Machine-Learning Methods Enable Exhaustive Searches for Active Bimetallic Facets and Reveal Active Site Motifs for CO 2 Reduction
Ulissi, Zachary W., Tang, Michael T., Xiao, Jianping, Liu, Xinyan, Torelli, Daniel A., Karamad, Mohammadreza, Cummins, Kyle, Hahn, Christopher +4 more·2017·ACS Catalysis
Cited by (386)
Items 301–386 of 386
- Machine-learning prediction of facet-dependent CO coverage on Cu electrocatalystsShanglin Wu, Shisheng Zheng, Wentao Zhang, Mingzheng Zhang, Shunning Li, Feng Pan · 2025 · Journal of Materials Informatics
- Machine Learning for Catalytic Reaction Systems: A Framework for Complex Chemical ProcessesMehmet Erdem Günay, Ramazan Yıldırım · 2026 · ACS Engineering Au
- Machine learning-guided design of energy-related catalysts from nanoparticles to single-atom sitesZhongbao Hu, Zhoukun Wang, Yunyi Peng, Zhen Gao, Chanyuan Jin, Zechao C. Zhuang, Jian‐Feng Li · 2026 · Communications Chemistry
- Machine Learning Based Electronic Structure Predictors in Single-Atom Alloys: A Model Study of CO Kink-Site Adsorption across Transition Metal SubstratesJavad Shirani, Hanh D. M. Pham, Shuaishuai Yuan, Alain Tchagang, Julio J. Valdés, Kirk H. Bevan · 2023 · The Journal of Physical Chemistry C
- Unlocking the efficiency of nonaqueous Li–air batteries through the synergistic effect of dual metal site catalysts: an interpretable machine learning approachNishchal Bharadwaj, Surya Sekhar Manna, Milan Kumar Jena, Diptendu Roy, Biswarup Pathak · 2024 · Journal of Materials Chemistry A
- How Does the Ni–Ga Alloy Structure Tune Methanol Productivity and Selectivity?Nora K. Zimmerli, Andrés Felipe Usuga, Stefano Checchia, Aleix Comas‐Vives, Christoph Rüdiger Müller, Paula M. Abdala · 2025 · ACS Catalysis
- Bimetal-Anchored Single-Atom Catalysts for Superior Nitrogen Reduction: Synergistic DFT and Machine Learning DesignBo Xiong, Chao Yang, Junhui Luo, Zhipeng Zhao, Zhongpu Fang, Silin Kang, Lei Zhu · 2026 · Langmuir
- From density functional theory to machine learning: Emerging paradigms in energy materials discoveryMullapudi V. Jyothirmai, Shrish Nath Upadhyay, S Rama Gokula Krishnan, Sudipta Roy, Jayant Kumar Singh · 2026 · Journal of Power Sources
- Advances in Electrochemical CO 2 Reduction: A Review and Perspective on Structure–Performance RelationshipsJyotiraditya Sikder, Jithul KP, Jay Pandey · 2026 · Energy & Fuels
- Rational catalyst design for CO oxidation: a gradient-based optimization strategyZiyun Wang, P. Hu · 2021 · Catalysis Science & Technology
- Structures, Scaling Relations, and Selectivities of the Copper-Based Binary Catalysts for CO2 Reduction ReactionsYanyan Ding, Yangyang Xu, Lixin Zhang · 2022 · The Journal of Physical Chemistry C
- Combining experimental and theoretical insights for reduction of CO2 to multi-carbon compoundsIan Brewis, Rana Faisal Shahzad, Robert W. Field, Abdesslem Jedidi, Shahid Rasul · 2022 · Discover Chemical Engineering
- DFT‐based Machine Learning for Ensemble Effect of Pd@Au Electrocatalysts on CO2 Reduction ReactionFuzhu Liu, Peng‐Fei Gao, Chao Jun Wu, Shengchun Yang, Xiangdong Ding · 2023 · ChemPhysChem
- Learning What Makes Catalysts GoodNongnuch Artrith · 2020 · Matter
- Engineering regulated catalysts for electrocatalytically driven CO2 preparation of ethanolGuanling Yang, Jinsheng Liang, Fei Wang · 2024 · Applied Catalysis A General
- Monolayer Gas Adsorption on Graphene-Based Materials: Surface Density of Adsorption Sites and Adsorption CapacityOlga M. Jaksic, Marko Spasenović, Zoran Jakšić, Dana G. Vasiljević-Radović · 2020 · Surfaces
