Papers citing The Rise of Catalyst Informatics: Towards Catalyst Genomics
Mass-based biocatalyst metrics to guide protein engineering and bioprocess development
Nature Catalysis · 2022-01-28
Murray P. Meissner, John M. Woodley
Read original paper ↗ ·Kinetic Modeling of Ethene Oligomerization on Bifunctional Nickel and Acid β Zeolites
Industrial & Engineering Chemistry Research · 2022-03-14
Elsa Koninckx, Rajamani Gounder, Joris W. Thybaut, Linda J. Broadbelt
Read original paper ↗ ·Machine Learning-Aided Catalyst Modification in Oxidative Coupling of Methane via Manganese Promoter
Industrial & Engineering Chemistry Research · 2022-04-08
Shun Nishimura, Junya Ohyama, Xinyue Li, Itsuki Miyazato, Toshiaki Taniike, KEISUKE G. TAKAHASHI
Read original paper ↗ ·Multi-output machine learning models for kinetic data evaluation : A Fischer–Tropsch synthesis case study
Chemical Engineering Journal · 2022-05-28
Anoop Chakkingal, Pieter Janssens, Jeroen Poissonnier, Mirella Virginie, Andreï Y. Khodakov, Joris W. Thybaut
Read original paper ↗ ·Data in Materials and Catalysts Informatics
ACS symposium series · 2022-06-14
KEISUKE G. TAKAHASHI, Lauren Takahashi
Read original paper ↗ ·Current Outlooks on Machine Learning Methods for the Development of Industrial Homogeneous Catalytic Systems
Current Organocatalysis · 2022-08-01
José Ferraz-Caetano
Read original paper ↗ ·Synthesis of Heterogeneous Catalysts in Catalyst Informatics to Bridge Experiment and High-Throughput Calculation
Journal of the American Chemical Society · 2022-08-19
KEISUKE G. TAKAHASHI, Lauren Takahashi, Son Dinh Le, Takaaki Kinoshita, Shun Nishimura, Junya Ohyama
Read original paper ↗ ·Designing Catalyst Descriptors for Machine Learning in Oxidative Coupling of Methane
ACS Catalysis · 2022-09-08
Sora Ishioka, Aya Fujiwara, Sunao Nakanowatari, Lauren Takahashi, Toshiaki Taniike, KEISUKE G. TAKAHASHI
Read original paper ↗ ·Graph-Driven Reaction Discovery: Progress, Challenges, and Future Opportunities
The Journal of Physical Chemistry A · 2022-10-03
Idil Ismail, Raphael Chantreau Majerus, Scott Habershon
Read original paper ↗ ·Developing Catalysts via Structure‐Property Relations Discovered by Machine Learning: An Industrial Perspective
Chemie Ingenieur Technik · 2022-10-11
Hrishikesh Joshi, Nicole Wilde, Thomas S. Asche, Dorit Wolf
Read original paper ↗ ·A deep neural network for oxidative coupling of methane trained on high-throughput experimental data
Journal of Physics Energy · 2022-11-30
Klea Ziu, Rubén Solozabal, Srinivas Rangarajan, Martin Takáč
Read original paper ↗ ·Exploring the Optimal Alloy for Nitrogen Activation by Combining Bayesian Optimization with Density Functional Theory Calculations
ACS Omega · 2022-11-30
Kazuki Okazawa, Yuta Tsuji, Keita Kurino, Masataka Yoshida, Yoshifumi Amamoto, Kazunari Yoshizawa
Read original paper ↗ ·Catalysts informatics: paradigm shift towards data-driven catalyst design
Chemical Communications · 2023-01-01
KEISUKE G. TAKAHASHI, Junya Ohyama, Shun Nishimura, Jun Fujima, Lauren Takahashi, Takeaki Uno, Toshiaki Taniike
Read original paper ↗ ·Improving scientific image processing accessibility through development of graphical user interfaces for scikit-image
Digital Discovery · 2023-01-01
Micke Kuwahara, Jun Fujima, KEISUKE G. TAKAHASHI, Lauren Takahashi
Read original paper ↗ ·Leveraging machine learning engineering to uncover insights into heterogeneous catalyst design for oxidative coupling of methane
Catalysis Science & Technology · 2023-01-01
Shun Nishimura, Xinyue Li, Junya Ohyama, KEISUKE G. TAKAHASHI
Read original paper ↗ ·Data-Centric Heterogeneous Catalysis: Identifying Rules and Materials Genes of Alkane Selective Oxidation
Journal of the American Chemical Society · 2023-02-06
Lucas Foppa, Frederik Rüther, Michael Geske, Gregor Koch, Frank Girgsdies, Pierre Kube, Spencer J. Carey, Michael Hävecker, Olaf Timpe, Andrey Tarasov, Matthias Scheffler, Frank Rosowski, Robert Schlögl, Annette Trunschke
Read original paper ↗ ·The Open Catalyst 2022 (OC22) Dataset and Challenges for Oxide Electrocatalysts
ACS Catalysis · 2023-02-16
Richard Tran, Janice Lan, Muhammed Shuaibi, Brandon M. Wood, Siddharth Goyal, Abhishek Das, Javier Heras‐Domingo, Adeesh Kolluru, Ammar Rizvi, Nima Shoghi, Anuroop Sriram, Félix Therrien, Jehad Abed, Oleksandr Voznyy, Edward Hartley Sargent, Zachary W. Ulissi, C. Lawrence Zitnick
Read original paper ↗ ·Can AI Help Improve Water Quality? Towards the Prediction of Degradation of Micropollutants in Wastewater.
