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RESEARCH PAPER · ACS Central Science · 2017

Optimizing Chemical Reactions with Deep Reinforcement Learning

Zhenpeng Zhou, Xiaocheng Li, Richard N. Zare

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Optimizing Chemical Reactions with Deep Reinforcement LearningOriginalChimera: enabling hierarchy based multi-objective optimization for self-driving laboratories160Machine learning for predicting product distributions in catalytic regioselective reactions41Towards a continuous formic acid synthesis: a two-step carbon dioxide hydrogenation in flow28Towards operando computational modeling in heterogeneous catalysis250Tuning the molecular weight distribution from atom transfer radical polymerization using deep reinforcement learning68Accelerating the discovery of materials for clean energy in the era of smart automation776Machine Learning for Organic Synthesis: Are Robots Replacing Chemists?74Maschinelles Lernen für die organische Synthese: Ersetzen Roboter Chemiker?8Combining theory and experiment in lithium–sulfur batteries: Current progress and future perspectives446Deeply learning molecular structure-property relationships using attention- and gate-augmented graph convolutional network73Deeply learning molecular structure-property relationships using graph attention neural network.8Globally Optimal Catalytic Fields – Inverse Design of Abstract Embeddings for Maximum Reaction Rate Acceleration33ChemOS: Orchestrating autonomous experimentation180Inverse molecular design using machine learning: Generative models for matter engineering2050ACS Central Science Virtual Issue on Machine Learning19Sparsity Facilitates Chemical-Reaction Selection for Engine Simulations1Phoenics: A Bayesian Optimizer for Chemistry373Error-Controlled Exploration of Chemical Reaction Networks with Gaussian Processes81Deep reinforcement learning for the control of microbial co-cultures in bioreactors2AIR-Chem: Authentic Intelligent Robotics for Chemistry53Prediction of Major Regio‐, Site‐, and Diastereoisomers in Diels–Alder Reactions by Using Machine‐Learning: The Importance of Physically Meaningful Descriptors146Prediction of Major Regio‐, Site‐, and Diastereoisomers in Diels–Alder Reactions by Using Machine‐Learning: The Importance of Physically Meaningful Descriptors22Uncertainty quantification of molecular property prediction using Bayesian neural network models2High Throughput Strategies for the Discovery and Optimization of Catalytic Reactions165Hochdurchsatzstrategien zur Entdeckung und Optimierung katalytischer Reaktionen19Using Reinforcement Learning to find Efficient Qubit Routing Policies for Deployment in Near-term Quantum Computers12A Bayesian graph convolutional network for reliable prediction of molecular properties with uncertainty quantification147A microdroplet-accelerated Biginelli reaction: mechanisms and separation of isomers using IMS-MS94Automated platforms for reaction self-optimization in flow140Decentralized manufacturing for biomimetics through cooperation of digitization and nanomaterial design1Machine Learning for Understanding Compatibility of Organic–Inorganic Hybrid Perovskites with Post-Treatment Amines112Enhancing Retrosynthetic Reaction Prediction with Deep Learning Using Multiscale Reaction Classification106How to explore chemical space using algorithms and automation245Prediction of higher-selectivity catalysts by computer-driven workflow and machine learning678Capturing chemical intuition in synthesis of metal-organic frameworks254Nanomaterials Discovery and Design through Machine Learning113Next-Generation Experimentation with Self-Driving Laboratories421From Complexity to Simplicity: Adaptive ES-Active Subspaces for Blackbox Optimization5Miniaturized and Automated Synthesis of Biomolecules—Overview and Perspectives28A reinforcement learning unit matching recurrent neural network for the state trend prediction of rolling bearings29Virtual Reaction Condition Optimization based on Machine Learning for a Small Number of Experiments in High-dimensional Continuous and Discrete Variables10Experiment Specification, Capture and Laboratory Automation Technology (ESCALATE): a software pipeline for automated chemical experimentation and data management73Deep Learning in Chemistry561Efficient Navigation of Active Particles in an Unseen Environment via Deep Reinforcement Learning.0Statistical Analysis and Discovery of Heterogeneous Catalysts Based on Machine Learning from Diverse Published Data90Advancing Drug Discovery via Artificial Intelligence649Deep learning in drug discovery: opportunities, challenges and future prospects350Synthetic organic chemistry driven by