- Intrinsic Descriptors for Coordination Environment and Synergistic Effects of Metal and Environment in Single-Atom-Catalyzed Carbon Dioxide ElectroreductionHao Yuan, Zhenyu Li · 2021 · The Journal of Physical Chemistry C
- Examining generalizability of AI models for catalysisShih‐Han Wang, Hongliang Xin, Luke E. K. Achenie, Kamal Kumar Choudhary · 2025 · Journal of Catalysis
- Metal–organic frameworks for photocatalytic CO 2 conversion: bridging fundamental insights to practical solutionsVenkadeshkumar Ramar, P. Sivakumar, Prabhu Sengodan, Shihua Huang · 2025 · Journal of Materials Chemistry A
- Achieving Digital Catalysis: Strategies for Data Acquisition, Storage and UseClara Patricia Marshall, Julia Schumann, Annette Trunschke · 2023 · Angewandte Chemie
- Predictive Model for Catalytic Methane PyrolysisUlrich Pototschnig, Martin Matas, David Scheiblehner, David Neuschitzer, Robert Obenaus-Emler, Helmut Antrekowitsch, David Holec · 2024 · The Journal of Physical Chemistry C
- The Importance of Reaction Energy in Predicting Chemical Reaction Barriers with Machine Learning ModelsNithin Lalith, Aayush R. Singh, Joseph A. Gauthier · 2024 · ChemPhysChem
- Intelligent chemometric modelling of Al 2 O 3 supported mixed metal oxide catalysts for oxidative dehydrogenation of n -butane using simple featuresRidhwan Lawal, Hassan Saeed Alasiri, Abdullah Mohammed Aitani, Abdulazeez Abdulraheem, Gazali Tanimu · 2024 · Reaction Chemistry & Engineering
- Sampling rare events using nanostructures for universal Pt neural network potentialJoonhee Kang, Byung‐Hyun Kim, Min Ho Seo, Jehyun Lee · 2024 · Current Applied Physics
- Screening Multicomponent Alloys Using Evidence Theory and High-Throughput DFT Calculations for C2-Selective eCO2RRFumiaki Kuroda, Masaya Ibe, Minoru Otani · 2024 · The Journal of Physical Chemistry C
- Unsupervised Assisted Directional Design of Chemical ReactionsLin Zhang, Zhilong Wang, Zhiyun Wei, Jinjin Li · 2020 · Cell Reports Physical Science
- Data Science and AI for Sustainable Futures: Opportunities and ChallengesGavin Shaddick, David O. Topping, Tristram Charles Hales, Usama Kadri, Joanne Louise Patterson, John Anthony Pickett, Ioan Petri, Stuart H. Taylor, Peiyuan Li, Ashish S. Sharma et al. · 2025 · Sustainability
- Toward predicting surface energy of rutile TiO 2 with machine learningFuming Lai, Riyue Ge, Min Zhao, Zhiling Zhou, Yanqiang Hu, Jian Jun Yang, Shengfu Tong · 2022 · CrystEngComm
- CKineticsDB─An Extensible and FAIR Data Management Framework and Datahub for Multiscale Modeling in Heterogeneous CatalysisSiddhant M. Lambor, Sashank Kasiraju, Dionisios G. Vlachos · 2023 · Journal of Chemical Information and Modeling
- Solid-liquid phase transition temperature prediction of alloys based on machine learning key feature screeningJiheng Fang, Shangrong Yang, Ming Xie, Jieqiong Hu, Hongsheng Sun, Guohua Liu, Shangqiang Zhao, Yongtai Chen, Youcai Yang, dekui ning et al. · 2023 · Applied Materials Today
- Committee machine that votes for similarity between materialsDuong‐Nguyen Nguyen, Tien-Lam Pham, Viet-Cuong Nguyen, Tuan-Dung Ho, Truyen Tran, KEISUKE G. TAKAHASHI, Hieu‐Chi Dam · 2018 · IUCrJ
- The time response of plasmonic sensors due to binary adsorption: analytical versus numerical modelingOlga M. Jaksic, Ivana M. Jokic, Zoran Jakšić, Ivana O. Mladenović, Katarina Radulović, Milos P. Frantlovic · 2020 · Applied Physics A
