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RESEARCH PAPER · Chemistry of Materials · 2020

Robot-Accelerated Perovskite Investigation and Discovery

Zhi Li, Mansoor Ani Najeeb, Liana Alves, Alyssa Sherman, Venkateswaran Shekar, Peter L. Cruz Parrilla, Ian M. Pendleton, Wesley Wang, Philip W. Nega, Mat­thias Zeller, Joshua Schrier, Alexander J. Norquist, Emory M. Chan

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Robot-Accelerated Perovskite Investigation and DiscoveryOriginalMachine Learning Transition Temperatures from 2D Structure10Computer Vision for Recognition of Materials and Vessels in Chemistry Lab Settings and the Vector-LabPics Dataset0Computer Vision for Recognition of Materials and Vessels in Chemistry Lab Settings and the Vector-LabPics Dataset1Machine-Learning-Accelerated Perovskite Crystallization145Can Machines “Learn” Halide Perovskite Crystal Formation without Accurate Physicochemical Features?12Elucidating the Weakly Reversible Cs–Pb–Br Perovskite Nanocrystal Reaction Network with High-Throughput Maps and Transformations73Materials Acceleration Platforms: On the way to autonomous experimentation149A mobile robotic chemist1488Notizen aus der Chemie0Computer Vision for Recognition of Materials and Vessels in Chemistry Lab Settings and the Vector-LabPics Data Set75Pressing challenges of halide perovskite thin film growth67On-the-fly closed-loop materials discovery via Bayesian active learning540Data-driven materials research enabled by natural language processing and information extraction302Digitizing Chemistry Using the Chemical Processing Unit: From Synthesis to Discovery94Accelerated AI development for autonomous materials synthesis in flow68Accelerating organic solar cell material's discovery: high-throughput screening and big data129Determining usefulness of machine learning in materials discovery using simulated research landscapes15Machine Learning Accelerated Insights of Perovskite Materials3Scientific intuition inspired by machine learning-generated hypotheses35Toward autonomous design and synthesis of novel inorganic materials159Scientific intuition inspired by machine learning-generated hypotheses31Our Most Downloaded Papers Published in 20200Elucidating the Full Potential of OPV Materials Utilizing a High-Throughput Robot-Based Platform and Machine Learning171Quo Vadis , Nanoparticle-Enabled In Vivo Fluorescence Imaging?46The 2D Halide Perovskite Rulebook: How the Spacer Influences Everything from the Structure to Optoelectronic Device Efficiency1085A data fusion approach to optimize compositional stability of halide perovskites158Machine learning in materials science: From explainable predictions to autonomous design280Solution Mixing Calculations as a Geometry, Linear Algebra, and Convex Analysis Problem11Data Science in Chemical Engineering: Applications to Molecular Science20The Value of Watching How Materials Grow: A Multimodal Case Study on Halide Perovskites20Improving Data and Prediction Quality of High-Throughput Perovskite Synthesis with Model Fusion19Crystallography companion agent for high-throughput materials discovery99Two-step machine learning enables optimized nanoparticle synthesis267Molecular excited states through a machine learning lens200Machine Learning in Solid‐State Chemistry: Heusler Compounds0Deep learning for visualization and novelty detection in large X-ray diffraction datasets63Nanoparticle synthesis assisted by machine learning544Fidelity of Robotic Chemical Operations of Homogenous and Heterogeneous Reactions1Autonomous experimentation systems for materials development: A community perspective398Using automated serendipity to discover how trace water promotes and inhibits lead halide perovskite crystal formation24Phase–Property Diagrams for Multicomponent Oxide Systems toward Materials Libraries58Applied Machine Learning for Developing Next‐Generation Functional Materials72Cyclohexylammonium‐Based 2D/3D Perovskite Heterojunction with Funnel‐Like Energy Band Alignment for Efficient Solar Cells (23.91%)130Accelerated discovery of 3D printing materials using data-driven multiobjective optimization134Machine learning for high-throughput experimental exploration of metal halide perovskites118High‐Entropy Energy Materials in the Age of Big Data: A Critical Guide to Next‐Generation Synthesis and Applications107Constrained non-negative matrix factorization enabling real-time insights of in situ and high-throughput experiments31Luminescence and Structural Characteristics of Lead Halide Perovskite Films Deposited In Situ by a Versatile Multisource Aerosol Assisted Chemical Vapor Deposition (AACVD) Method12High-Throughput Study of Antisolvents on the Stability of Multicomponent Metal Halide Perovskites through