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RESEARCH PAPER · Accounts of Chemical Research · 2021

Predicting Reaction Yields via Supervised Learning

Andrzej M. Żurański, Jesus I. Martinez Alvarado, Benjamin J. Shields, Abigail G. Doyle

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Predicting Reaction Yields via Supervised LearningOriginalIntegration of data-intensive, machine learning and robotic experimental approaches for accelerated discovery of catalysts in renewable energy-related reactions283D Computer Vision Models Predict DFT-Level HOMO-LUMO Gap Energies from Force-Field-Optimized Geometries0Machine Learning Aids Classification and Discrimination of Noncanonical DNA Folding Motifs by an Arrayed Host:Guest Sensing System59Towards Data‐Driven Design of Asymmetric Hydrogenation of Olefins: Database and Hierarchical Learning78Towards Data‐Driven Design of Asymmetric Hydrogenation of Olefins: Database and Hierarchical Learning6Highly accurate prediction of reaction performance and enantioselectivity with a uniform machine learning protocol0Application of Machine Learning and Reaction Optimization for the Iterative Improvement of Enantioselectivity of Cinchona-Derived Phase Transfer Catalysts27Computational mechanistic study in organometallic catalysis: Why prediction is still a challenge35Using Data Science To Guide Aryl Bromide Substrate Scope Analysis in a Ni/Photoredox-Catalyzed Cross-Coupling with Acetals as Alcohol-Derived Radical Sources191Mechanistically Guided Workflow for Relating Complex Reactive Site Topologies to Catalyst Performance in C–H Functionalization Reactions40Generalizability and limitations of machine learning for yield prediction of oxidative coupling of methane6Quantum chemistry-augmented neural networks for reactivity prediction: Performance, generalizability, and explainability93Working at the interfaces of data science and synthetic electrochemistry21Machine Learning May Sometimes Simply Capture Literature Popularity Trends: A Case Study of Heterocyclic Suzuki–Miyaura Coupling189An Ensemble Structure and Physicochemical (SPOC) Descriptor for Machine‐Learning Prediction of Chemical Reaction and Molecular Properties35Machine Learning for Chemical Reactivity: The Importance of Failed Experiments217Maschinelles Lernen zur Vorhersage chemischer Reaktivität: Die Bedeutung “gescheiterter” Experimente8Ligand-Based Control of Nickel Catalysts: Switching Chemoselectivity from One-Electron to Two-Electron Pathways in Competing Reactions of 4-Halotetrahydropyrans7Autonomous high-throughput screening technology for accelerating drug molecule discovery and synthesis1Advancing Base Metal Catalysis through Data Science: Insight and Predictive Models for Ni-Catalyzed Borylation through Supervised Machine Learning24Computational Catalyst Design with Data–Driven Tools – General Approaches and Applications1Mechanistic Inference from Statistical Models at Different Data-Size Regimes37Study of Correlation between Intestinal Microbiota and Traditional Chinese Medicine Syndrome of Patients with Colon Cancer0Machine Learning Yield Prediction from NiCOlit, a Small-Size Literature Data Set of Nickel Catalyzed C–O Couplings87A Statistical Modeling Approach to Catalyst Generality Assessment in Enantioselective Synthesis3Intelligent control of nanoparticle synthesis on microfluidic chips with machine learning102When machine learning meets molecular synthesis56Roadmap to Pharmaceutically Relevant Reactivity Models Leveraging High-Throughput Experimentation17Selective functionalization of hindered meta-C–H bond of o-alkylaryl ketones promoted by automation and deep learning31SELFIES and the future of molecular string representations261Bridging Chemical Knowledge and Machine Learning for Performance Prediction of Organic Synthesis51Into the Unknown: How Computation Can Help Explore Uncharted Material Space65A decision support system for selecting the most suitable machine learning in healthcare using user parameters and requirements20Advancing molecular graphs with descriptors for the prediction of chemical reaction yields20Expediting Chemical Enhanced Oil Recovery Processes with Prediction of Chemical Reaction Yield Using Machine Learning0Machine learning for the yield prediction of CO2 cyclization reaction catalyzed by the ionic liquids21An Unsupervised Machine Learning Workflow for Assigning and Predicting Generality in Asymmetric Catalysis0ACCELERATING DRUG DISCOVERY BY HIGH-THROUGHPUT EXPERIMENTATION1Automated LC-MS analysis and data extraction for high-throughput chemistry22HTE and machine learning-assisted development of iridium( i )-catalyzed selective O–H bond insertion reactions toward carboxymethyl ketones23On the use of real-world datasets for reaction yield prediction141Prediction of product distribution using machine learning techniques1Regio- and stereospecific cis -hydrophenoxylation of ynamides with acidic phenols8The challenge of balancing model sensitivity and robustness in predicting yields: a benchmarking study of amide coupling reactions39Transferrable selectivity profiles enable prediction in synergistic catalyst space15Structural Evidence for Aromatic Heterocycle N–O Bond Activation via Oxidative Addition17AROPS: A