catalyst Informatics for Oxidative Coupling of Methane
    ACS Catal (2020) 10 (2), 921–932　プレスリリース

  52. Lauren Takahashi, Keisuke Takahashi*
    Visualizing Scientists’ Cognitive Representation of Materials Data through the Application of Ontology
    J. Phys. Chem. Lett.(Perspective) (2019) 10 (23), 7482–7491

  53. Itsuki Miyazato, Sevil Sarikurt. Keisuke Takahashi, Fatih Ersan
    Controlling electronic structure of single-layered HfX3 (X=S,Se) trichalcogenides through systematic Zr doping
    Journal of Materials Science (2020) 55, 660–669

  54. Keisuke Takahashi*, Lauren Takahashi
    Data Driven Determination in Growth of Silver from Clusters to Nanoparticles and Bulk
    J. Phys. Chem. Lett. (2019) 10 (14), 4063–4068

  55. Junya Ohyama, Shun Nishimura, Keisuke Takahashi*
    Data Driven Determination of Reaction Conditions in Oxidative Coupling of Methane via Machine Learning
    ChemCatChem (2019) 11 (17), 4307–4313

  56. Itsuki Miyazato, Keisuke Takahashi*, Lauren Takahashi
    Automatic oxidation threshold recognition of XAFS data using supervised machine learning
    M Mol. Syst. Des. Eng (2019) 4 (5), 1014–1018

  57. Keisuke Takahashi*, Lauren Takahashi
    Creating Machine Learning-Driven Material Recipes Based on Crystal Structure
    J. Phys. Chem. Lett. (2019) 10 (2), 283–288

  58. Keisuke Takahashi*, Lauren Takahashi
    Functionalized Single-Atom-Embedded Bilayer Graphene and Hexagonal Boron Nitride
    ACS Appl. Electron. Mater. (2019) 1 (1), pp 2–6

  59. Duong-Nguyen Nguyen, Tien-Lam Pham, Viet-Cuong Nguyen, Tuan-Dung Ho, Truyen Tran, Keisuke Takahashi, Hieu-Chi Dam
    Committee machine that votes for similarity between materials
    IUCrJ (2018) 5, 6, 830,840

  60. Keisuke Takahashi*, Lauren Takahashi, Itsuki Miyazato, Jun Fujima, Yuzuru Tanaka, Takeaki Uno, Hiroko Satoh, Koichi Ohno, Mayumi Nishida, Kenji Hirai, Junya Ohyama, Thanh Nhat Nguyen, Shun Nishimura, Toshiaki Taniike
    The Rise of Catalyst Informatics: Towards Catalyst Genomics
    ChemCatChem (2018) 11, 4, 1146-1152

  61. Lauren Takahashi, Itsuki Miyazato, Keisuke Takahashi*
    Redesigning the Materials and Catalysts Database Construction Process Using Ontologies
    J. Chem. Inf. Model. (2018)58, 9, 1742-1754

  62. Keisuke Takahashi*, Itsuki Miyazato
    Rapid estimation of activation energy in heterogeneous catalytic reactions via machine learning
    J. Comput. Chem (2018) 39, 28, 2405-2408

  63. Keisuke Takahashi*, Itsuki Miyazato, Shun Nishimura, Junya Ohyama
    Unveiling hidden catalysts for the oxidative coupling of methane based on combining machine learning and literature data
    ChemCatChem (2018) 10 (15), 3223-3228(Very Important Paperとインタビュー記事)

  64. Farheen Khurshid, M Jeyavelan, Keisuke Takahashi, M. Sterlin Leo Hudson, Samuthira Nagarajan*
    Aryloride functionalized graphene oxides for excellent room temperature ammonia sensitivity/selectivity
    RSC Adv (2018) 8 (36), (2018), 20440-20449

  65. Keisuke Takahashi*
    Uncovering hidden trend and periodicity for predicting the magnetic moment in body centered cubic crystal
    ChemPhysChem (2018) 19, 13, 1593-1598 フロントカバー

  66. Lauren Takahashi, Keisuke Takahashi*
    Geometric and electronic structure of AlP nanotube with octagonal lattice configuration
    ACS Appl. Nano Mater. (2018), 1 (2), 501504

  67. Keisuke Takahashi*, Lauren Takahashi, Itsuki Miyazato, Yuzuru Tanaka
    Exploring hidden perovskite metal oxides for solar cell applications via data science
    ACS Photonics (2018) 5 (3), 771775

  68. Itsuki Miyazato, Yuzuru Tanaka, Keisuke Takahashi*
    Accelerating the discovery of hidden two-dimensional magnets using machine learning and first principle calculations
    J. Phys. Condens. Matter (2018) 6, 30

