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RESEARCH PAPER · MRS Communications · 2019

Experiment Specification, Capture and Laboratory Automation Technology (ESCALATE): a software pipeline for automated chemical experimentation and data management

Ian M. Pendleton, Gary Cattabriga, Zhi Li, Mansoor Ani Najeeb, Sorelle A. Friedler, Alexander J. Norquist, Emory M. Chan, Joshua Schrier

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Experiment Specification, Capture and Laboratory Automation Technology (ESCALATE): a software pipeline for automated chemical experimentation and data managementOriginalProgress and prospects for accelerating materials science with automated and autonomous workflows228Data Infrastructure Elements in Support of Accelerated Materials Innovation: ELA, PyMKS, and MATIN21Rapid Characterization and Parameter Space Exploration of Perovskites Using an Automated Routine12Autonomous intelligent agents for accelerated materials discovery95Machine-Learning-Assisted Synthesis of Polar Racemates32Can Machines “Learn” Halide Perovskite Crystal Formation without Accurate Physicochemical Features?12Twenty years of exceptional success: The molecular education and research consortium in undergraduate computational chemistry ( MERCURY )29Automation and low-cost proteomics for characterization of the protein corona: experimental methods for big data20Robot-Accelerated Perovskite Investigation and Discovery187Materials Acceleration Platforms: On the way to autonomous experimentation149A user-centered approach to designing an experimental laboratory data platform2Random forest machine learning models for interpretable X-ray absorption near-edge structure spectrum-property relationships171On-the-fly closed-loop materials discovery via Bayesian active learning540Golem: an algorithm for robust experiment and process optimization39Integrated “Generate, Make, and Test” for Formulated Products using Knowledge Graphs9Solution Mixing Calculations as a Geometry, Linear Algebra, and Convex Analysis Problem11Data Science in Chemical Engineering: Applications to Molecular Science20Automation and computer-assisted planning for chemical synthesis191Improving Data and Prediction Quality of High-Throughput Perovskite Synthesis with Model Fusion19Data Shepherding in Nanotechnology. The Initiation15Autonomous experimentation systems for materials development: A community perspective398Using automated serendipity to discover how trace water promotes and inhibits lead halide perovskite crystal formation24Chemputation and the Standardization of Chemical Informatics73Enabling modular autonomous feedback-loops in materials science through hierarchical experimental laboratory automation and orchestration5Implications of the BATTERY 2030+ AI‐Assisted Toolkit on Future Low‐TRL Battery Discoveries and Chemistries65Application Analysis of Electrical Automation Based on Artificial Intelligence Technology0Modern machine learning for tackling inverse problems in chemistry: molecular design to realization50Enabling Modular Autonomous Feedback‐Loops in Materials Science through Hierarchical Experimental Laboratory Automation and Orchestration74From Platform to Knowledge Graph: Evolution of Laboratory Automation108Dimensional Control over Metal Halide Perovskite Crystallization Guided by Active Learning32Machine learning in nuclear materials research125Round Trip: An Automated Pipeline for Experimental Design, Execution, and Analysis9Digital Twins for Materials89A Perspective on Digital Knowledge Representation in Materials Science and Engineering40The case for data science in experimental chemistry: examples and recommendations83Spatiotemporal Route to Understanding Metal Halide Perovskitoid Crystallization7Effect of Blended Teaching Mode in Colleges and Universities Based on Automation Technology on College Students’ English Performance10Serendipity 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 models5Principled Exploration of Bipyridine and Terpyridine Additives to Promote Methylammonium Lead Iodide Perovskite Crystallization13Renewed Prospects for Organic Photovoltaics1052Delivering real-time multi-modal materials analysis with enterprise beamlines5Collaborative methods to enhance reproducibility and accelerate discovery20ESAMP: event-sourced architecture for materials provenance management and application to accelerated materials discovery18Integrating autonomy into automated research platforms32Orchestrating nimble experiments across interconnected labs37The laboratory of Babel: highlighting community needs for integrated materials data management20The materials experiment knowledge graph25What is missing in autonomous discovery: open challenges for the community44Knowledge-integrated machine learning for materials: lessons from gameplaying and robotics137How to build an effective self-driving laboratory15Machine learning and experiments: A synergy for the development of functional materials19Next-generation intelligent laboratories for materials design and manufacturing25An Innovation Development of Document Management and Security Model for Commercial Database Handling Systems4Flexible formulation of value for experiment interpretation and design6AlabOS: a Python-based reconfigurable workflow management framework for autonomous laboratories34Autonomous millimeter scale high throughput battery research system12The future of self-driving laboratories: from human in the loop interactive AI to gamification103Autonomous millimeter scale high throughput battery research system (Auto-MISCHBARES)0Autonomous millimeter scale high throughput battery research system (Auto-MISCHBARES)1Autonomous millimeter scale high throughput battery research system (Auto-MISCHBARES)0A dynamic knowledge graph approach to distributed self-driving laboratories108A workflow management system for reproducible and interoperable high-throughput self-driving experiments9A Vision for the Future of Materials Innovation and How to Fast-Track It with Services2Reproducibility in automated chemistry laboratories using computer science abstractions28A property graph schema for automated metadata capture, reproducibility and knowledge discovery in high-throughput bioprocess development5Science acceleration and accessibility with self-driving labs83Towards a sustainable high-quality materials data ecosystem: frameworks and strategies6Bayesian Optimisation for the Experimental Sciences: A Practical Guide to Data‐Efficient Optimisation of Laboratory Workflows5Leveling Up Upconverting Nanoparticles with Machine Learning4Real-time Multi-instrument Autonomous Materials Screening for Discovery of Novel Phase-change Memory Materials0The past, present and future of self-driving laboratories5The Interface Science Data Repository: A (meta)data framework and platform for FAIR data reporting in experimental fluid interface science0

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  5. Machine-Learning-Assisted Synthesis of Polar Racemates

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  16. Solution Mixing Calculations as a Geometry, Linear Algebra, and Convex Analysis Problem

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