CHIMIA International Journal for Chemistry · 2023-02-22
Hiroko Satoh, Jasmin Hafner, Jürg Hutter, Kathrin Fenner
Read original paper ↗ ·Developing Machine Learning Models for Catalysts in Oxidative Dehydrogenation of n‐butane
ChemCatChem · 2023-07-01
Gazali Tanimu, Jimoh Olawale Ajadi, Yussif Yahaya, Hassan Saeed Alasiri, Nurudeen Adedayo Adegoke
Read original paper ↗ ·Exploring Metal Nanocluster Catalysts for Ammonia Synthesis Using Informatics Methods: A Concerted Effort of Bayesian Optimization, Swarm Intelligence, and First-Principles Computation
ACS Omega · 2023-08-07
Yuta Tsuji, Yuta Yoshioka, Kazuki Okazawa, Kazunari Yoshizawa
Read original paper ↗ ·Accelerated discovery of multi-elemental reverse water-gas shift catalysts using extrapolative machine learning approach
Nature Communications · 2023-09-21
Gang Wang, Shinya Mine, Duotian Chen, Yuan Jing, Kah Wei Ting, Taichi Yamaguchi, Motoshi Takao, Zen Maeno, Ichigaku Takigawa, Koichi Matsushita, Ken‐ichi Shimizu, Takashi Toyao
Read original paper ↗ ·Materials Genes of CO2 Hydrogenation on Supported Cobalt Catalysts: an AI Approach Integrating Theoretical and Experimental Data
ChemRxiv · 2023-11-16
Ray Miyazaki, Kendra Solveig Belthle, Harun Tüysüz, Lucas Foppa, Matthias Scheffler
Read original paper ↗ ·Application of Machine Learning to Fischer–Tropsch Synthesis for Cobalt Catalysts
Industrial & Engineering Chemistry Research · 2023-11-20
Kirill Motaev, Мaxim S. Моlokeev, Bulat Sultanov, V. B. Kharitontsev, Alexey V. Matigorov, Mikhail Palianov, Nikita O. Azarapin, Andrey Vladimirovich Elyshev
Read original paper ↗ ·Advancing catalysis research through FAIR data principles implemented in a local data infrastructure – a case study of an automated test reactor
Catalysis Science & Technology · 2024-01-01
Abdulrhman Moshantaf, Michael Wesemann, Simeon D. Beinlich, Heinz Junkes, Julia Schumann, Barış Alkan, Pierre Kube, Clara Patricia Marshall, Nils Pfister, Annette Trunschke
Read original paper ↗ ·Unveiling the relation between multiple chemical products and process conditions for trichloroethylene and perchloroethylene production via catalysis network analysis
Catalysis Science & Technology · 2024-01-01
Lauren Takahashi, Taku Yamada, Hidekazu Okamoto, KEISUKE G. TAKAHASHI
Read original paper ↗ ·Parametric analysis of CO2 hydrogenation via Fischer-Tropsch synthesis: A review based on machine learning for quantitative assessment
International Journal of Hydrogen Energy · 2024-02-13
Jing Hu, Yixao Wang, Xiyue Zhang, Yunshan Wang, Gang Yang, Lufang Shi, Yong Sun
Read original paper ↗ ·Application of machine learning‐based read‐across structure‐property relationship (RASPR) as a new tool for predictive modelling: Prediction of power conversion efficiency (PCE) for selected classes of organic dyes in dye‐sensitized solar cells (DSSCs)
Molecular Informatics · 2024-02-19
Souvik Pore, Arkaprava Banerjee, Kunal Roy
Read original paper ↗ ·Materials Genes of CO2 Hydrogenation on Supported Cobalt Catalysts: An Artificial Intelligence Approach Integrating Theoretical and Experimental Data
Journal of the American Chemical Society · 2024-02-20
Ray Miyazaki, Kendra Solveig Belthle, Harun Tüysüz, Lucas Foppa, Matthias Scheffler