  69. Keisuke Takahashi*
    Designing a tunable magnet using cluster-assembled iron
    J. Appl. Phys (2018) 123, 015102

  70. Lauren Takahashi, Tessui Nakagawa, Keisuke Takahashi*
    Electronic structure of octagonal boron nitride nanotubes
    Int. J. Quantum Chem (2018) 118 (11), e25542

  71. Itsuki Miyazato, Keisuke Takahashi*
    Revealing the multi hydrogen bonding state within iron doped amorphous carbon
    Chem. Phys. Lett (2018) 691,122-125

  72. Jakub D Baran, Christopher Eames, Keisuke Takahashi, Marco Molinari, M Saiful Islam, Stephen C Parker*
    Structural, Electronic, and Transport Properties of Hybrid SrTiO3-Graphene and Carbon Nanoribbon Interfaces
    Chem. Mater (2017) 29 (17), 7364-7370

  73. Itsuki Miyazato, Keisuke Takahashi*
    Electronic structure of boron based single and multi-layer two dimensional materials
    J. Appl. Phys (2017) 122 (10), 104302

  74. Lauren Takahashi, Keisuke Takahashi*
    Structural stability and electronic properties of an octagonal allotrope of two dimensional boron nitride
    Dalton Trans (2017) 46 (13), 4259-4264

  75. Keisuke Takahashi*, Lauren Takahashi, Jakub D Baran, Yuzuru Tanaka
    Descriptors for predicting the lattice constant of body centered cubic crystal
    J. Chem. Phys (2017) 146 (20), 204104

  76. Lauren Takahashi, Keisuke Takahashi*
    Structural stability and electronic properties of an octagonal allotrope of two dimensional boron nitride
    Dalton Trans 46 13 (2017), 4259-4264

  77. Keisuke Takahashi*, Yuzuru Tanaka
    Unveiling descriptors for predicting the bulk modulus of amorphous carbon
    Phys. Rev. B (2017) 95 (5), 054110

  78. Alvaro Munoz*, Keisuke Takahashi
    Towards Two-Dimensional Ge9-Cluster Based Materials. Computational Evaluation of [Ge9(Si(SiMe3))3]- Aggregates
    J. Phys. Chem. C 121 3 (2017) 1934-1940

  79. Keisuke Takahashi*, Yuzuru Tanaka
    Role of descriptors in predicting the dissolution energy of embedded oxides and the bulk modulus of oxide-embedded iron
    Phys. Rev. B (2016) 95 (1), 014101

  80. Lauren Takahashi, Keisuke Takahashi*
    Designing Mg7 cluster-assembled two dimensional crystal
    Flat Chem (2016) 1, 57-59

  81. Tengfei Zhange*, Shigehito Isobe, Yongming Wang, Chaomei Liu, Naoyuki Hashimoto, Keisuke Takahashi
    Enhanced hydrogen desorption properties of LiAlH4 by doping lithium metatitanate
    Phys. Chem. Chem. Phys. (2016) 18, 27623-27629

  82. Lauren Takahashi, Keisuke Takahashi*
    Reactivity of two dimensional Au9, Pt9, and Au18Pt18 against common gas molecules
    Inorg. Chem. (2016) 55 (18), 9410-9416

  83. Keisuke Takahashi*, Yuzuru Tanaka
    “Material Informatics: Journey towards Material Design and Synthesis
    Dalton Trans, (Perspectives) (2016) 45, 10497-10499

  84. Keisuke Takahashi*, Yuki Nakagawa, Lauren Takahashi, Shigehito Isobe
    Prediction of catalytic activities of ammonia borane by dual descriptors: electronegativity and crystal structure
    New J. Chem. (2016),40 (9), 7303-7306

  85. Keisuke Takahashi*, Shigehito Isobe, Kengo Omori,Torge Masho, Domenica Convertino, Vaidotas Miseikis, Camilla Coletti,Valentina Tozzini, Stephan Heun
    Revealing the multi-bonding state between hydrogen and Ti clusters supported graphene
    J. Phys. Chem. C (2016), 120 (24), 12974-12979

  86. Tanveer Hussain, Debra Searles, Keisuke Takahashi*
    Reversible Hydrogen Uptake by BN and BC3 Monolayers Functionalized with Small Fe Clusters: A Route to Effective Energy Storage
    J. Phys. Chem. A (2016) 120 (12), 20092013

  87. Keisuke Takahashi*, Tanveer Hussain, Lauren Takahashi, Jakub B Baran
    Designing square two dimensional gold and platinum
    Cryst. Growth Des., (2016) 16 (3), 1746–1750

  88. Keisuke Takahashi*, Hiroshi Oka, Somei Ohnuki
    Selective growth of noble gases at metal/oxide interface
    A CS Appl. Mater. Interfaces, (2016) 8 (6), 3725–3729

  89. Keisuke Takahashi*, Lauren. Takahashi
    Hydrophobic and antioxidant effects in In, Sn, and Sb based two dimensional materials
    Dalton Trans, (2016) 45, 3244-3246 (Hot Articleとして掲載)

