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RESEARCH PAPER · Scientific Data · 2019

Text-mined dataset of inorganic materials synthesis recipes

Olga Kononova, Haoyan Huo, Tanjin He, Ziqin Rong, Tiago Botari, Wenhao Q. Sun, Vahe Tshitoyan, Gerbrand Ceder

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Text-mined dataset of inorganic materials synthesis recipesOriginalIn Layman’s Terms: Semi-Open Relation Extraction from Scientific Texts25Promising photovoltaic efficiency of a layered silicon oxide crystal Si 3 O2Representing Semantified Biological Assays in the Open Research Knowledge Graph5Toward Accelerated Thermoelectric Materials and Process Discovery102Merging Materials and Data Science: Opportunities, Challenges, and Education in Materials Informatics17Annotating and Extracting Synthesis Process of All-Solid-State Batteries from Scientific Literature14Perovskite Oxides Prepared by Hydrothermal and Solvothermal Synthesis: A Review of Crystallisation, Chemistry, and Compositions152Nanomaterial Synthesis Insights from Machine Learning of Scientific Articles by Extracting, Structuring, and Visualizing Knowledge64Property-Oriented Material Design Based on a Data-Driven Machine Learning Technique89Machine learning in materials genome initiative: A review231Polymer Nanocomposite Data: Curation, Frameworks, Access, and Potential for Discovery and Design49A database of battery materials auto-generated using ChemDataExtractor162Similarity of Precursors in Solid-State Synthesis as Text-Mined from Scientific Literature85Relation/Entity-Centric Reading Comprehension0Predictive Synthesis of Quantum Materials by Probabilistic Reinforcement Learning0Data-driven materials research enabled by natural language processing and information extraction302Perovskite-inspired materials for photovoltaics and beyond—from design to devices206Prospects for lithium-ion batteries and beyond—a 2030 vision959Polymer informatics: Current status and critical next steps272Analyzing Research Trends in Inorganic Materials Literature Using NLP8Automated Mining of Leaderboards for Empirical AI Research19SuperMat: construction of a linked annotated dataset from superconductors-related publications22The Impact of Domain-Specific Pre-Training on Named Entity Recognition Tasks in Materials Science33Toward autonomous design and synthesis of novel inorganic materials159Predicting the Outcomes of Material Syntheses with Deep Learning13Text mining of hypereutectic Al-Si alloys literature based on active learning9Artificial intelligence and machine learning in glass science and technology: 21 challenges for the 21 st century55Opportunities and challenges of text mining in materials research180Reducing Time to Discovery: Materials and Molecular Modeling, Imaging, Informatics, and Integration65MatScIE: An automated tool for the generation of databases of methods and parameters used in the computational materials science literature14Synthetic approaches for thin-film halide double perovskites38Advances in scientific literature mining for interpreting materials characterization9Prediction of solar‐chargeable battery materials: A text‐mining and first‐principles investigation17Observing and Modeling the Sequential Pairwise Reactions that Drive Solid‐State Ceramic Synthesis89Sentence, Phrase, and Triple Annotations to Build a Knowledge Graph of Natural Language Processing Contributions—A Trial Dataset8Best practices in machine learning for chemistry505Rational Solid-State Synthesis Routes for Inorganic Materials115Copolymer Informatics with Multitask Deep Neural Networks101Annotation and Classification of Graphs of Property Values Reported in Material Science Literature0Predictive Synthesis54Autonomous reinforcement learning agent for chemical vapor deposition synthesis of quantum materials45In Situ Mechanistic Studies of Two Divergent Synthesis Routes Forming the Heteroanionic BiOCuSe27IP Analytics and Machine Learning Applied to Create Process Visualization Graphs for Chemical Utility Patents4Extracting processing and testing parameters from materials science literature for improved property prediction of glasses35Synthesis‐condition recommender system discovers novel inorganic oxides2Artificial Intelligence Applied to Battery Research: Hype or Reality?503Extrapolative Bayesian Optimization with Gaussian Process and Neural Network Ensemble Surrogate Models44Toward Predictive Chemical Deformulation Enabled by Deep Generative Neural Networks7Panoramic (in beam) studies of materials synthesis1Artificial Intelligence for Autonomous Molecular Design: A Perspective49Machine-Guided Polymer Knowledge Extraction Using Natural Language Processing: The Example of Named Entity