Read original paper ↗ ·Recent advances in catalyst design, performance, and challenges of metal-heteroatom-co-doped biochar as peroxymonosulfate activator for environmental remediation
Environmental Research · 2024-04-15
Ganapaty Manickavasagam, Chao Hui He, Kun‐Yi Andrew Lin, Mardiana Saaid, Wen‐Da Oh
Read original paper ↗ ·Toward accelerated discovery of solid catalysts using extrapolative machine learning approach
Chemistry Letters · 2024-07-31
Takashi Toyao
Read original paper ↗ ·Catalysis in the digital age: Unlocking the power of data with machine learning
Wiley Interdisciplinary Reviews Computational Molecular Science · 2024-09-01
Bokinala Moses Abraham, Mullapudi V. Jyothirmai, Priyanka Sinha, Francesc Viñes, Jayant Kumar Singh, Francesc Illas
Read original paper ↗ ·CO Oxidation Catalyzed by Perovskites: The Role of Crystallographic Distortions Highlighted by Systematic Experiments and Artificial Intelligence
Angewandte Chemie · 2024-10-21
Giulia Bellini, Gregor Koch, Frank Girgsdies, Jinhu Dong, Spencer J. Carey, Olaf Timpe, Gudrun Auffermann, Matthias Scheffler, Robert Schlögl, Lucas Foppa, Annette Trunschke
Read original paper ↗ ·CO Oxidation Catalyzed by Perovskites: The Role of Crystallographic Distortions Highlighted by Systematic Experiments and Artificial Intelligence
Angewandte Chemie International Edition · 2024-10-21
Giulia Bellini, Gregor Koch, Frank Girgsdies, Jinhu Dong, Spencer J. Carey, Olaf Timpe, Gudrun Auffermann, Matthias Scheffler, Robert Schlögl, Lucas Foppa, Annette Trunschke
Read original paper ↗ ·Web-based graphical user interface for automated materials feature engineering for machine learning
Science and Technology of Advanced Materials Methods · 2024-12-16
Yoshiki Hasukawa, Micke Kuwahara, Fernando Garcia‐Escobar, Lauren Takahashi, Toshiaki Taniike, KEISUKE G. TAKAHASHI
Read original paper ↗ ·Multidimensional Catalysis Data Representation for Designing Oxidative Coupling of Methane Catalysts
The Journal of Physical Chemistry C · 2024-12-19
Yoshiki Hasukawa, Fernando Garcia‐Escobar, KEISUKE G. TAKAHASHI, Lauren Takahashi
Read original paper ↗ ·Ensemble Model Approach for Predicting the Yield of Dehydrogenation Products during the Oxidative Dehydrogenation of n-Butane
ACS Omega · 2024-12-26
Gazali Tanimu, Nurudeen Adedayo Adegoke, Jimoh Olawale Ajadi, Yussif Yahaya, Hassan Saeed Alasiri
Read original paper ↗ ·AI and automation: democratizing automation and the evolution towards true AI-autonomous robotics
Chemical Science · 2025-01-01
Lauren Takahashi, Micke Kuwahara, KEISUKE G. TAKAHASHI
Read original paper ↗ ·Digitalisation of catalytic processes for sustainable production of biobased chemicals and exploration of wider chemical space
Catalysis Science & Technology · 2025-01-01
Firdaus Parveen, Anna Grace Slater
Read original paper ↗ ·NHC-Cracker: A Platform for the In Silico Engineering of N-Heterocyclic Carbenes for Diverse Chemical Applications
ACS Catalysis · 2025-03-27
Gentoku Takasao, Bholanath Maity, Sayan Dutta, Rajesh Kancherla, Magnus Rueping, Luigi Cavallo
