Researcher basic information

• Doctor of Engineering, Chemical Engineering, The University of Tokyo, Jan. 2020
• Master of Science, Applied IT, Gothenburg University, Oct. 2011
• Bachelor of Art, Linguistics, The University of Arizona, Dec. 2008

• https://researchmap.jp/lnt?lang=en

• https://orcid.org/0000-0001-9922-8889
• https://jglobal.jst.go.jp/detail?JGLOBAL_ID=201901002390162772
• https://takahashigroup.github.io/

• 30865069

• https://orcid.org/0000-0001-9922-8889

• 201901002390162772

• Informatics, Robotics and intelligent system, Lab Automation, Catalyst Development Robotics
• Nanotechnology/Materials, Inorganic compounds and inorganic materials chemistry, Catalysis, Catalyst Design, Reaction Networks
• Informatics, Mathematical informatics, Graph Theory, Machine Learning, Data Science
• Informatics, Database, Ontology, Data Preprocessing
• Nanotechnology/Materials, Structural materials and functional materials, 2D Materials, Cluster-Assembled Materials
• Nanotechnology/Materials, Applied condensed matter physics, First Principles Calculations, DFT
• Humanities & Social Sciences, Linguistics, Semantics, Natural Language Processing, Descriptive Logic

• Bachelor's degree program, School of Science
• Master's degree program, Graduate School of Chemical Sciences and Engineering
• Doctoral (PhD) degree program, Graduate School of Chemical Sciences and Engineering

Research activity information

• Design and fabrication of a low-cost 3D-printed pH sensor positioning robot for laboratory automation
  Shinnosuke Yorozuya; Mikael Kuwahara; Koki Sakamoto; Keisuke Takahashi; Lauren Takahashi
  Science and Technology of Advanced Materials: Methods, 31 Dec. 2026
  Scientific journal
• Effect of Vegetable Feedstock Minerals on Biochar Structure and CO2 Uptake
  Koki Sakamoto; Yoshiki Hasukawa; Rensuke Koiwai; Tomoya Tashiro; Fernando Garcia-Escobar; Lauren Takahashi; Keisuke Takahashi
  ACS Omega, 11 Aug. 2026
  Scientific journal
• Materials informatics for glass ionomer cements: key features and design
  Kenta Tsuchiya; Atsushi Tomokiyo; Lauren Takahashi; Salvatore Sauro; James Kit Hon Tsoi; Jukka P. Matinlinna; Monica Yamauti; Akira Hasebe; Hidehiko Sano; Keisuke Takahashi
  Dental Materials, 42, 7, 1105, 1111, Elsevier BV, Jul. 2026
  Scientific journal
• Descriptor Identification and Synthesis of Bimetallic Catalysts for CO ₂ Methanation
  Yoshiki Hasukawa; Fernando Garcia-Escobar; Shun Nishimura; Lauren Takahashi; Keisuke Takahashi
  ACS Catalysis, 16, 4, 3188, 3197, American Chemical Society (ACS), 31 Jan. 2026
  Scientific journal
• Web-based graphical interface for catalyst gene design and profiling
  Kenshin Shibata; Mikael Kuwahara; Yoshiki Hasukawa; Fernando Garcia-Escobar; Lauren Takahashi; Keisuke Takahashi
  Science and Technology of Advanced Materials: Methods, 6, 1, Informa UK Limited, 29 Jan. 2026
  Scientific journal
• Temperature-tunable Fabry–Perot cavity for aqueous systems
  Masaki Itatani; Nobuki Iwasa; Naotoshi Miyasaka; Lauren Takahashi; Keisuke Takahashi; Tomohiro Fukushima; Kei Murakoshi
  Research on Chemical Intermediates, 52, 3, 1791, 1805, Springer Science and Business Media LLC, 16 Jan. 2026
  Scientific journal
• Designing Anode Materials for Proton Exchange Membrane Electrolysis via Literature Data and Machine Learning
  Fernando Garcia-Escobar; Tomoya Tashiro; Naotoshi Miyasaka; Rensuke Koiwai; Lauren Takahashi; Keisuke Takahashi
  ACS Applied Energy Materials, 9, 2, 842, 852, American Chemical Society (ACS), 05 Jan. 2026
  Scientific journal
• Importance of consistent and well-dispersed catalyst datasets for machine learning in oxidative coupling of methane
  Hinata Sudo; Yoshiki Hasukawa; Rensuke Koiwai; Fernando Garcia-Escobar; Shun Nishimura; Lauren Takahashi; Keisuke Takahashi
  Catalysis Science & Technology, 16, 11, 3791, 3798, Royal Society of Chemistry (RSC), 2026
  Scientific journal, The role of highly uniform, diverse experimental data in catalyst informatics is examined using an oxidative coupling of methane dataset measured by a single researcher under consistent devices and conditions.
• Design rules for ternary CO ₂ hydrogenation catalysts via literature-sourced network construction and analysis
  Yoshiki Hasukawa; Fernando Garcia-Escobar; Shun Nishimura; Keisuke Takahashi; Lauren Takahashi
  Chemical Science, 17, 22, 11127, 11139, Royal Society of Chemistry (RSC), 2026
  Scientific journal, Ternary catalyst design for CO ₂ hydrogenation is conducted via network analysis and experimental validation.
• Compatibility Diagnosis for the Design of Oxidative Coupling of Methane Catalysts
  Kei Kobayashi; Fernando Garcia-Escobar; Yoshiki Hasukawa; Rensuke Koiwai; Lauren Takahashi; Keisuke Takahashi
  The Journal of Physical Chemistry Letters, 12177, 12183, American Chemical Society (ACS), 15 Nov. 2025
  Scientific journal
• Unique Phase Evolution and Multielemental Effects in Natural Rhodochrosite for Methane Oxidation
  Rensuke Koiwai; Fernando Garcia‐Escobar; Koki Sakamoto; Lauren Takahashi; Keisuke Takahashi
  Chemistry – A European Journal, 31, 62, Wiley, 09 Oct. 2025
  Scientific journal, Abstract
  