artificial intelligence303Machine learning in materials science1058A deep neural network combined with molecular fingerprints (DNN-MF) to develop predictive models for hydroxyl radical rate constants of water contaminants107Concurrent Optimization of Organic Donor–Acceptor Pairs through Machine Learning78Autonome Entdeckung in den chemischen Wissenschaften, Teil I: Fortschritt12Autonomous Discovery in the Chemical Sciences Part I: Progress317Efficient Navigation of Colloidal Robots in an Unknown Environment via Deep Reinforcement Learning82I'm sorry Dave, I'm afraid I can't do that, Deep Q-learning from forbidden action7A reinforcement learning decision model for online process parameters optimization from offline data in injection molding76Machine Learning for Tailoring Optoelectronic Properties of Single-Walled Carbon Nanotube Films92Machine Learning for Accelerated Discovery of Solar Photocatalysts179Reinforcement Learning-Driven Test Generation for Android GUI Applications using Formal Specifications12A Deep Reinforcement Learning Architecture for Multi-stage Optimal Control2Deep Learning for Deep Chemistry: Optimizing the Prediction of Chemical Patterns181Deep reinforcement learning in World-Earth system models to discover sustainable management strategies25Exploration of flow reaction conditions using machine-learning for enantioselective organocatalyzed Rauhut–Currier and [3+2] annulation sequence65Quantitative Structure–Selectivity Relationships in Enantioselective Catalysis: Past, Present, and Future211Correction: Exploration of flow reaction conditions using machine-learning for enantioselective organocatalyzed Rauhut–Currier and [3+2] annulation sequence13Estimating Optimum Process Parameters in Textile Draping of Variable Part Geometries - A Reinforcement Learning Approach38Interpretable machine learning as a tool for scientific discovery in chemistry62Meta-Learning for Black-Box Optimization9NEURAL NETWORK AGENT PLAYING SPIN HAMILTONIAN GAMES ON A QUANTUM COMPUTER6Non-precious-metal catalysts for alkaline water electrolysis: operando characterizations, theoretical calculations, and recent advances884Optimisation of flow chemistry : tools and algorithms0Optimizing chemical reaction conditions using deep learning: a case study for the Suzuki–Miyaura cross-coupling reaction52A unified machine-learning protocol for asymmetric catalysis as a proof of concept demonstration using asymmetric hydrogenation131The Roles of the NLRP3 Inflammasome in Neurodegenerative and Metabolic Diseases and in Relevant Advanced Therapeutic Interventions84Automated droplet reactor for the synthesis of iron oxide/gold core-shell nanoparticles41Toward “On‐Demand” Materials Synthesis and Scientific Discovery through Intelligent Robots76Neural network agent playing spin Hamiltonian games on a quantum computer6Artificial intelligence and machine learning for targeted energy storage solutions64Cautious Reinforcement Learning with Logical Constraints19Current and Future Roles of Artificial Intelligence in Medicinal Chemistry Synthesis243Hard-threshold neural network-based prediction of organic synthetic outcomes1Spoken Language Acquisition Based on Reinforcement Learning and Word Unit Segmentation7Deep reinforcement learning for the control of microbial co-cultures in bioreactors130ChemOS: An orchestration software to democratize autonomous discovery156Evolving the Materials Genome: How Machine Learning Is Fueling the Next Generation of Materials Discovery99Microfluidic Synthesis of Luminescent and Plasmonic Nanoparticles: Fast, Efficient, and Data‐Rich87A Comparative Study of Model-Free Reinforcement Learning Approaches2Artificial Chemist: An Autonomous Quantum Dot Synthesis Bot323Deep Deterministic Policy Gradient for Portfolio Management6Big-Data Science in Porous Materials: Materials Genomics and Machine Learning599"I’m Sorry Dave, I’m Afraid I Can’t Do That" Deep Q-Learning from Forbidden Actions7Machine-learning-based simulation and fed-batch control of cyanobacterial-phycocyanin production in Plectonema by artificial neural network and deep reinforcement learning47A Prediction of Future States: AI-powered Chemical Innovation for Defense Applications2Machine Learning for Polymer Swelling in Liquids34Introduction: An Overview of AI in Oncology Drug Discovery and Development7Predictive Synthesis of Quantum Materials by Probabilistic Reinforcement Learning0Machine learning-based discrete element reaction model for predicting the dechlorination of poly (vinyl chloride) in NaOH/ethylene glycol solvent with ball milling13Multithreaded scheduling for program segments based on chemical reaction optimizer22Reinforcement learning based optimization of