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RESEARCH PAPER · Nature Synthesis · 2023

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

Milad Abolhasani, Eugenia Kumacheva

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42 direct citing works

The rise of self-driving labs in chemical and materials sciencesOriginalAccelerating reaction modeling using dynamic flow experiments, part 2: development of a digital twin21Digital pipette: open hardware for liquid transfer in self-driving laboratories28Driving school for self-driving labs17AlphaFlow: autonomous discovery and optimization of multi-step chemistry using a self-driven fluidic lab guided by reinforcement learning215Autonomous experimental systems in materials science22The promise and pitfalls of AI for molecular and materials synthesis22Recent Developments in Reactor Automation for Multistep Chemical Synthesis27Autonomous sputter synthesis of thin film nitrides with composition controlled by Bayesian optimization of optical plasma emission26Treasuring trash: Pt/SrTiO3 catalysts process plastic waste into high-value materials25Learning the Language of NMR: Structure Elucidation from NMR spectra using Transformer Models32Future directions in ceramic additive manufacturing: Fiber reinforcements and artificial intelligence23Intelligent Materials and Nanomaterials Improving Physical Properties and Control Oriented on Electronic Implementations24In Pursuit of the Exceptional: Research Directions for Machine Learning in Chemical and Materials Science992023 Roadmap on molecular modelling of electrochemical energy materials40Large language models for chemistry robotics110Single‐Atom Heterogeneous Catalysts: Human‐ and AI‐Driven Platform for Augmented Designs, Analytics and Reality‐Enabled Manufacturing22New insights on designing the next-generation materials for electrochemical synthesis of reactive oxidative species towards efficient and scalable water treatment: A review and perspectives16Smart Dope: A Self‐Driving Fluidic Lab for Accelerated Development of Doped Perovskite Quantum Dots47A Review of Transition Metal Boride, Carbide, Pnictide, and Chalcogenide Water Oxidation Electrocatalysts295Keeping an “eye” on the experiment: computer vision for real-time monitoring and control44Conducting polymers: Towards printable transparent electrodes32Integrating QSAR modelling and deep learning in drug discovery: the emergence of deep QSAR397Autonomous nanomanufacturing of lead-free metal halide perovskite nanocrystals using a self-driving fluidic lab29Navigating the unknown with AI: multiobjective Bayesian optimization of non-noble acidic OER catalysts59Autonomous, multiproperty-driven molecular discovery: From predictions to measurements and back172AlabOS: a Python-based reconfigurable workflow management framework for autonomous laboratories33Automation and machine learning augmented by large language models in a catalysis study107Bioinformatics software development: Principles and future directions17Heterogeneous catalysis for the environment92PANDA: a self-driving lab for studying electrodeposited polymer films27Review of low-cost self-driving laboratories in chemistry and materials science: the “frugal twin” concept93What can molecular assembly learn from catalysed assembly in living organisms?21Disordered enthalpy–entropy descriptor for high-entropy ceramics discovery246Advancing perovskite solar cell commercialization: Bridging materials, vacuum deposition, and AI-assisted automation32Self-driving laboratories to autonomously navigate the protein fitness landscape207A dynamic knowledge graph approach to distributed self-driving laboratories108Metabolomics in the era of artificial intelligence25A dynamic Bayesian optimized active recommender system for curiosity-driven partially Human-in-the-loop automated experiments45Transforming research laboratories with connected digital twins19Performance metrics to unleash the power of self-driving labs in chemistry and materials science93Artificial Intelligence (AI) for Sustainable Resource Management and Chemical Processes25Artificial Intelligence (AI) for Sustainable Resource Management and Chemical Processes31Autonomous reaction Pareto-front mapping with a self-driving catalysis laboratory74Materials genome engineering accelerates the research and development of organic and perovskite photovoltaics64Crystal Structure Assignment for Unknown Compounds from X-ray Diffraction Patterns with Deep Learning31An integrated high-throughput robotic platform and active learning approach for accelerated discovery of optimal electrolyte formulations84Autonomous closed-loop mechanistic