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RESEARCH PAPER · Applied Physics Reviews · 2020

Data-driven materials research enabled by natural language processing and information extraction

Elsa Olivetti, Jacqueline M. Cole, Edward Kim, Olga Kononova, Gerbrand Ceder, T. Yong-Jin Han, Anna M. Hiszpanski

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Data-driven materials research enabled by natural language processing and information extractionOriginalImportance of multimodal characterization and influence of residual Li 2 S impurity in amorphous Li 3 PS 4 inorganic electrolytes33SuperMat: construction of a linked annotated dataset from superconductors-related publications22The Impact of Domain-Specific Pre-Training on Named Entity Recognition Tasks in Materials Science33Opportunities and challenges of text mining in materials research180Process Discovery through Assimilation of Complex Biogeochemical Datasets0Prediction of solar‐chargeable battery materials: A text‐mining and first‐principles investigation17Predicting inorganic dimensionality in templated metal oxides8Accelerated Atomistic Modeling of Solid-State Battery Materials With Machine Learning70An automated domain-independent text reading, interpreting and extracting approach for reviewing the scientific literature0MOF Synthesis Prediction Enabled by Automatic Data Mining and Machine Learning15Challenges and Advances in Information Extraction from Scientific Literature: a Review67Words to Matter: De novo Architected Materials Design Using Transformer Neural Networks40Opportunities and challenges for engineering construction materials as carbon sinks19Process intensification 4.0: A new approach for attaining new, sustainable and circular processes enabled by machine learning76Realizing the data-driven, computational discovery of metal-organic framework catalysts61XERUS: An open-source tool for quick XRD phase identification and refinement automation15Machines for Materials and Materials for Machines: Metal-Insulator Transitions and Artificial Intelligence6A Scheduled Mask Method for TextVQA0BatteryDataExtractor: battery-aware text-mining software embedded with BERT models43Guidance for Materials 4.0 to interact with a digital twin16Informatics Driven Materials Innovation for a Regenerative Economy: Harnessing NLP for Safer Chemistry in Manufacturing of Solar Cells6Lifelong Pretraining: Continually Adapting Language Models to Emerging Corpora26Lifelong Pretraining: Continually Adapting Language Models to Emerging Corpora27SynKB: Semantic Search for Synthetic Procedures8ULSA: unified language of synthesis actions for the representation of inorganic synthesis protocols28Machine Learning and Natural Language Processing Enable a Data-Oriented Experimental Design Approach for Producing Biochar and Hydrochar from Biomass67Machine learning in nuclear materials research125Automated pipeline for superalloy data by text mining83Sentence Boundary Extraction from Scientific Literature of Electric Double Layer Capacitor Domain: Tools and Techniques16MOF Synthesis Prediction Enabled by Automatic Data Mining and Machine Learning**237Vorhersage der MOF‐Synthese durch automatisches Data‐Mining und maschinelles Lernen**4Universal machine learning framework for defect predictions in zinc blende semiconductors56A review of the recent progress in battery informatics178Artificial intelligence to bring nanomedicine to life189Data-driven modeling of process, structure and property in additive manufacturing: A review and future directions120Automating Materials Exploration with a Semantic Knowledge Graph for Li‐Ion Battery Cathodes37Aluminum alloy compositions and properties extracted from a corpus of scientific manuscripts and US patents25Interpretable Machine Learning for Investigating Photoelectrochemical Properties of Cosensitizer-Based CH3NH3PbI3/TiO2 Films in Water11Accelerated discovery of porous materials for carbon capture by machine learning: A review19Quantifying the advantage of domain-specific pre-training on named entity recognition tasks in materials science163Recent advances and applications of deep learning methods in materials science1161Opportunities for machine learning to accelerate halide-perovskite commercialization and scale-up35Auto-generated database of semiconductor band gaps using ChemDataExtractor49MatSciBERT: A materials domain language model for text mining and information extraction342BatteryBERT: A Pretrained Language Model for Battery Database Enhancement135Challenges in Information-Mining the Materials Literature: A Case Study and Perspective21Text-mined dataset of gold nanoparticle synthesis procedures, morphologies, and size entities56Unleashing the Power of Knowledge Extraction from Scientific Literature in Catalysis27Deep Learning for Materials Recognition from FTIR Images0Machine Learning in Tissue Engineering73Uncertainty Informed Screening for Safer Solvents used in the Synthesis of Perovskite Based Solar Cells via Machine Learning1Band