Robotics-Based Synthesis and Machine Learning Approaches75Probabilistic deep learning approach for targeted hybrid organic-inorganic perovskites8Autonomous materials synthesis via hierarchical active learning of nonequilibrium phase diagrams98Accelerating perovskite materials discovery and correlated energy applications through artificial intelligence62An Object-Oriented Framework to Enable Workflow Evolution Across Materials Acceleration Platforms0Bayesian optimization in continuous spaces via virtual process embeddings11Intelligent control of nanoparticle synthesis through machine learning83Machine learning enabling high-throughput and remote operations at large-scale user facilities16Development and Prospects of Halide Perovskite Single Crystal Films19From Platform to Knowledge Graph: Evolution of Laboratory Automation108Dimensional Control over Metal Halide Perovskite Crystallization Guided by Active Learning32Toward autonomous materials research: Recent progress and future challenges61Electrocatalytic Oxygen Evolution Reaction1Active meta-learning for predicting and selecting perovskite crystallization experiments24Data-Driven Design and Autonomous Experimentation in Soft and Biological Materials Engineering42Hypothesis Learning in Automated Experiment: Application to Combinatorial Materials Libraries72Predicting Experimental Formability of Hybrid Organic–Inorganic Perovskites via Imbalanced Learning25Two-Dimensional Organic–Inorganic Hybrid Materials with Dielectric Switching and Photoluminescence Properties29The case for data science in experimental chemistry: examples and recommendations83Discovery of Pb-free hybrid organic–inorganic 2D perovskites using a stepwise optimization strategy24Opportunities for machine learning to accelerate halide-perovskite commercialization and scale-up35Structured illumination with thermal imaging (SI-TI): A dynamically reconfigurable metrology for parallelized thermal transport characterization16Sidekick: A Low-Cost Open-Source 3D-printed liquid dispensing robot35Low-Dimensional Organic Lead Halides with Organic–Inorganic Collaborative Luminescence Regulated by Anion in Dimension14Spatiotemporal Route to Understanding Metal Halide Perovskitoid Crystallization7The Development of New Perovskite-Type Oxygen Transport Membranes Using Machine Learning10Predicting Indium Phosphide Quantum Dot Properties from Synthetic Procedures Using Machine Learning47Serendipity based recommender system for perovskites material discovery: balancing exploration and exploitation across multiple models7Serendipity based recommender system for perovskites material discovery: balancing exploration and exploitation across multiple models5An Object-Oriented Framework to Enable Workflow Evolution across Materials Acceleration Platforms1Highly Emitting Perovskite Nanocrystals with 2-Year Stability in Water through an Automated Polymer Encapsulation for Bioimaging99Principled Exploration of Bipyridine and Terpyridine Additives to Promote Methylammonium Lead Iodide Perovskite Crystallization13The chemistry of errors9An object-oriented framework to enable workflow evolution across materials acceleration platforms21High-throughput computations and machine learning for halide perovskite discovery32Efficient autonomous material search method combining ab initio calculations, autoencoder, and multi-objective Bayesian optimization16Recent Developments in Process Digitalisation for Advanced Nanomaterial Syntheses11AutoMat: Automated materials discovery for electrochemical systems16Challenges, Opportunities, and Prospects in Metal Halide Perovskites from Theoretical and Machine Learning Perspectives53Machine learning for a sustainable energy future517An adaptive framework to accelerate optimization of high flame retardant composites using machine learning41Toward autonomous laboratories: Convergence of artificial intelligence and experimental automation118Collaborative methods to enhance reproducibility and accelerate discovery20An open-source environmental chamber for materials-stability testing using an optical proxy13Bayesian optimisation for efficient material discovery: a mini review49Combinatorial mixtures of organic solutes for improved liquid/liquid extraction of ions4ESAMP: event-sourced architecture for materials provenance management and application to accelerated materials discovery18Machine learning in energy chemistry: introduction, challenges and perspectives31The Application of Novel Functional Materials to Machine Learning0Spacer-Dependent and Pressure-Tuned Structures and Optoelectronic Properties of 2D Hybrid Halide Perovskites21Reexamining the Post‐Treatment Effects on Perovskite Solar Cells: Passivation and Chloride Redistribution24Materials informatics for developing