Framework of Automated 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Learning that Proposes Reaction Conditions and Yields for Wittig-type Methylenation of Aldehydes with Bis(iodozincio)methane in a Flow-microreactor5Prediction and interpretation of photocatalytic NO removal on g-C3N4-based catalysts using machine learning29It Is Not All about the Ligands: Exploring the Hidden Potentials of tBu3P through Its Oxidative Addition Complex as the Precatalyst17A Data-Driven Workflow for Assigning and Predicting Generality in Asymmetric Catalysis71Reaction performance prediction with an extrapolative and interpretable graph model based on chemical knowledge73Bayesian-optimization-assisted discovery of stereoselective aluminum complexes for ring-opening polymerization of racemic lactide68Unsupervised Analysis of Optical Imaging Data for the Discovery of Reactivity Patterns in Metal Alloy18Machine Learning Prediction of High-Yield Cobalt- and Nickel-Catalyzed Borylations10Rapid planning and analysis of high-throughput experiment arrays for reaction 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activation barriers9Extracting structured data from organic synthesis procedures using a fine-tuned large language model45Photocatalytic NO x removal and recovery: progress, challenges and future perspectives69Probing machine learning models based on high throughput experimentation data for the discovery of asymmetric hydrogenation catalysts26Selective recognition between aromatics and aliphatics by cage-shaped borates supported by a machine learning approach0Universal machine learning aided synthesis approach of two-dimensional perovskites in a typical laboratory86Machine learning advancements in organic synthesis: A focused exploration of artificial intelligence applications in chemistry93Applications de l'organocatalyse asymétrique et de la photocatalyse aux additions nucléophiles sur des dérivés α,β-insaturés électroappauvris0Paving the road towards automated homogeneous catalyst design32Prediction of chemical reaction yields with large-scale multi-view pre-training30The Role of 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through Mobile Services in Bangladesh1Advancements and prospects of deep learning in biomaterials evolution22Top 20 influential AI-based technologies in chemistry50Intermediate Knowledge Enhanced the Performance of N-Acylation Yield Prediction Model06‐Hydroxy Picolinohydrazides Promoted Cu(I)‐Catalyzed Hydroxylation Reaction in Water: Machine‐Learning Accelerated Ligands Design and Reaction Optimization46‐Hydroxy Picolinohydrazides Promoted Cu(I)‐Catalyzed Hydroxylation Reaction in Water: Machine‐Learning Accelerated Ligands Design and Reaction Optimization24Dissociation role on the catalytic activity of organic halides in CO2 conversion to cyclic carbonates: Experimental and computational study17Machine learning-guided strategies for reaction conditions design and optimization49High-throughput experimentation and machine learning-promoted synthesis of α-phosphoryloxy ketones via Ru-catalyzed P(O)O-H insertion reactions of sulfoxonium ylides14Robustness in deep learning models for 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Leveraging Pd Knowledge for Ni Discovery43Integrating a multitask graph neural network with DFT calculations for site-selectivity prediction of arenes and mechanistic knowledge generation19Local reaction condition optimization via machine learning1Exploring BERT for Reaction Yield Prediction: Evaluating the Impact of Tokenization, Molecular Representation, and Pretraining Data Augmentation9AI Approaches to Homogeneous Catalysis with Transition Metal Complexes47Data-intelligent-driven exploration of robotic chemist systems1Developing Pharmaceutically Relevant Pd-Catalyzed C–N Coupling Reactivity Models Leveraging High-Throughput Experimentation23Interpretation of chemical reaction yields with graph neural additive network1Predicting Reactivity with Machine Learning1Machine Learning for Organic Fluorescent Materials26Data Driven Stereoselective Cationic Polymerization1Discovery of Ni(I) Complexes for CO2 Insertion Enabled by a Machine Learning-Computational-Selection Sequence12Machine learning guided catalytic ethyl lactate preparation from xylose3Eco-friendly extraction of Pistacia lentiscus bioactives: Supercritical CO2 technology and artificial neural networks predictions2A unified pre-trained deep learning framework for cross-task reaction performance prediction and synthesis planning14Synergy of Machine Learning and High‐Throughput Experimentation: A Road Toward Autonomous Synthesis8Artificial intelligence in chemical reaction engineering0Bulky yet Flexible Alkyl Substituents at Remote Positions in Tertiary Phosphines: Synthesis and Catalytic Performance of the Phosphine Ligands in the Nickel-Catalyzed Suzuki–Miyaura Reaction3Chemical mechanism prediction unravels multiple macromolecular outcomes from free-radical reactions0Efficient Machine Learning for Yield Prediction in Transition Metal-Catalyzed meta -C(sp 2 )–H Bond Activation and Other Reactions2Biomaterials education through artificial intelligence-enabled product-based learning1Understanding and 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