Normalization28Dataset of Solution-based Inorganic Materials Synthesis Recipes Extracted from the Scientific Literature2Annotation and Classification of Graphs of Property Values Reported in Material Science Literature0BatteryDataExtractor: battery-aware text-mining software embedded with BERT models43DiSCoVeR: a materials discovery screening tool for high performance, unique chemical compositions28Easy Semantification of Bioassays1Extracting and Analyzing Inorganic Material Synthesis Procedures in the Literature10Impact of processing conditions on the film formation of lead-free halide double perovskite Cs 2 AgBiBr 637Informatics Driven Materials Innovation for a Regenerative Economy: Harnessing NLP for Safer Chemistry in Manufacturing of Solar Cells6Machine learning-driven advanced development of carbon-based luminescent nanomaterials23Measurement Extraction with Natural Language Processing: A Review14New challenges in oxygen reduction catalysis: a consortium retrospective to inform future research53Perspectives on manufacturing simulations of Li-S battery cathodes13Synthesis of flexible Co nanowires from bulk precursors2Machine Learning and Natural Language Processing Enable a Data-Oriented Experimental Design Approach for Producing Biochar and Hydrochar from Biomass67Machine learning in nuclear materials research125Designing a multilayer film via machine learning of scientific literature8Sentence Boundary Extraction from Scientific Literature of Electric Double Layer Capacitor Domain: Tools and Techniques16Review of computational approaches to predict the thermodynamic stability of inorganic solids196Mining Insights on Metal–Organic Framework Synthesis from Scientific Literature Texts72Inverse Material Search and Synthesis Verification by Hand Drawings via Transfer Learning and Contour Detection6Extensible Structure-Informed Prediction of Formation Energy with improved accuracy and usability employing neural networks36Machine learning assisted synthesis of lithium-ion batteries cathode materials102Text Mining for Energy Materials3Quantifying the advantage of domain-specific pre-training on named entity recognition tasks in materials science163Recent advances and applications of deep learning methods in materials science1161Cost Profile of Membranes That Use Polymers of Intrinsic Microporosity (PIMs)16Auto-generated database of semiconductor band gaps using ChemDataExtractor49MatSciBERT: A materials domain language model for text mining and information extraction342Dataset of solution-based inorganic materials synthesis procedures extracted from the scientific literature83Text-mined dataset of gold nanoparticle synthesis procedures, morphologies, and size entities56Predicting the formation and stability of oxide perovskites by extracting underlying mechanisms using machine learning24Auto-generating databases of Yield Strength and Grain Size using ChemDataExtractor43Unleashing the Power of Knowledge Extraction from Scientific Literature in Catalysis27Understanding the Fluorination of Disordered Rocksalt Cathodes through Rational Exploration of Synthesis Pathways43Machine-Learning Rationalization and Prediction of Solid-State Synthesis Conditions79Uncertainty Informed Screening for Safer Solvents used in the Synthesis of Perovskite Based Solar Cells via Machine Learning1Conventional and less conventional solution-based synthesis of battery materials: Cathodes, anodes and electrolytes1Optical emissivity dataset of multi-material heterogeneous designs generated with automated figure extraction11Challenges, Opportunities, and Prospects in Metal Halide Perovskites from Theoretical and Machine Learning Perspectives53Recommender system for discovery of inorganic compounds11Building Chemical Property Models for Energetic Materials from Small Datasets Using a Transfer Learning Approach42Hierarchical machine learning based structure–property correlations for as–cast complex concentrated alloys16Big Data in a Nano World: A Review on Computational, Data-Driven Design of Nanomaterials Structures, Properties, and Synthesis83Graph neural networks for materials science and chemistry860Automatic extraction of materials and properties from superconductors scientific literature23Development of a baseline model for MAX/MXene synthesis recipes extraction via pre-trained model with domain knowledge5A review on the application of molecular descriptors and machine learning in polymer design108A Text Mining Pipeline for Mining the Quantum Cascade Laser Properties3Extracting structured seed-mediated gold nanorod growth procedures from scientific text with LLMs26Investigating the Impact of Syntax-Enriched Transformers on Quantity Extraction in Scientific Texts6Large Language