  Rhodochrosite, a naturally occurring ‐based mineral with inherent compositional complexity, is investigated as a catalyst for methane oxidation. The material exhibits distinctive catalytic behavior, including enhanced hydrocarbon formation and selective CO production, attributed to its multielemental composition and dynamic phase transformations under reaction conditions. In particular, rhodochrosite suppresses CO formation while enhancing production compared to pure , the primary component of rhodochrosite. Thermal treatment converts rhodochrosite into mixed manganese oxide phases (, ), while trace elements and mineral impurities are retained and may influence oxide phase evolution and catalytic behavior. These findings highlight the potential of natural multicomponent minerals as compositionally diverse, phase‐adaptive platforms for selective methane conversion.
• Designing and synthesizing perovskites with targeted bandgaps via tailored descriptors
  Kenshin Shibata; Fernando Garcia-Escobar; Tomoya Tashiro; Lauren Takahashi; Keisuke Takahashi
  Chemical Science, 16, 36, 16703, 16711, Royal Society of Chemistry (RSC), Aug. 2025
  Scientific journal, Descriptors for representing bandgaps of perovskite materials are identified using machine learning and literature data, and predicted perovskite materials for solar energy applications are synthesized experimentally.
• AI and automation: democratizing automation and the evolution towards true AI-autonomous robotics
  Lauren Takahashi; Mikael Kuwahara; Keisuke Takahashi
  Chemical Science, 16, 35, 15769, 15780, Royal Society of Chemistry (RSC), Aug. 2025
  Scientific journal, Through artificial intelligence and robotics, autonomous labs are transforming chemical and materials research by enabling high-throughput, data-driven experiments with minimal human input.
• Development of an Open-Source 3D-Printed Material Synthesis Robot FLUID: Hardware and Software Blueprints for Accessible Automation in Materials Science
  Mikael Kuwahara; Yoshiki Hasukawa; Fernando Garcia-Escobar; Satoshi Maeda; Lauren Takahashi; Keisuke Takahashi
  ACS Applied Engineering Materials, 3, 4, 978, 987, American Chemical Society (ACS), 08 Apr. 2025
  Scientific journal
• Web-based graphical user interface for automated materials feature engineering for machine learning
  Yoshiki Hasukawa; Mikael Kuwahara; Fernando Garcia-Escobar; Lauren Takahashi; Toshiaki Taniike; Keisuke Takahashi
  Science and Technology of Advanced Materials: Methods, 5, 1, Informa UK Limited, 08 Jan. 2025
  Scientific journal
• Web-based graphical user interface for visualizing and analyzing chemical reaction networks
  Akihiro Honda; Mikael Kuwahara; Yoshiki Hasukawa; Keisuke Takahashi; Lauren Takahashi
  Reaction Chemistry & Engineering, 10, 9, 2062, 2066, Royal Society of Chemistry (RSC), 2025
  Scientific journal, A graphical user interface for network visualization and analysis is proposed, integrated within the Catalyst Acquisition by Data Science (CADS) platform to simplify the study of chemical reaction networks.
• Design of low temperature La₂O₃ oxidative coupling of methane catalysts using feature engineering and automated sampling
  Fernando Garcia-Escobar; Lauren Takahashi; Ali Shaaban; Shun Nishimura; Keisuke Takahashi
  Catalysis Science & Technology, 15, 1, 92, 99, Royal Society of Chemistry (RSC), 2025
  Scientific journal, Machine learning with feature engineering is employed to design heterogeneous catalysts for the oxidative coupling of methane, resulting in the identification of four active catalysts whose catalytic activities are experimentally validated.
• Multidimensional Catalysis Data Representation for Designing Oxidative Coupling of Methane Catalysts
  Yoshiki Hasukawa; Fernando Garcia-Escobar; Keisuke Takahashi; Lauren Takahashi
  The Journal of Physical Chemistry C, 129, 1, 391, 401, American Chemical Society (ACS), 19 Dec. 2024
  Scientific journal
• Development of graphical user interface for design of experiments via Gaussian process regression and its case study
  Yoshiki Hasukawa; Mikael Kuwahara; Lauren Takahashi; Keisuke Takahashi
  Science and Technology of Advanced Materials: Methods, 4, 1, Informa UK Limited, 16 Jan. 2024
  Scientific journal
• Unveiling the relation between multiple chemical products and process conditions for trichloroethylene and perchloroethylene production via catalysis network analysis