- Advanced manufacturing in heterogeneous catalysisSwarom Kanitkar, Biswanath Dutta, Ashraf Abedin, Xue Bai, Daniel J. Haynes · 2024 · Royal Society of Chemistry eBooks
- Hybrid pathways for methane production: Merging thermodynamic insights with machine learningAzita Etminan, Peter J. Holliman, Peyman Karimi, Majid Majd, Ian Mabbett, Mary Larimi, Ciarán Martin, Anna R. L. Carter · 2025 · Journal of Cleaner Production
- Harnessing Artificial Intelligence (AI) for a greener future: a review of AI advancements in green chemistry, chemical processes and sustainable materialsAhmed M. Elkhatat, Shaheen A. Al‐Muhtaseb · 2026 · Applied Intelligence
- Design Strategy of Multi‐electron Transfer Catalysts Based on a Bioinformatic Analysis of Oxygen Evolution and Reduction EnzymesHideshi Ooka, Kazuhito Hashimoto, Ryuhei Nakamura · 2018 · Molecular Informatics
- Ab initio machine learning in chemical compound spaceBing Huang, O. Anatole von Lilienfeld · 2020 · arXiv (Cornell University)
- MatOpt: A Python Package for Nanomaterials Design Using Discrete OptimizationChristopher L. Hanselman, Xiangyu Yin, David C. Miller, Chrysanthos E. Gounaris · 2022 · Journal of Chemical Information and Modeling
- An overview of electrochemical carbon dioxide conversion strategySvetlana Posokhova, Nikita O. Akhmetov, Anton M. Manakhov, Vikrant B. Wagle · 2026 · Next Energy
- From Subnanometric Clusters toward Single-Atom CatalystsAfshan Mohajeri · 2020 · ACS symposium series
- Accelerating the Design of Automotive Catalyst Products Using Machine LearningThomas M. Whitehead, Flora Chen, Christopher Daly, G. J. Conduit · 2021 · Johnson Matthey Technology Review
- The effects of near-surface atomic order on the catalytic properties of Cu 3 Au and CuAu 3 intermetallics for the CO 2 reduction reactionLucas G. Verga, Yunzhe Wang, Tanmoy Chakraborty, Juarez L. F. Da Silva, Tim Mueller · 2023 · Catalysis Science & Technology
- Accessing the usefulness of atomic adsorption configurations in predicting the adsorption properties of molecules with machine learningWalter Malone, Johnathan von der Heyde, Abdelkader Kara · 2024 · Physical Chemistry Chemical Physics
- A Decade of Computational Surface CatalysisKarsten Reuter, Horia I. Metiu · 2020 · Springer eBooks
- Deposition and characterization of nickel gallium thin filmsShidong He, Andrew J. Pfau, J. Trey Diulus, Gustavo H. Albuquerque, Gregory S. Herman · 2018 · Journal of Vacuum Science & Technology A Vacuum Surfaces and Films
- A Decade of Computational Surface CatalysisKarsten Reuter, Horia I. Metiu · 2018 · Springer eBooks
- Two-dimensional forms of robust CO2 reduction photocatalystsSteven B. Torrisi, Arunima K. Singh, Joseph H. Montoya, Tathagata Biswas, Kristin Aslaug Persson · 2020 · npj 2D Materials and Applications
- An interpretable machine learning framework for prediction of adsorption energies and generative design of active sites on arbitrary catalystsMatthew S. Johnson, Richard H. West, Judit Zádor · 2026 · Faraday Discussions
- Invariant Molecular Representations for Heterogeneous CatalysisJawad Chowdhury, Charles H. Fricke, Olajide H. Bamidele, Mubarak Bello, Wenqiang Yang, Andreas Heyden, Gabriel Terejanu · 2024 · Journal of Chemical Information and Modeling
- Recent Advances in Electrode Materials for Electrochemical CO2ReductionXin Li, Justus Masa, Zhenyu Sun · 2020 · ACS symposium series
- Rational Design of Continuous Flow Processes for Synthesis of Functional MoleculesAlexei A. Lapkin · 2019 · Elsevier eBooks
