Next-Generation Experimentation with Self-Driving Laboratories

Electrical energy storage for the grid: A battery of choices

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Pattern Recognition and Neural Networks

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Automatic Chemical Design Using a Data-Driven Continuous Representation of Molecules

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Materials for next-generation desalination and water purification membranes

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The high-throughput highway to computational materials design

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Planning chemical syntheses with deep neural networks and symbolic AI

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Automatic Chemical Design Using a Data-Driven Continuous Representation of Molecules.

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Machine-learning-assisted materials discovery using failed experiments

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Generating Focused Molecule Libraries for Drug Discovery with Recurrent Neural Networks

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Impact of high-throughput screening in biomedical research

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A review of graphene and graphene oxide sponge: material synthesis and applications to energy and the environment

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Design of efficient molecular organic light-emitting diodes by a high-throughput virtual screening and experimental approach

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Integration of virtual and high-throughput screening

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Big Data Meets Quantum Chemistry Approximations: The Δ-Machine Learning Approach

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Accelerated search for materials with targeted properties by adaptive design

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Low Data Drug Discovery with One-Shot Learning

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Accelerating the discovery of materials for clean energy in the era of smart automation

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Controlling an organic synthesis robot with machine learning to search for new reactivity

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Machine Learning in Computer-Aided Synthesis Planning

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Machine learning of molecular electronic properties in chemical compound space

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Assessment and Validation of Machine Learning Methods for Predicting Molecular Atomization Energies

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A redox-flow battery with an alloxazine-based organic electrolyte

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Retrosynthetic Reaction Prediction Using Neural Sequence-to-Sequence Models

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Reconfigurable system for automated optimization of diverse chemical reactions

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Optimizing Chemical Reactions with Deep Reinforcement Learning

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Neural Networks for the Prediction of Organic Chemistry Reactions

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Machine learning of molecular electronic properties in chemical compound space

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Combinatorial and High‐Throughput Materials Science

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Autonomy in materials research: a case study in carbon nanotube growth

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Phoenics: A Bayesian Optimizer for Chemistry

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Accelerating Electrolyte Discovery for Energy Storage with High-Throughput Screening

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High-throughput screening of solid-state catalyst libraries

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Intelligent routes to the controlled synthesis of nanoparticles

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Commercializing generic technology: The case of advanced materials ventures

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Fast machine-learning online optimization of ultra-cold-atom experiments

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An Integrated Microreactor System for Self‐Optimization of a Heck Reaction: From Micro‐ to Mesoscale Flow Systems

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A Novel Internet-Based Reaction Monitoring, Control and Autonomous Self-Optimization Platform for Chemical Synthesis

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High-throughput discovery of organic cages and catenanes using computational screening fused with robotic synthesis

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ChemOS: Orchestrating autonomous experimentation

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The Surprising Creativity of Digital Evolution: A Collection of Anecdotes from the Evolutionary Computation and Artificial Life Research Communities

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Predicting Organic Reaction Outcomes with Weisfeiler-Lehman NetworkPreprint

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<i>In silico</i> Design of Porous Polymer Networks: High-Throughput Screening for Methane Storage Materials

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Enabling Technologies for the Future of Chemical Synthesis

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ChemOS: An orchestration software to democratize autonomous discovery

Roch, L. M., Häse, F., Kreisbeck, C., Tamayo-Mendoza, T., Yunker, L. P. E., Hein, J. E., & Aspuru‐Guzik, A. (2020) · PLoS ONE · doi:10.1371/journal.pone.0229862 · Cited by 166 · see citing works

Chimera: enabling hierarchy based multi-objective optimization for self-driving laboratories

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Online monitoring and analysis for autonomous continuous flow self-optimizing reactor systems

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Pattern Recognition and Neural Networks

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Automated Multitrajectory Method for Reaction Optimization in a Microfluidic System using Online IR Analysis

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Machine learning exciton dynamics

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Human versus Robots in the Discovery and Crystallization of Gigantic Polyoxometalates

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Simultaneous solvent screening and reaction optimization in microliter slugs

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Remote-controlled experiments with cloud chemistry

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An autonomous organic reaction search engine for chemical reactivity

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Designing Algorithms To Aid Discovery by Chemical Robots

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Networking chemical robots for reaction multitasking

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Self‐Optimizing Reactor Systems: Algorithms, On‐line Analytics, Setups, and Strategies for Accelerating Continuous Flow Process Optimization

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A retrospective on the automation of laboratory synthetic chemistry

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The Effect of Self-Optimisation Targets on the Methylation of Alcohols Using Dimethyl Carbonate in Supercritical CO2

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Investigation of Cocatalysis Conditions Using an Automated Microscale Multireactor Workstation: Synthesis of meso-Tetramesitylporphyrin

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Human versus Robots in the Discovery and Crystallization of Gigantic Polyoxometalates

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The Surprising Creativity of Digital Evolution: A Collection of Anecdotes from the Evolutionary Computation and Artificial Life Research CommunitiesPreprint

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Materials for the 21st Century

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Catalyst: The Metaphysics of Chemical Reactivity

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Reaction: The Near Future of Artificial Intelligence in Materials Discovery

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ChemOS: An Orchestration Software to Democratize Autonomous DiscoveryPreprint

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Autonomous Experimentation Applied to Carbon Nanotube Synthesis

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Automation and optimization by simplex methods of 6-chlorohexanol synthesis

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Water electrolysis: from textbook knowledge to the latest scientific strategies and industrial developments

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Bayesian reaction optimization as a tool for chemical synthesis

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QSAR without borders

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Graph neural networks for materials science and chemistry

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Self-driving laboratory for accelerated discovery of thin-film materials

MacLeod, B. P., Parlane, F. G. L., Morrissey, T. D., Häse, F., Roch, L. M., Dettelbach, K. E., Moreira, R., Yunker, L. P. E., Rooney, M. B., Deeth, J. R., et al. (2020) · Science Advances · doi:10.1126/sciadv.aaz8867 · Cited by 824 · see citing works

Technological Innovations in Photochemistry for Organic Synthesis: Flow Chemistry, High-Throughput Experimentation, Scale-up, and Photoelectrochemistry

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Self-Driving Laboratories for Chemistry and Materials Science

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Big-Data Science in Porous Materials: Materials Genomics and Machine Learning

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The rise of self-driving labs in chemical and materials sciences

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Opportunities and Challenges for Machine Learning in Materials Science

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Artificial Intelligence Applied to Battery Research: Hype or Reality?

Lombardo, T., Duquesnoy, M., El-Bouysidy, H., Årén, F., Gallo‐Bueno, A., Jørgensen, P. B., Bhowmik, A., Demortière, A., Ayerbe, E., Alcaide, F., et al. (2021) · Chemical Reviews · doi:10.1021/acs.chemrev.1c00108 · Cited by 511 · see citing works

Data-Driven Strategies for Accelerated Materials Design

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The Role of Machine Learning in the Understanding and Design of Materials

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Integrating QSAR modelling and deep learning in drug discovery: the emergence of deep QSAR

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Autonomous experimentation systems for materials development: A community perspective

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Machine learning directed drug formulation development

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Machine learning for metabolic engineering: A review

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A machine learning Automated Recommendation Tool for synthetic biology

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Autonomous Chemical Experiments: Challenges and Perspectives on Establishing a Self-Driving Lab

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Machine learning in clinical decision making

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Machine learning in materials science: From explainable predictions to autonomous design

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Data-science driven autonomous process optimization

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Progress and prospects for accelerating materials science with automated and autonomous workflows

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