investigation of molecular electrochemistry via automation64Building an Arduino-Based Open-Source Programmable Multichannel Syringe Pump: A Useful Tool for Fluid Delivery in Microfluidics and Flow Chemistry21Navigating phase diagram complexity to guide robotic inorganic materials synthesis82The twelve goals of circular analytical chemistry61Together but not scrambled: A perspective on chaotic printing/bioprinting18Donor Preactivation-Based Glycan Assembly: from Manual to Automated Synthesis38AEcroscopy: A Software–Hardware Framework Empowering Microscopy Toward Automated and Autonomous Experimentation33Embracing data science in catalysis research117Toward Self-Driven Autonomous Material and Device Acceleration Platforms (AMADAP) for Emerging Photovoltaics Technologies54Degradable π-Conjugated Polymers60Autonomous Synthesis of Thin Film Materials with Pulsed Laser Deposition Enabled by In Situ Spectroscopy and Automation42Multiparameter optimization of microbial fuel cell outputs using linear sweep voltammetry and microfluidics16Combined helical-blade-strengthened co-flow focusing and high-throughput screening for the synthesis of highly homogeneous nanoliposomes16Delocalized, asynchronous, closed-loop discovery of organic laser emitters160Roadmap on data-centric materials science27The advancement of artificial intelligence in biomedical research and health innovation: challenges and opportunities in emerging economies79Recent progress on surface chemistry II: Property and characterization58Wet-spinning of carbon nanotube fibers: dispersion, processing and properties76Autonomous chemistry: Navigating self-driving labs in chemical and material sciences95Accelerating Formulation Design via Machine Learning: Generating a High-throughput Shampoo Formulations Dataset24Single Atom Catalysts Based on Earth-Abundant Metals for Energy-Related Applications311Targeted materials discovery using Bayesian algorithm execution48Temperature excavation to boost machine learning battery thermochemical predictions69Accelerated discovery of perovskite solid solutions through automated materials synthesis and characterization29Engineering a Sustainable Future: Harnessing Automation, Robotics, and Artificial Intelligence with Self-Driving Laboratories42Self-Driving Laboratories for Chemistry and Materials Science674Bayesian Conavigation: Dynamic Designing of the Material Digital Twins via Active Learning17Cephalo: Multi‐Modal Vision‐Language Models for Bio‐Inspired Materials Analysis and Design38AI‐Equipped Scanning Probe Microscopy for Autonomous Site‐Specific Atomic‐Level Characterization at Room Temperature29Catalysing (organo-)catalysis: Trends in the application of machine learning to enantioselective organocatalysis17Synthesis and Optical Characterization of Hydrazone-Substituted Push–Pull-Type NLOphores20Deeper insights into flame retardancy of polymers by interpretable, quantifiable, yet accurate machine-learning model17Traversing chemical space with active deep learning for low-data drug discovery44An affordable platform for automated synthesis and electrochemical characterization23Machine learning-guided strategies for reaction conditions design and optimization49Reproducibility in automated chemistry laboratories using computer science abstractions28Pivotal Role of Surface Terminations in MXene Thermodynamic Stability83From Molecular Electronics to Molecular Intelligence59Autonomous Battery Optimization by Deploying Distributed Experiments and Simulations19Impact of inhibition mechanisms, automation, and computational models on the discovery of organic corrosion inhibitors64AI-assisted autonomous manufacturing of tailored drug-loaded nanoparticles by multi-step continuous-flow platform22Artificial intelligence and machine learning at various stages and scales of process systems engineering36Autonomous mobile robots for exploratory synthetic chemistry215Large language models design sequence-defined macromolecules via evolutionary optimization16Multimodal Machine Learning for Materials Science: Discovery of Novel Li-Ion Solid Electrolytes22Machine learning materials properties with accurate predictions, uncertainty estimates, domain guidance, and persistent online accessibility17Continuous collective analysis of chemical reactions18COBRA web application to benchmark linear regression models for catalyst optimization with few-entry datasets16A multi-robot–multi-task scheduling system for autonomous chemistry laboratories32A self-driving fluidic lab for data-driven synthesis of lead-free perovskite nanocrystals20AI-driven advances in metal–organic frameworks: from data to design and