- Neural network-based study of structural, chemical and electronic properties of doped $$\hbox {MoO}_{3}$$Mahesh Raj Neupane, Jenille Cruz, James D. Weil, Michael N. Groves · 2021 · Journal of materials research/Pratt's guide to venture capital sources
- Carbon dioxide molecular interactions with hydrogenated Ni(111) surface: a DFT studyAndrii V. Yatsymyrskyi, Alla G. Dyachenko, Elena V. Ischenko, Tetiana M. Zakharova, S. V. Gaidai, Vitaliy E. Diyuk, Vladyslav V. Lisnyak · 2022 · Molecular Crystals and Liquid Crystals
- Computational Modeling of Carbon Dioxide Catalytic ConversionJavier Amaya Suárez, Elena R. Remesal, José J. Plata, Antonio M. Márquez, Javier Fdez. Sanz · 2021
- Energy Maps of Complex Catalyst SurfacesAndrey Tarasov, Sabine Wrabetz, Jutta Kröhnert, Frank Rosowski, Robert Schlögl, Annette Trunschke · 2024 · ACS Catalysis
- Interplanar synergy of a copper-based electrocatalyst favors the reduction of CO 2 into C 2+ productsJiangnan Li, Xinyi Duan, Chao Jun Wu, Yucheng Cao, Zhiyao Duan, Wenjun Fan, Peng Zhang, Fuxiang Zhang · 2024 · EES Catalysis
- Machine Learning in Quantum Density Functional TheoryThorsten Deilmann · 2026 · Machine intelligence for materials science
- Catalytic tango in diatomic catalysts: from precision-guided pair construction to machine-learning-driven identification and designBowen Jiang, Jishui Huang, Kuibo Yin, Litao Sun · 2026 · Nanoscale
- Prediction of hydrogen adsorption energy of CeO2-based oxides by machine learningJie Wei, Meng-da LIU, Hong-Da Guo, Xin-Zheng Zhang, Yue Chang, Ziming Wang, Xingwen Feng, Jiang-Feng Song, Xiao-Hui Wang, Jiangli Cao · 2026 · International Journal of Hydrogen Energy
- Generative Discovery of Alloy Catalysts for Radical-Mediated Methane-to-Methanol ConversionChengyi Zhang, Qiang Song, Wanping Xu, Yuguang Li, Patrick Joseph Cullen, Ziyun Wang · 2026 · Journal of the American Chemical Society
- Machine Learned Force Fields: Fundamentals, Their Reach, and ChallengesCarlos A. Vital-José, Román J. Armenta‐Rico, Huziel E. Sauceda · 2025
- Accelerated Discovery of New Materials for Oxygen Evolution ReactionYimeng Min · 2019 · TSpace (University of Toronto)
- Coadsorption and Reaction of CO2, CO, and H2 on Ni-Fe(111) SurfaceAndrii V. Yatsymyrskyi, Olena V. Ischenko, S. V. Gaidai, Alla G. Dyachenko, Tetiana M. Zakharova, Vladyslav V. Lisnyak · 2020 · IEEE International Conference on Electronics and Nanotechnology (ELNANO)
- Digging Deeper into the Methods of Computational ChemistryJoshua A. Kammeraad · 2020 · Deep Blue (University of Michigan)
- Investigating the Nature of the Active Sites for the CO 2 Reduction Reaction on Carbon-Based ElectrocatalystsTristan Asset, Samuel T. Garcia, Sergio Herrera, Nalin I. Andersen, Yechuan Chen, Eric J. Peterson, Ivana Matanović, Kateryna Artyushkova, Jack K. Lee, Shelley D. Minteer et al. · 2019 · SSRN Electronic Journal
- OutlookDaniel V. Esposito, Heinz Frei · 2022 · Royal Society of Chemistry eBooks
- High-throughput thiophene adsorption calculations on bimetallic surfacesSoleil Chapman, Innis Michael, Walter Malone · 2024 · Chemical Data Collections
- Tentative exploration of artificial intelligence in developing and optimizing fuel cell catalystsHua Qiuru, Yiming Gu, Xianbin Guo, Chu Wu, Gang Li, Yihuang Zhang, Shudong Wang · 2024 · Scientia Sinica Chimica
- Machine Learning Approaches for Tackling Atomic-Scale Surface-Driven Complexities in Heterogeneous CatalysisSnehitha Srirangam, Swastik Paul, Siddharth Deshpande · 2025 · Journal of the Indian Institute of Science