  90. Keisuke Takahashi*, Yuzuru Tanaka
    Material synthesis and design from first principle calculations and machine learning
    Comput. Mater. Sci., 112 (2016), 364-367

  91. M Sterlin Leo Hudson*, Keisuke Takahashi, A Ramesh, Seema Awasthi, Ashish Kumar Ghosh, Ponniah Ravindran, Onkar Nath Srivastava*
    Graphene decorated with Fe nanoclusters for improving the hydrogen sorption kinetics of MgH2 – Experimental and theoretical evidence
    Catal. Sci. Technol., 6 1 (2016), 261-268

  92. Lauren Takahashi, Keisuke Takahashi*
    Low temperature pollutant trapping and dissociation over two-dimensional tin
    Phys. Chem. Chem. Phys, (2015), 17 (33), 21394-21396

  93. Keisuke Takahashi*
    Iron oxide cluster induced barrier-free conversion of nitric oxide to ammonia
    Chem. Commun, 51 (2015), 4062-4064

  94. Seiji Sakuraya, Keisuke Takahashi*, Naoyuki Hashimoto, Somei Ohnuki
    The effect of point defects on diffusion pathway within α-Fe
    J. Phys. Condens. Matter, 27 (2015) 175007 (論文誌の表紙に採用)

  95. Nobuko Hanada*, Tessui Nakagawa, Hirotaka Asada, Masayoshi Ishida, Keisuke Takahashi, Shigehito Isobe, Itoko Saita, Kohta Asano, Yumiko Nakamura, Akitoshi Fujisawa, Shinichi Miura
    Dependence of constituent elements of AB5 type metal hydrides on hydrogenation degradation by CO2 poisoning
    J. Alloys Compd, 647 (2015) 198-203

  96. Keisuke Takahashi*
    The growth of Fe clusters over graphene
    2D Materials, 2 (2015), 014001

  97. Keisuke Takahashi*, Shigehito Isobe
    Enhancing the hydrogen storage capacity of TiFe by utilizing clusters
    Phys. Chem. Chem. Phys, 16 (2014), 16765-16770

  98. Keisuke Takahashi*, Yongming Wang, Shotaro Chiba, Yuki Nakagawa, Shigehito Isobe, Somei Ohnuki
    Low temperature hydrogenation of iron nanoparticles on graphene
    Sci. Rep, 4 (2014), 4598

  99. Seiji Sakuraya, Keisuke Takahashi*, Shuai Wang, Naoyuki Hashimoto, Somei Ohnuki
    Physical properties of α-Fe upon the introduction of H, He, C, and N
    Solid State Commun 195 (2014) 7073

  100. Keisuke Takahashi*, Shigehito Isobe, Somei Ohnuki
    The stabilization of Fe, Ru, and Os clusters upon hydrogenation
    RSC Adv. 3 (2013), 21841-21847

  101. Keisuke Takahashi*, Shigehito Isobe, Somei Ohnuki
    The catalytic effect of Nb, NbO and Nb2O5 with different surface plane on dehydrogenation in MgH2: Density functional theory study
    J. Alloys Compd. 580 (2013), S25-S28

  102. Keisuke Takahashi*, Shigehito Isobe, Somei Ohnuki
    H2 dissociation over NbO: The first step towards hydrogenation of Mg
    Langmuir 29 38 (2013), 12059-12065

  103. Keisuke Takahashi*, Shigehito Isobe, Somei Ohnuki
    Erratum:Chemisorption of hydrogen on Fe clusters through hybrid bonding mechanisms
    Appl. Phys. Lett., 102 (2013), 113108-113108

  104. Keisuke Takahashi*, Shigehito Isobe, Somei Ohnuki
    Chemisorption of hydrogen on Fe clusters through hybrid bonding mechanisms
    Appl. Phys. Lett., 102 (2013): 113108-113108

  105. Shuai Wang*, Keisuke Takahashi, Naoyuki Hashimoto, Shigehito Isobe, Somei Ohnuki
    A density function theory study of hydrogen-induced local strain field in b.c.c. iron and its effect on dislocation motion
    Scr. Mater 68 (2013): 249–252

  106. Keisuke Takahashi*, Shigehito Isobe, Somei Ohnuki
    The Structural and Electronic Properties of Small Osmium Clusters (2-14): A Density Functional Theory Study
    Chem. Phys. Lett, 555 (2013): 26–30

  107. Tao Ma*, Shigehito Isobe, Keisuke Takahashi, Shuai Wang, Yongming Wang, Naoyuki Hashimoto, Somei Ohnuki
    Phase Transition of Mg during Hydrogenation of Mg–Nb2O5 Evaporated Composites
    J. Phys. Chem. C 116 32 (2012), 17089-17093