Read original paper ↗ ·15 Years of Progress on Transition Metal-Based Electrocatalysts for Microbial Electrochemical Hydrogen Production: From Nanoscale Design to Macroscale Application
Nano-Micro Letters · 2025-06-18
Seyed Masoud Parsa, Zhijie Chen, Huu Hao Ngo, Wei Wei, Xinbo Zhang, Ying Liu, Bing‐Jie Ni, Wenshan Guo
Read original paper ↗ ·Development of Highly Active Catalysts for Low-Temperature CO 2 Hydrogenation to Methanol Using a Machine Learning Approach
Journal of the American Chemical Society · 2025-08-12
Shirun Zhao, Shinya Mine, Gang Wang, Weiyang Zhang, Abdellah Ait El Fakir, Bin Yang, Zengwei Qin, Nazmul Hasan MD Dostagir, Koichi Matsushita, Ichigaku Takigawa, Ken‐ichi Shimizu, Takashi Toyao
Read original paper ↗ ·Statistical and Predictive Analysis of Supported Catalytically Active Metal Solutions (SCALMS) in Propane Dehydrogenation
ChemCatChem · 2025-08-27
Angelika Owsienko, Philipp Stangl, Nnamdi Madubuko, Richard Lenz, Marco Haumann
Read original paper ↗ ·Machine learning (ML)-assisted development of 2D green catalysts to support sustainability
Materials Horizons · 2025-10-15
Manshu Dhillon, Soumya Mahapatra, Adreeja Basu, Adreeja Basu, Shyam Sudhir Pandey, Manpreet Singh Manna, Shantanu Bhattacharya, Basab Chakraborty, Ajeet Kumar Kaushik, Aviru Kumar Basu, Aviru Kumar Basu
Read original paper ↗ ·Multiscale modelling in ammonia synthesis: Integrating CFD and process simulation - A review
Case Studies in Chemical and Environmental Engineering · 2025-10-25
Leonardo Bravo, Camilo Rengifo Gutierrez, Martha I. Cobo, Manuel Alfredo Figueredo
Read original paper ↗ ·Compatibility Diagnosis for the Design of Oxidative Coupling of Methane Catalysts
The Journal of Physical Chemistry Letters · 2025-11-15
Kei Kobayashi, Fernando Garcia‐Escobar, Yoshiki Hasukawa, Rensuke Koiwai, Lauren Takahashi, KEISUKE G. TAKAHASHI
Read original paper ↗ ·Dynamic catalysts and the digital age: Synthetic consequences
The Journal of Chemical Physics · 2025-11-21
Robert Schlögl
Read original paper ↗ ·Extrapolative-Machine-Learning-Guided Discovery of Multielemental Heterogeneous Catalysts for Low-Temperature NO Reduction by H 2
ACS Catalysis · 2025-12-04
Yuan Jing, Chenyang Zhang, Shinya Mine, Xiupeng Zhang, Chenxi He, Ningqiang Zhang, Xu Ming Guo, Akihiko Anzai, Kohei Oka, Ryo Toyoshima, Hiroshi Kondoh, Ichigaku Takigawa, Ken‐ichi Shimizu, Takashi Toyao
Read original paper ↗ ·Web-based graphical interface for catalyst gene design and profiling
Science and Technology of Advanced Materials Methods · 2025-12-11
Kazuhiko Shibata, Micke Kuwahara, Yoshiki Hasukawa, Fernando Garcia‐Escobar, Lauren Takahashi, KEISUKE G. TAKAHASHI
Read original paper ↗ ·Accelerating Multi-Elemental Catalyst Discovery with Interpretable Machine Learning and Automated Experimentation
ACS Nano · 2026-04-10
F. T. Liu, Zhilong Chen, Han Hu, C. C. Li, Lisong Zhang, Zeming Liu, Guangxu Chen
Read original paper ↗ ·Machine-Learning-Guided Discovery of CH 4 Combustion Catalysts Operating in the Presence of SO 2
Journal of the American Chemical Society · 2026-04-10
Yuan Jing, Kah Wei Ting, Junxian Qin, Katsuya Yamada, Daichi Tajima, Akihiko Anzai, Shinya Mine, Ryo Toyoshima, Hiroshi Kondoh, Ichigaku Takigawa, Ken‐ichi Shimizu, Takashi Toyao
Read original paper ↗ ·