  Lauren Takahashi; Taku Yamada; Hidekazu Okamoto; Keisuke Takahashi
  Catalysis Science & Technology, 14, 17, 4927, 4938, Royal Society of Chemistry (RSC), 2024
  Scientific journal, Unveiling the complex condition for producing trichloroethylene & perchloroethylene.
• Unsupervised Machine Learning and Beyond Machine Learning
  Keisuke Takahashi; Lauren Takahashi
  2024
• Machine Learning
  Keisuke Takahashi; Lauren Takahashi
  2024
• Supervised Machine Learning
  Keisuke Takahashi; Lauren Takahashi
  2024
• Programming
  Keisuke Takahashi; Lauren Takahashi
  2024
• Data Visualization
  Keisuke Takahashi; Lauren Takahashi
  2024
• Programming and Python
  Keisuke Takahashi; Lauren Takahashi
  2024
• Developing an Informatics Work Environment
  Keisuke Takahashi; Lauren Takahashi
  2024
• Materials Informatics and Catalysts Informatics
  Keisuke Takahashi; Lauren Takahashi
  ACS Symposium Series, 239, 246, American Chemical Society, 2024
• An Introduction to Materials Informatics and Catalysts Informatics
  Keisuke Takahashi; Lauren Takahashi
  Materials Informatics and Catalysts Informatics, 1, 24, Springer Nature Singapore, 29 Dec. 2023
  In book
• Toward the Golden Age of Materials Informatics: Perspective and Opportunities
  Keisuke Takahashi; Lauren Takahashi
  The Journal of Physical Chemistry Letters, 14, 20, 4726, 4733, American Chemical Society (ACS), 12 May 2023
  Scientific journal
• Improving scientific image processing accessibility through development of graphical user interfaces for scikit-image
  Mikael Kuwahara; Jun Fujima; Keisuke Takahashi; Lauren Takahashi
  Digital Discovery, 2, 3, 775, 780, Royal Society of Chemistry (RSC), 2023
  Scientific journal, Catalyst informatics has garnered a lot of attention within the research community as it is a very powerful method for discovering and understanding catalysts from the data perspective.
• Catalysts informatics: paradigm shift towards data-driven catalyst design
  Keisuke Takahashi; Junya Ohyama; Shun Nishimura; Jun Fujima; Lauren Takahashi; Takeaki Uno; Toshiaki Taniike
  Chemical Communications, 59, 16, 2222, 2238, Royal Society of Chemistry (RSC), 2023
  Scientific journal, This work summarizes how catalysts informatics plays a role in catalyst design.
• The Rise of Catalysts Informatics
  Keisuke Takahashi; Lauren Takahashi; Shun Nishimura; Jun Fujima; Junya Ohyama
  Crystalline Metal Oxide Catalysts, 349, 371, Springer Nature Singapore, 26 Oct. 2022
  In book
• Designing Catalyst Descriptors for Machine Learning in Oxidative Coupling of Methane
  Sora Ishioka; Aya Fujiwara; Sunao Nakanowatari; Lauren Takahashi; Toshiaki Taniike; Keisuke Takahashi
  ACS Catalysis, 12, 19, 11541, 11546, American Chemical Society (ACS), 08 Sep. 2022
  Scientific journal
• Synthesis of Heterogeneous Catalysts in Catalyst Informatics to Bridge Experiment and High-Throughput Calculation
  Keisuke Takahashi; Lauren Takahashi; Son Dinh Le; Takaaki Kinoshita; Shun Nishimura; Junya Ohyama
  Journal of the American Chemical Society, 144, 34, 15735, 15744, American Chemical Society (ACS), 19 Aug. 2022
  Scientific journal
• Designing transformer oil immersion cooling servers for machine learning and first principle calculations
  Keisuke Takahashi; Itsuki Miyazato; Satoshi Maeda; Lauren Takahashi
  PLOS ONE, 17, 5, e0266880, e0266880, Public Library of Science (PLoS), 17 May 2022
  Scientific journal, A transfomer oil immersion cooling server is designed and constructed for machine learning applications and first principle calculations that are carried out for materials-related research. CPU, motherboard, random access memory, hard disk drive, solid state drive, graphic card, and the power supply unit are submerged into the transformer oil in order to cool the entire system. Benchmark tests reveal that overall performance is improved while performance times for multicore calculations are dramatically improved. Furthermore, calculation times for machine learning with large data sets and density functional theory calculations are shortened during single core calculations. Thus, a transformer oil immersion cooling server is proposed to be an alternative cooling system used for improving the performance of first principle calculations and machine learning.
• Unveiling the reaction pathways of hydrocarbonsviaexperiments, computations and data science
  Lauren Takahashi; Shigehiro Yoshida; Jun Fujima; Hiroshi Oikawa; Keisuke Takahashi