new restorative dental materials: a narrative review17The rise of self-driving labs in chemical and materials sciences571How to build an effective self-driving laboratory15Role of AI in experimental materials science42Combinatorial synthesis for AI-driven materials discovery113Self-Driving Laboratory for Polymer Electronics86Accelerated Design of Architected Materials with Multifidelity Bayesian Optimization6A self-driving laboratory optimizes a scalable process for making functional coatings17The role of machine learning in perovskite solar cell research42A review on computational modeling of instability and degradation issues of halide perovskite photovoltaic materials24Recent development in metal halide perovskites synthesis to improve their charge-carrier mobility and photocatalytic efficiency22Sustainable materials acceleration platform reveals stable and efficient wide-bandgap metal halide perovskite alloys31Conversion of a 3D printer for versatile automation of dip coating processes9Revolutionizing Low‐Cost Solar Cells with Machine Learning: A Systematic Review of Optimization Techniques35Improving efficiency of autonomous material search via transfer learning from nontarget properties4Alloy synthesis and processing by semi-supervised text mining27Optimizing Perovskite Thin‐Film Parameter Spaces with Machine Learning‐Guided Robotic Platform for High‐Performance Perovskite Solar Cells89Automation to Enable High-Throughput Chemical Proteomics8Accelerated Discovery of Perovskite-Inspired Materials through Robotized Screening Including Solar Cell Characterization2Automated LARP synthesis identifies optimal ligand combinations for perovskite nanocrystal preparation2Modular, multi-robot integration of laboratories: an autonomous workflow for solid-state chemistry104Machine learning for expediting next-generation of fire-retardant polymer composites43A high throughput synthetic workflow for solid state synthesis of oxides9Autonomous robotic experimentation system for powder X-ray diffraction19Navigation through high-dimensional chemical space: discovery of Ba 5 Y 13 [SiO 4 ] 8 O 8.5 and Ba 3 Y 2 [Si 2 O 7 ] 22PASCAL: the perovskite automated spin coat assembly line accelerates composition screening in triple-halide perovskite alloys17Review of low-cost self-driving laboratories in chemistry and materials science: the “frugal twin” concept93Six metal cations in one double perovskite: exploring complexity of chloride elpasolites by high-throughput experimentation7Structural Insights from X-Ray Crystallography0Advancing perovskite solar cell commercialization: Bridging materials, vacuum deposition, and AI-assisted automation32Synchrotron radiation data-driven artificial intelligence approaches in materials discovery30Transforming research laboratories with connected digital twins19Lead-Free Halide Perovskites for Photocatalysis via High-Throughput Exploration30Designing workflows for materials characterization22Materials genome engineering accelerates the research and development of organic and perovskite photovoltaics64Machine‐Learning‐Assisted Discovery of Mechanosynthesized Lead‐Free Metal Halide Perovskites for the Oxidative Photocatalytic Cleavage of Alkenes22Unprecedented Richness of Temperature‐ and Pressure‐Induced Polymorphism in 1D Lead Iodide Perovskite10Progress and prospects of quantum emission from perovskites6Integration of artificial intelligence and big data in materials science: New paradigms and scientific discoveries2Structural Evolution of Millisecond Laser-Induced Metastable Crystalline GeTe0Effects of Ligand Chemistry on Ion Transport in 2D Hybrid Organic–Inorganic Perovskites12Self-Driving Laboratories for Chemistry and Materials Science664Autonomous search for materials with high Curie temperature using ab initio calculations and machine learning2Autonomous search for half-metallic materials with B 2 structure5Digital manufacturing of perovskite materials and solar cells12Repeatable Perovskite Solar Cells through Fully Automated Spin-Coating and Quenching21The synergy of artificial intelligence and nanotechnology towards advancing innovation and sustainability - A mini-review116From Sunlight to Solutions: Closing the Loop on Halide Perovskites3Advancing Rare-Earth (4 f ) and Actinide (5 f ) Separation through Machine Learning and Automated High-Throughput Experiments11A comprehensive review of machine learning applications in perovskite solar cells: Materials discovery, device performance, process optimization and systems integration41Enhancing Durability of Organic–Inorganic Hybrid Perovskite Solar Cells in High‐Temperature Environments: Exploring Thermal Stability, Molecular Structures, and AI Applications18

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