- Modeling of chemical reactions and reactors using ANNsMohsen Shayanmehr, Ahad Ghaemi · 2025 · Elsevier eBooks
- Machine learning and catalyst engineering for sustainable hydrogen release from ammoniaUmer Aizaz, Mohd Asad Ansari, Zuhair Omar Malaibari, Ijaz Hussain · 2026 · Journal of the Energy Institute
- Machine Learning‐Assisted Discovery of Unconventional Molybdenum Nitride Nano‐Facets as Hydrogen Evolution ElectrocatalystsXutao Gao, Chun Kit Chan, Eric Pok Man Kan, Edmund C. M. Tse · 2026 · Small Methods
- The Emergence of Catalysis-ai: A New Frontier in Catalysis Research?Samuel Villanueva, Lisbeth Mendoza, Paulino Betancourt, Susana Pinto-Castilla · 2026 · Research Square
- Deep learning-driven anomaly detection and feature discovery in Ce-rich (Ni–Fe–Co–Ce)O x catalysts for oxygen evolution reactionChih‐Yang Cheng, Yi‐Huan Wu, Feng-Yin Li · 2026 · RSC Advances
- Advances in machine learning-assisted screening of electrocatalysts for CO2 reductionSuihan Gao, Linming Bai, Yadi Hu, Li Wang (15202), Qian Zhang, Wei Yan · 2026 · Chinese Chemical Letters
- Machine learning applications in microfluidic thermochemical reactorsAhmed Yusuf, Bilkis Mojisola Ajiwokewu, Adewale Giwa · 2026 · Elsevier eBooks
- Study of Cu alloy catalysts for hydrogen oxidation by machine learningYupeng Li, H J Guo, Meng-da LIU, Yue Chang, Ziming Wang, X Y Feng, Jiang-Feng Song, Jiangli Cao · 2026 · Journal of Alloys and Compounds
- Active Learning for Optimizing Adsorption Energy Predictions in Large Chemical SpacesJohnathan von der Heyde, Walter Malone, Abdelkader Kara · 2026 · The Journal of Physical Chemistry A
- Machine Learning-Accelerated Advancements in Electrocatalytic CO2 ReductionHao Wang, Junfeng Li, Yuquan Li, Zeqiu Chen, Xiaoyang Xuan, Hongxin Qi, Likun Pan · 2026 · Environmental Science & Technology
- The emergence of the catalysis artificial intelligence paradigm transforms modern chemical and catalytic researchSamuel Villanueva, Lisbeth Mendoza, Paulino Betancourt, Susana Pinto-Castilla · 2026 · Discover Chemistry.
- Reliability assessment of machine learning models for single-atom alloy catalyst screening: A chemistry-aware validation framework for methane C–H activation barrier predictionMd. Atik Faisal, Md. Amanullah Asif, Md. Shamim Al Razi, Mahbir Ahmed Maheen, Ahmed Sharif · 2026 · Computational Materials Today
- Kinetic Isotope Effects in CO 2 Reduction: Insights Into Reaction MechanismsXuemei Diao, Yiyang Li, Xiaowei Zhang, Xiubing Huang, PENG WANG · 2026 · Advanced Energy Materials
- AdsorbFlow: Energy-conditioned deterministic transport for catalyst screening in artificial intelligence-driven materials-reaction-process designJiangjie Qiu, Wentao Li, Honghao Chen, Leyi Zhao, Xiaonan Wang · 2026 · Chinese Journal of Chemical Engineering
- Theoretical insights into intermetallic compound surfaces in hydrogen-involving catalytic reactionsArshak A. Tsaturyan, Florian Brix, Dmytro Kandaskalov, Émilie Gaudry · 2026 · Surface Science Reports
- Reaction-anchored generative informatics for million-scale CO2 catalyst screening via multi-adsorbate constraintsDongjin Tang, Ruili Li, Zhidi Lei, Qingqing Mao, Ritankar Das, Beien Zhu, Yi Gao, Rui Qi · 2026 · Journal of Materials Informatics
- Physics-Guided Design of Ammonia Decomposition Catalysts with Interpretable Machine LearningPragyansh Singh, Jiaqi Yang, Fanglin Che · 2026 · Research Square