  Physical Chemistry Chemical Physics, 24, 48, 29841, 29849, Royal Society of Chemistry (RSC), 2022
  Scientific journal, Reaction networks of hydrocarbons are explored using first principles calculations, data science, and experiments.
• Catalysis Gene Expression Profiling: Sequencing and Designing Catalysts
  Keisuke Takahashi; Jun Fujima; Itsuki Miyazato; Sunao Nakanowatari; Aya Fujiwara; Thanh Nhat Nguyen; Toshiaki Taniike; Lauren Takahashi
  The Journal of Physical Chemistry Letters, 12, 30, 7335, 7341, American Chemical Society ({ACS}), 05 Aug. 2021, [Peer-reviewed]
  Scientific journal
• Unveiling gas‐phase oxidative coupling of methane via data analysis
  Sora Ishioka; Itsuki Miyazato; Lauren Takahashi; Thanh Nhat Nguyen; Toshiaki Taniike; Keisuke Takahashi
  Journal of Computational Chemistry, 42, 20, 1447, 1451, Wiley, 30 Jul. 2021, [Peer-reviewed]
  Scientific journal
• Extraction of Catalyst Design Heuristics from Random Catalyst Dataset and their Utilization in Catalyst Development for Oxidative Coupling of Methane
  Sunao Nakanowatari; Thanh Nhat Nguyen; Hiroki Chikuma; Aya Fujiwara; Kalaivani Seenivasan; Ashutosh Thakur; Lauren Takahashi; Keisuke Takahashi; Toshiaki Taniike
  ChemCatChem, 13, 14, 3262, 3269, Wiley, 21 Jul. 2021
  English, Scientific journal
• Extraction of Catalyst Design Heuristics from Random Catalyst Dataset and their Utilization in Catalyst Development for Oxidative Coupling of Methane
  Sunao Nakanowatari; Thanh Nhat Nguyen; Hiroki Chikuma; Aya Fujiwara; Kalaivani Seenivasan; Ashutosh Thakur; Lauren Takahashi; Keisuke Takahashi; Toshiaki Taniike
  ChemCatChem, 13, 14, 3262, 3269, Wiley, 08 Jun. 2021
  AbstractIn the oxidative coupling of methane (OCM), the activation of methane and the suppression of deep oxidation are in a persistent trade‐off relationship, and a catalyst design strategy that balances the activity and the selectivity is desired. In this study, we analyzed a random catalyst dataset for OCM that was earlier obtained by high‐throughput experimentation, and extracted heuristics such as elements, supports, and their combinations related to methane activation at a low temperature and selective formation of C2 compounds at a high temperature. The obtained heuristics were used for catalyst development. The most effective was the use of a mixed support between La2O3 and BaO, which improved the low‐temperature activity, the high‐temperature selectivity, as well as the maximum C2 yield. It was considered that La2O3 acted as a heater and helped low‐temperature operation of BaO, which is highly selective but not active at a low temperature.
• Learning Catalyst Design Based on Bias-Free Data Set for Oxidative Coupling of Methane
  Thanh Nhat Nguyen; Sunao Nakanowatari; Thuy Phuong Nhat Tran; Ashutosh Thakur; Lauren Takahashi; Keisuke Takahashi; Toshiaki Taniike
  ACS Catalysis, 11, 3, 1797, 1809, American Chemical Society ({ACS}), 05 Feb. 2021, [Peer-reviewed]
  Scientific journal
• Representing Catalytic and Processing Space in Methane Oxidation Reaction via Multioutput Machine Learning
  Itsuki Miyazato; Thanh Nhat Nguyen; Lauren Takahashi; Toshiaki Taniike; Keisuke Takahashi
  The Journal of Physical Chemistry Letters, 12, 2, 808, 814, American Chemical Society ({ACS}), 21 Jan. 2021, [Peer-reviewed]
  Scientific journal
• Representing the Methane Oxidation Reaction via Linking First-Principles Calculations and Experiment with Graph Theory
  Lauren Takahashi; Junya Ohyama; Shun Nishimura; Keisuke Takahashi
  The Journal of Physical Chemistry Letters, 12, 1, 558, 568, American Chemical Society ({ACS}), 14 Jan. 2021, [Peer-reviewed]
  Scientific journal
• Constructing catalyst knowledge networks from catalyst big data in oxidative coupling of methane for designing catalysts
  Lauren Takahashi; Thanh Nhat Nguyen; Sunao Nakanowatari; Aya Fujiwara; Toshiaki Taniike; Keisuke Takahashi
  Chemical Science, 12, 38, 12546, 12555, Royal Society of Chemistry ({RSC}), 2021, [Peer-reviewed]
  Scientific journal
• Direct design of active catalysts for low temperature oxidative coupling of methane via machine learning and data mining
  Junya Ohyama; Takaaki Kinoshita; Eri Funada; Hiroshi Yoshida; Masato Machida; Shun Nishimura; Takeaki Uno; Jun Fujima; Itsuki Miyazato; Lauren Takahashi; Keisuke Takahashi
  Catalysis Science & Technology, Royal Society of Chemistry ({RSC}), 2021, [Peer-reviewed]
  Scientific journal,