gap information extraction from materials science literature – a pilot study2Image-based machine learning for materials science54Clinical XLNet-based End-to-End Knowledge Discovery on Clinical Text Data using Natural Language Processing0Superconductivity information extraction from the literature: A new corpus and its evaluations4Text Summarization towards Scientific Information Extraction5Challenges, Opportunities, and Prospects in Metal Halide Perovskites from Theoretical and Machine Learning Perspectives53On scientific understanding with artificial intelligence372Modeling materials under coupled extremes: Enabling better predictions of performance4Toward autonomous laboratories: Convergence of artificial intelligence and experimental automation118Data driven knowledge summarization of friction stir welded magnesium alloys literature by using natural language processing algorithms8Environmentally-Assisted Fatigue at Small Scales1Clinical XLNet-based End-to-End Knowledge Discovery on Clinical Text Data using Natural Language Processing014 examples of how LLMs can transform materials science and chemistry: a reflection on a large language model hackathon214A high-quality dataset construction method for text mining in materials science20ChemDataWriter: a transformer-based toolkit for auto-generating books that summarise research4Data-driven design of electrocatalysts: principle, progress, and perspective46Extracting structured seed-mediated gold nanorod growth procedures from scientific text with LLMs26Failure Case Reporting in Materials Informatics — What Is Documented and What Is Silenced0HoneyBee: Progressive Instruction Finetuning of Large Language Models for Materials Science18Large Language Models as Master Key: Unlocking the Secrets of Materials Science20Made of Steel? Learning Plausible Materials for Components in the Vehicle Repair Domain1MatSci-NLP: Evaluating Scientific Language Models on Materials Science Language Tasks Using Text-to-Schema Modeling32Perceptions of the use of IsiZulu Termbank Technology at University of KwaZulu-Natal.0Realizing the cooking recipe of materials synthesis through large language models14Knowledge-integrated machine learning for materials: lessons from gameplaying and robotics137Interpretable Machine Learning Enabled Inorganic Reaction Classification and Synthesis Condition Prediction41Deep language models for interpretative and predictive materials science78Scientific novelty beyond the experiment63Machine Learning for Perovskite Solar Cells and Component Materials: Key Technologies and Prospects170Rational design of high-entropy ceramics based on machine learning – A critical review52Data-driven thermal and percolation analyses of 3D composite structures with interface resistance20High‐Entropy Perovskites for Energy Conversion and Storage: Design, Synthesis, and Potential Applications85Extracting Accurate Materials Data from Research Papers with Conversational Language Models and Prompt Engineering10AI-Based Knowledge Extraction from the Bioprinting Literature for Identifying Technology Trends3High-throughput calculation and machine learning of two-dimensional halide perovskite materials: Formation energy and band gap35Common Elements Approaches to Implementation Research and Practice: Methods and Integration with Intervention Science36Accelerating the design of compositionally complex materials via physics-informed artificial intelligence110Probe microscopy is all you need *20Domain knowledge discovery from abstracts of scientific literature on Nickel-based single crystal superalloys29Automatic knowledge acquisition from superconductivity information in literature0Testing open-source tools for optical chemical structure recognition on novel nitrogen-rich energetic materials2Ab-initio computation of structural, elastic, mechanical and optical properties of Cs2ScAgI6 double perovskite semiconductor compound10Methods, progresses, and opportunities of materials informatics72First-principles, machine learning and symbolic regression modelling for organic molecule adsorption on two-dimensional CaO surface12Functional Material Systems Enabled by Automated Data Extraction and Machine Learning33Modeling ionic conductivity and activation energy in garnet-structured solid electrolytes: The role of composition, grain boundaries and processing16Natural Language Processing in Higher Education10FFMDFPA: A FAIRification Framework for Materials Data with No-Code Flexible Semi-Structured Parser and Application Programming Interfaces5Enhancing corrosion-resistant alloy design through natural language processing and deep learning77Predicting Ionic Conductivity in Thin Films of Garnet Electrolytes Using Machine Learning13ChemNLP: A Natural Language-Processing-Based Library for Materials Chemistry Text Data46The ScholarNet and Artificial Intelligence (AI) Supervisor in Material Science Research15An automated materials and processes identification tool for material informatics using deep learning