Models as Master Key: Unlocking the Secrets of Materials Science20Material Named Entity Recognition (MNER) for Knowledge-Driven Materials Using Deep Learning Approach3MatNexus: A Comprehensive Text Mining and Analysis Suite for Materials Discovery0Retrosynthesis from transforms to predictive sustainable chemistry and nanotechnology: a brief tutorial review19Transcription between human-readable synthetic descriptions and machine-executable instructions: an application of the latest pre-training technology3Unveiling the synthesis patterns of nanomaterials: a text mining and meta-analysis approach with ZIF-8 as a case study9Chemical reaction networks and opportunities for machine learning141Knowledge-integrated machine learning for materials: lessons from gameplaying and robotics137Interpretable Machine Learning Enabled Inorganic Reaction Classification and Synthesis Condition Prediction41Direct Mechanochemical Synthesis, Phase Stability, and Electrochemical Performance of α-NaFeO 219Self-Driving Laboratory for Polymer Electronics86A general-purpose material property data extraction pipeline from large polymer corpora using natural language processing149The role of machine learning in carbon neutrality: Catalyst property prediction, design, and synthesis for carbon dioxide reduction62Fatigue database of additively manufactured alloys39The promise and pitfalls of AI for molecular and materials synthesis22Modernist materials synthesis: Finding thermodynamic shortcuts with hyperdimensional chemistry19Functional Material Systems Enabled by Automated Data Extraction and Machine Learning33Natural Language Processing Techniques for Advancing Materials Discovery: A Short Review18Precursor recommendation for inorganic synthesis by machine learning materials similarity from scientific literature65Machine learning assisted phase and size-controlled synthesis of iron oxide particles36ChemNLP: A Natural Language-Processing-Based Library for Materials Chemistry Text Data46Predicting the synthesizability of crystalline inorganic materials from the data of known material compositions38An automated materials and processes identification tool for material informatics using deep learning approach12Artificial Intelligence for Learning Material Synthesis Processes of Thermoelectric Materials21Data driven design of compositionally complex energy materials13Extracting the Synthetic Route of Pd-Based Catalysts in Methanol Steam Reforming from the Scientific Literature7Assessing Thermodynamic Selectivity of Solid-State Reactions for the Predictive Synthesis of Inorganic Materials41VOLTA: a tool for battery screening bridging the gap between virtual electrode materials and practical applications0Artificial Intelligence for Surface‐Enhanced Raman Spectroscopy149Combining text mining, in situ characterization, and ab initio calculations to rationalize BiFeO3 crystallization pathways8MatNexus: A Comprehensive Text Mining and Analysis Suite for Materials Discover0Opinion Mining by Convolutional Neural Networks for Maximizing Discoverability of Nanomaterials8Semi-automatic staging area for high-quality structured data extraction from scientific literature6An autonomous laboratory for the accelerated synthesis of inorganic materials1000Language models and protocol standardization guidelines for accelerating synthesis planning in heterogeneous catalysis68GPT-Assisted Learning of Structure–Property Relationships by Graph Neural Networks: Application to Rare-Earth-Doped Phosphors16Predicting synthesis recipes of inorganic crystal materials using elementwise template formulation15MatGD: Materials Graph Digitizer9Selective Synthesis of Defect-Rich LaMnO3 by Low-Temperature Anion Cometathesis7Text Mining the Literature to Inform Experiments and Rationalize Impurity Phase Formation for BiFeO312Automated electrosynthesis reaction mining with multimodal large language models (MLLMs)23Bias in Materials Datasets without Datasets: A Conceptual Account of How Bias Enters Before Any Modeling1Flexible, model-agnostic method for materials data extraction from text using general purpose language models42Harnessing GPT-3.5 for text parsing in solid-state synthesis – case study of ternary chalcogenides26Insights into the Development of Electrocatalysts Based on Information Extracted from Literatures Using Natural Language Processing1Selective formation of metastable polymorphs in solid-state synthesis36Self-assembly of peptides: The acceleration by molecular dynamics simulations and machine learning61Semantic knowledge graph as a companion for catalyst recommendation6Accelerating materials language processing with large language models78

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