  Direct design of low temperature oxidative coupling of methane catalysts is proposed via machine learning and data mining.

• Multidimensional Classification of Catalysts in Oxidative Coupling of Methane through Machine Learning and High-Throughput Data
  Keisuke Takahashi; Lauren Takahashi; Thanh Nhat Nguyen; Ashutosh Thakur; Toshiaki Taniike
  The Journal of Physical Chemistry Letters, 11, 16, 6819, 6826, American Chemical Society ({ACS}), 20 Aug. 2020, [Peer-reviewed]
  Scientific journal
• Data-Driven Identification of the Reaction Network in Oxidative Coupling of the Methane Reaction via Experimental Data
  Itsuki Miyazato; Shun Nishimura; Lauren Takahashi; Junya Ohyama; Keisuke Takahashi
  The Journal of Physical Chemistry Letters, 11, 3, 787, 795, American Chemical Society ({ACS}), 06 Feb. 2020, [Peer-reviewed]
  Scientific journal
• Catalyst Acquisition by Data Science (CADS): a web-based catalyst informatics platform for discovering catalysts
  Jun Fujima; Yuzuru Tanaka; Itsuki Miyazato; Lauren Takahashi; Keisuke Takahashi
  Reaction Chemistry & Engineering, Royal Society of Chemistry ({RSC}), 2020, [Peer-reviewed]
  English, Scientific journal,

