ストウブ・ルーベン

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ストウブ・ルーベン
特任助教
Co-PI（ヴァーネックグループ）
連絡先

ruben.staub atmark icredd.hokudai.ac.jp

アレクサンドル・ヴァーネック グループ
主任研究者
教員
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    ストウブ・ルーベン
博士研究員

研究紹介

研究テーマ

Prediction of chemically relevant properties using machine learning, for accelerating AFIR calculations

キーワード

Neural Networks Potentials, Machine Learning Force Fields, Active Learning

経歴

履歴書をご参照ください。

代表的な研究成果

Efficient recursive least squares solver for rank-deficient matrices
R. Staub, S. N. Steinmann, Appl. Math. Comput., 2021, 399, 125996
DOI: 10.1016/j.amc.2021.125996

DockOnSurf: A Python Code for the High-Throughput Screening of Flexible Molecules Adsorbed on Surfaces
C. Martí, S. Blanck, R. Staub, S. Loehlé, C. Michel, S. N. Steinmann, J. Chem. Inf. Model., 2021, 61, 3386-3396
DOI: 10.1021/acs.jcim.1c00256

Parameter-free coordination numbers for solutions and interfaces
R. Staub, S. N. Steinmann, J. Chem. Phys., 2020, 152, 024124
DOI: 10.1063/1.5135696

Water adlayers on noble metal surfaces: Insights from energy decomposition analysis
P. Clabaut, R. Staub, J. Galiana, E. Antonetti, S. N. Steinmann, J. Chem. Phys., 2020, 153, 054703
DOI: 10.1063/5.0013040

Energy Decomposition Analysis for Metal Surface–Adsorbate Interactions by Block Localized Wave Functions
R. Staub, M. Iannuzzi, R. Z. Khaliullin, S. N. Steinmann, J. Chem. Theory Comput., 2019, 15, 265-275
DOI: 10.1021/acs.jctc.8b00957

関連する研究記事

業績一覧

2026年

  • Predicting Enantioselectivity via Kinetic Simulations on Gigantic Reaction Path Networks
    Y. Harabuchi, R. Staub, M. Gao, N. Tsuji, B. List, A. Varnek, S. Maeda, ACS CENTRAL SCIENCE, 2026, ,
    DOI: 10.1021/acscentsci.6c00079
  • Toward Reaction Vessel Mimicry: Machine Learning-Assisted Automated Exploration of Alkene Polymerization and Its Transferability
    S. Ghorai, R. Staub, Y. Harabuchi, T. Nakano, A. Varnek, S. Maeda, J. Chem. Theory Comput., 2026, ,
    DOI: 10.1021/acs.jctc.5c02120

2025年

  • An Accurate and Efficient Reaction Path Search with Iteratively Trained Neural Network Potential: Answering the Passerini Mechanism Controversy
    R. Staub, Y. Harabuchi, C. Seraphim, A. Varnek, S. Maeda, J. Chem. Theory Comput., 2025, ,
    DOI: 10.1021/acs.jctc.5c01293
  • "Node" Facilitated Thermostable Mechanophores for Rapid Self-Strengthening in Double Network Materials
    J. Jiang, Z. Wang, R. Staub, Y. Harabuchi, A. Varnek, J. Gong, S. Maeda, Chem. Sci., 2025, 16, 14278-14285
    DOI: 10.1039/d5sc00151j

2024年

  • Chemography-Guided Analysis of a Reaction Path Network for Ethylene Hydrogenation with a Model Wilkinson's Catalyst
    P. Gantzer, R. Staub, Y. Harabuchi, S. Maeda, A. Varnek, Molecular Informatics, 2024, , e202400063
    DOI: 10.1002/minf.202400063

2023年

  • Challenges for Kinetics Predictions via Neural Network Potentials: A Wilkinson's Catalyst Case
    R. Staub, P. Gantzer, Y. Harabuchi, S. Maeda, A. Varnek, Molecules, 2023, 28 (11), 4477
    DOI: 10.3390/molecules28114477