approach12Biomaterials text mining: A hands-on comparative study of methods on polydioxanone biocompatibility9The Significance of Text Mining in Research: A Comprehensive Review0Data-Driven Imputation of Miscibility of Aqueous Solutions via Graph-Regularized Logistic Matrix Factorization6Shared metadata for data-centric materials science63Development of an NLP-Based Automatic Data Retrieval Model1Artificial Intelligence for Learning Material Synthesis Processes of Thermoelectric Materials21A machine learning approach for accelerated design of magnesium alloys. Part A: Alloy data and property space57Natural language processing for knowledge discovery and information extraction from energetics corpora7Forecasting the future of artificial intelligence with machine learning-based link prediction in an exponentially growing knowledge network91Next Generation Noble Metal‐Engineered Catalysts: From Structure Evolution to Structure‐Reactivity Correlation in Water Splitting51Machine learning-based evaluation of functional characteristics of Li-rich layered oxide cathode materials using the data of XPS and XRD spectra16Research activities in the dielectric ceramics: information from data mining in literature0Advances of machine learning in materials science: Ideas and techniques105Language models and protocol standardization guidelines for accelerating synthesis planning in heterogeneous catalysis68Quantitative Topic Analysis of Materials Science Literature Using Natural Language Processing24First-principles and machine learning investigation on A4BX6 halide perovskites4A Prompt Engineering Approach for Structured Data Extraction from Unstructured Text Using Conversational LLMs16NLP meets Materials Science: Quantifying the presentation of materials data in scientific literature1Label-Free Data Mining of Scientific Literature by Unsupervised Syntactic Distance Analysis13A Study of Key Elements of Computer Linguistics Extraction Based on Artificial Intelligence NLP0Automated extraction of synthesis parameters of pulsed laser-deposited materials from scientific literature8Constructing an Evaluation Framework for English Teaching in Higher Education: Integrating Neural Networks and Natural Language Processing0Data Augmentation Method Utilizing Template Sentences for Variable Definition Extraction0Development and application of Few-shot learning methods in materials science under data scarcity47Flexible, model-agnostic method for materials data extraction from text using general purpose language models42Insights into the Development of Electrocatalysts Based on Information Extracted from Literatures Using Natural Language Processing1Natural Language Processing7Novelty Detection in the Design of Synthesis of Energy Storage Materials: a Case Study of Garnet-Structured Solid Electrolytes1Accuracy improvement of the load forecasting in the district heating system by the informer-based framework with the optimal step size selection38ChatGPT in the Material Design: Selected Case Studies to Assess the Potential of ChatGPT36Enhancing quality control in bioprinting through machine learning36Fuzzy information recognition and translation processing in English interpretation based on a generalized maximum likelihood ratio algorithm8The impact of artificial intelligence on scientific practices: an emergent area of research for science education89Accelerating materials language processing with large language models78Extracting accurate materials data from research papers with conversational language models and prompt engineering354X-ray diffraction under grazing incidence conditions62NLP meets materials science: Quantifying the presentation of materials data in literature12CO 2 Reduction beyond Copper-Based Catalysts: A Natural Language Processing Review from the Scientific Literature11Novelty detection in the design of synthesis of garnet-structured solid electrolytes6Creation of a structured solar cell material dataset and performance prediction using large language models28Optimising Human-Machine Collaboration for Efficient High-Precision Information Extraction from Text Documents11Machine Learning Aided Design and Optimization of Thermal Metamaterials195Oxide ceramics of A2M3O12 family with negative and close-to-zero thermal expansion coefficients: Machine learning-based modeling of functional characteristics12A document-level information extraction pipeline for layered cathode materials for sodium-ion batteries16Embracing data science in catalysis research117Recent advances in artificial intelligence boosting materials design for electrochemical energy storage124

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  1. Importance of multimodal characterization and influence of residual Li 2 S impurity in amorphous Li 3 PS 4 inorganic electrolytes

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  2. SuperMat: construction of a linked annotated dataset from superconductors-related publications

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