  An innovative web-based integrated catalyst informatics platform, Catalyst Acquisition by Data Science (CADS), is developed for use towards the discovery and design of catalysts.

• Visualizing Scientists’ Cognitive Representation of Materials Data through the Application of Ontology
  Lauren Takahashi; Keisuke Takahashi
  The Journal of Physical Chemistry Letters, 10, 23, 7482, 7491, American Chemical Society ({ACS}), 05 Dec. 2019, [Peer-reviewed], [Invited]
  English, Scientific journal
• High-Throughput Experimentation and Catalyst Informatics for Oxidative Coupling of Methane
  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
  ACS Catalysis, 10, 2, 921, 932, Dec. 2019, [Peer-reviewed]
  English, Scientific journal
• Data Driven Determination in Growth of Silver from Clusters to Nanoparticles and Bulk
  Keisuke Takahashi; Lauren Takahashi
  The Journal of Physical Chemistry Letters, 10, 14, 4063, 4068, American Chemical Society ({ACS}), 18 Jul. 2019, [Peer-reviewed]
  Scientific journal
• The Rise of Catalyst Informatics: Towards Catalyst Genomics
  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
  ChemCatChem, 11, 4, 1146, 1152, Wiley, 20 Feb. 2019, [Peer-reviewed]
  Scientific journal
• Functionalized Single-Atom-Embedded Bilayer Graphene and Hexagonal Boron Nitride
  Keisuke Takahashi; Lauren Takahashi
  ACS Applied Electronic Materials, 1, 1, 2, 6, American Chemical Society ({ACS}), 22 Jan. 2019, [Peer-reviewed]
  Scientific journal
• Creating Machine Learning-Driven Material Recipes Based on Crystal Structure
  Keisuke Takahashi; Lauren Takahashi
  The Journal of Physical Chemistry Letters, 10, 2, 283, 288, American Chemical Society ({ACS}), 17 Jan. 2019, [Peer-reviewed]
  Scientific journal
• Automatic oxidation threshold recognition of XAFS data using supervised machine learning
  Itsuki Miyazato; Lauren Takahashi; Keisuke Takahashi
  Molecular Systems Design & Engineering, 4, 5, 1014, 1018, Royal Society of Chemistry (RSC), 2019
  Scientific journal,

  Oxidation states of materials are characterized by the X-ray absorption near edge structure (XANES) region in X-ray absorption spectroscopy (XAS).

• Redesigning the Materials and Catalysts Database Construction Process Using Ontologies
  Takahashi, L.; Miyazato, I.; Takahashi, K.
  Journal of Chemical Information and Modeling, 58, 9, 1742, 1754, American Chemical Society ({ACS}), Sep. 2018, [Peer-reviewed]
  Scientific journal
• Electronic structure of octagonal boron nitride nanotubes
  Lauren Takahashi; Tessui Nakagawa; Keisuke Takahashi
  International Journal of Quantum Chemistry, 118, 11, e25542, John Wiley and Sons Inc., 05 Jun. 2018, [Peer-reviewed]
  English, Scientific journal
• Searching for Hidden Perovskite Materials for Photovoltaic Systems by Combining Data Science and First Principle Calculations
  Keisuke Takahashi; Lauren Takahashi; Itsuki Miyazato; Yuzuru Tanaka
  ACS Photonics, 5, 3, 771, 775, American Chemical Society, 21 Mar. 2018, [Peer-reviewed]
  English, Scientific journal
• Tuning the Electronic Structure of an Aluminum Phosphide Nanotube through Configuration of the Lattice Geometry
  Lauren Takahashi; Keisuke Takahashi
  ACS Applied Nano Materials, 1, 2, 501, 504, American Chemical Society ({ACS}), 23 Feb. 2018, [Peer-reviewed]
  Scientific journal
• Descriptors for predicting the lattice constant of body centered cubic crystal
  Keisuke Takahashi; Lauren Takahashi; Jakub D. Baran; Yuzuru Tanaka
  JOURNAL OF CHEMICAL PHYSICS, 146, 20, 204104, 204104, May 2017, [Peer-reviewed]
  English, Scientific journal
• Structural stability and electronic properties of an octagonal allotrope of two dimensional boron nitride
  Lauren Takahashi; Keisuke Takahashi
  DALTON TRANSACTIONS, 46, 13, 4259, 4264, Apr. 2017, [Peer-reviewed]
  English, Scientific journal
• Designing Mg7 cluster-assembled two dimensional crystal
  Lauren Takahashi; Keisuke Takahashi
  FlatChem, 1, 57, 59, Elsevier B.V., 01 Jan. 2017, [Peer-reviewed]
  English, Scientific journal
• Reactivity of Two-Dimensional Au-9, Pt-9, and Au18Pt18 against Common Molecules
  Lauren Takahashi; Keisuke Takahashi
  INORGANIC CHEMISTRY, 55, 18, 9410, 9416, Sep. 2016, [Peer-reviewed]
  English, Scientific journal
• Designing Square Two-Dimensional Gold and Platinum
  Keisuke Takahashi; Tanveer Hussain; Lauren Takahashi; Jakub D. Baran
  CRYSTAL GROWTH & DESIGN, 16, 3, 1746, 1750, Mar. 2016, [Peer-reviewed]
  English, Scientific journal
• Prediction of the dopant activity of chemical compounds against ammonia borane with key descriptors: electronegativity and crystal structures
  Keisuke Takahashi; Yuki Nakagawa; Lauren Takahashi; Shigehito Isobe
  NEW JOURNAL OF CHEMISTRY, 40, 9, 7303, 7306, 2016, [Peer-reviewed]
  English, Scientific journal
• Hydrophobic and antioxidant effects in In, Sn, and Sb based two dimensional materials
  Keisuke Takahashi; Lauren Takahashi
  DALTON TRANSACTIONS, 45, 8, 3244, 3246, 2016, [Peer-reviewed]
  English, Scientific journal
• Low temperature pollutant trapping and dissociation over two-dimensional tin
  Lauren Takahashi; Keisuke Takahashi
  PHYSICAL CHEMISTRY CHEMICAL PHYSICS, 17, 33, 21394, 21396, 2015, [Peer-reviewed]
  English, Scientific journal
• Developing an Interactive Communicative Search Agent
  Lauren Takahashi
  University of Gothenburg, University of Gothenburg, 08 Sep. 2011, [Peer-reviewed], [International Magazine]
  English