process chromatography for continuous processing of biopharmaceuticals60Functional test generation from UI test scenarios using reinforcement learning for android applications25Automated Functional Test Generation Practice for a Large-Scale Android Application2Virtual microstructure design for steels using generative adversarial networks56Additive Manufacturing of Functional Microarchitected Reactors for Energy, Environmental, and Biological Applications50Prediction of Energetic Material Properties from Electronic Structure Using 3D Convolutional Neural Networks97Machine Learning Tools to Predict Hot Injection Syntheses Outcomes for II–VI and IV–VI Quantum Dots37Adaptive Optimization of Chemical Reactions with Minimal Experimental Information82Artificial intelligence and automation in computer aided synthesis planning88Deep Learning for Prediction and Optimization of Fast-Flow Peptide Synthesis60Machine Learning Methods in Drug Discovery456Learning-based controlled concurrency testing20Multi-task Bayesian Optimization of Chemical Reactions1Multi-task Bayesian Optimization of Chemical Reactions3Intelligent Microfluidics: The Convergence of Machine Learning and Microfluidics in Materials Science and Biomedicine189Pareto Deterministic Policy Gradients and Its Application in 5G Massive MIMO Networks1Machine Learning Based Applications for Data Visualization, Modeling, Control, and Optimization for Chemical and Biological Systems1Digitization of Organic Synthesis — How Synthetic Organic Chemists Use AI Technology —24Self‐Driven Multistep Quantum Dot Synthesis Enabled by Autonomous Robotic Experimentation in Flow95Modeling and optimization of textile manufacturing process using intelligent techniques0Explainability in deep reinforcement learning319Accelerated screening of colloidal nanocrystals using artificial neural network-assisted autonomous flow reactor technology32Automated Process Synthesis Using Reinforcement Learning2Control of A Polyol Process Using Reinforcement Learning9Data-driven algorithms for inverse design of polymers100Energy-, time-, and labor-saving synthesis of α-ketiminophosphonates: machine-learning-assisted simultaneous multiparameter screening for electrochemical oxidation39Exploring the Landscapes and Emerging Trends of Reinforcement Learning from 1990 to 2020: A Bibliometric Analysis0Machine-learning-assisted low dielectric constant polymer discovery49Toward autonomous design and synthesis of novel inorganic materials159Toward Machine Learning-Enhanced High-Throughput Experimentation155Transformative Applications of Machine Learning for Chemical Reactions4Navigating through the Maze of Homogeneous Catalyst Design with Machine Learning88ES-ENAS: Efficient Evolutionary Optimization for Large Hybrid Search Spaces0Recent Progress of Deep Learning in Drug Discovery22What Can Text Mining Tell Us About Lithium‐Ion Battery Researchers’ Habits?34Self‐Driven Multistep Quantum Dot Synthesis Enabled by Autonomous Robotic Experimentation in Flow31Summit: Benchmarking Machine Learning Methods for Reaction Optimisation95A Study on the Efficacy of Deep Reinforcement Learning for Intrusion Detection12Bayesian reaction optimization as a tool for chemical synthesis1044Integrating Computational and Experimental Workflows for Accelerated Organic Materials Discovery74Deep Reinforcement Learning Techniques in Diversified Domains: A Survey57The Challenges of Machine Learning and Their Economic Implications18Gemini: Dynamic Bias Correction for Autonomous Experimentation and Molecular Simulation1Solvent extraction process design using deep reinforcement learning15Quantum circuit optimization with deep reinforcement learning66A knowledge‐enhanced deep reinforcement learning‐based shape optimizer for aerodynamic mitigation of wind‐sensitive structures81Gaming the beamlines—employing reinforcement learning to maximize scientific outcomes at large-scale user facilities12Sampling and Analysis in Flow: The Keys to Smarter, More Controllable, and Sustainable Fine‐Chemical Manufacturing71Sampling and Analysis in Flow: The Keys to Smarter, More Controllable, and Sustainable Fine‐Chemical Manufacturing31Multi-objective optimization of the textile manufacturing process using deep-Q-network based multi-agent reinforcement learning108Dreams, False Starts, Dead Ends, and Redemption: A Chronicle of the Evolution of a Chemoinformatic Workflow for the Optimization of Enantioselective Catalysts56Max-plus approximation for reinforcement learning9

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  2. Machine learning for predicting product distributions in catalytic regioselective reactions

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