applications47Artificial intelligence in drug development498Autonomous laboratories in China: an embodied intelligence-driven platform to accelerate chemical discovery20Autonomous organic synthesis for redox flow batteries via flexible batch Bayesian optimization22Cross-disciplinary perspectives on the potential for artificial intelligence across chemistry51Democratizing self-driving labs: advances in low-cost 3D printing for laboratory automation25Integrating artificial intelligence in energy transition: A comprehensive review248Recent Advances in Polymer-Based Photocatalysts for Environmental Remediation and Energy Conversion: A Review27Autonomous Optimization of Air‐Processed Perovskite Solar Cell in a Multidimensional Parameter Space23Self-driving lab for the photochemical synthesis of plasmonic nanoparticles with targeted structural and optical properties60Autonomous platform for solution processing of electronic polymers68Automated Research Platform for Development of Triplet–Triplet Annihilation Photon Upconversion Systems16Artificial Intelligence Meets Laboratory Automation in Discovery and Synthesis of Metal–Organic Frameworks: A Review41A Self-Driving Lab for Nano- and Advanced Materials Synthesis33Polymer-based nanocarriers to transport therapeutic biomacromolecules across the blood-brain barrier39Large language model for knowledge synthesis and AI-enhanced biomanufacturing39Solvent Screening for Separation Processes Using Machine Learning and High-Throughput Technologies34A Multiagent-Driven Robotic AI Chemist Enabling Autonomous Chemical Research On Demand167The emergence of automation in electrochemistry17Advancing polymer nanocomposites through mechanochemical approaches25Advances in the Design and Discovery of Organic Semiconductors Aided by Machine Learning18Intelligent Systems for Inorganic Nanomaterial Synthesis38Peptide catalysis: Trends and opportunities17Science acceleration and accessibility with self-driving labs83Using GNN property predictors as molecule generators35Empowering Generalist Material Intelligence with Large Language Models29Interpretable Machine Learning Applications: A Promising Prospect of AI for Materials68Machine Learning in nanoarchitectonics24Artificial Intelligence‐Driven Approaches in Semiconductor Research44Material intelligence by the convergence of artificial intelligence and robotic platforms16Real-time experiment-theory closed-loop interaction for autonomous materials science29Generative Deep Learning for de Novo Drug Design─A Chemical Space Odyssey40Flow-driven data intensification to accelerate autonomous inorganic materials discovery25A review on model-based design of experiments for parameter precision – Open challenges, trends and future perspectives21Tech-Enhanced Synthesis: Exploring the Synergy between Organic Chemistry and Technology45A chemical autonomous robotic platform for end-to-end synthesis of nanoparticles33From Molecules to Machines: A Multiscale Roadmap to Intelligent, Multifunctional Soft Robotics47Autonomous multi-robot synthesis and optimization of metal halide perovskite nanocrystals20Machine learning in X-ray diffraction for materials discovery and characterization19In Search of Beautiful Molecules: A Perspective on Generative Modeling for Drug Design37Advancing Organic Chemistry Using High‐Throughput Experimentation2633 Unresolved Questions in Nanoscience and Nanotechnology58Generative Artificial Intelligence Navigated Development of Solvents for Next Generation High‐Performance Magnesium Batteries17Accelerating discovery in natural science laboratories with AI and robotics: Perspectives and challenges19Reac-Discovery: an artificial intelligence–driven platform for continuous-flow catalytic reactor discovery and optimization16Evaluating large language model agents for automation of atomic force microscopy41A Computational Renaissance in High-Energy Density Materials (HEDMs) Research38Autonomous catalysis research with human–AI–robot collaboration37Harnessing artificial intelligence to advance CRISPR-based genome editing technologies32Toward AI ecosystems for electrolyte and interface engineering in solid-state batteries23Artificial intelligence and machine learning for plasmonic and surface-enhanced sensing37Using Machine Learning for Green Substitution of Industrial Chemicals: Integrating Functionality, Hazard, and Life Cycle Impact17Optimizing toward Discovery: AI-Driven Exploration of Lewis Acid–Base Catalysts for PET Glycolysis16LUMI-lab: A foundation model-driven autonomous platform enabling discovery of ionizable lipid designs for mRNA delivery38

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