• Spectroscopic Evaluation of Water Hydration Structures under Vibrational Strong Coupling State
  板谷昌輝; 岩佐敦己; 宮坂直寿; 高橋ローレン; 高橋ローレン; 高橋啓介; 福島知宏; 福島知宏; 村越敬, 分子科学討論会講演プログラム&要旨(Web), 19th, 2025
• Evaluation of the structure of water molecular ensembles under vibrational strong coupling using infrared spectroscopy
  岩佐敦己; 宮坂直寿; 高橋ローレン; 高橋ローレン; 高橋啓介; 福島知宏; 福島知宏; 板谷昌輝; 村越敬, 分子科学討論会講演プログラム&要旨(Web), 19th, 2025
• Development of Heterogeneous Solid Catalysts Linked with Synthesis and Measurement Data by Catalytic Informatics Moving Away from Machine Learning
  高橋ローレン, 豊田研究報告(Web), 78, 2025
• アイテムセットマイニングを用いたメタン酸化カップリング反応における低温活性を示す触媒組成の探索
  木下卓明; 大山順也; 芳田嘉志; 藤間淳; 宮里一旗; 高橋ローレン; 高橋啓介; 宇野毅明; 西村俊; 町田正人, 石油・石油化学討論会講演要旨, 50th (Web), 2020

• Materials Informatics and Catalysts Informatics: An Introduction
  Keisuke Takahashi; Lauren Takahashi
  Springer, 31 Mar. 2024, 981970216X, 306

• 物質化学（材料化学）, 2024年, 修士課程, 総合化学院

• 自律型流通系固体触媒評価ロボットの開発
  戦略的な研究開発の推進 戦略的創造研究推進事業 さきがけ
  2024 - 2027
  髙橋 ローレンニコール
  本提案では世界初の自律型ガス流通型不均一触媒評価ロボット装置の開発を実施する。3dプリンター部品、触媒評価装置(フローマイクロリアクターを採用)、ガスライン、電子基板、制御ソフト、データ科学手法、データベースなど全てを完全自作し、低価格かつ汎用性が高い装置を開発する。対象反応はCO2水素化によるメタン生成とし炭素資源循環型の技術開発を目的とする。本提案では国内の触媒開発のロボット化普及に貢献する。
  科学技術振興機構, 北海道大学
• Design of heterogeneous catalysis using synthesis and measurement data via non machine learning catalysts informatics
  2024 Toyota Riken Scholar
  Apr. 2024
  Lauren Takahashi
  Toyota Physical and Chemical Research Institute (Incorporated Foundation), Principal investigator