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RESEARCH PAPER · iScience · 2021

Opportunities and challenges of text mining in materials research

Olga Kononova, Tanjin He, Haoyan Huo, Amalie Trewartha, Elsa Olivetti, Gerbrand Ceder

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Opportunities and challenges of text mining in materials researchOriginalAnalyzing Research Trends in Inorganic Materials Literature Using NLP8The Impact of Domain-Specific Pre-Training on Named Entity Recognition Tasks in Materials Science33Toward autonomous design and synthesis of novel inorganic materials159Accelerated Atomistic Modeling of Solid-State Battery Materials With Machine Learning70Computational Discovery of Transition-metal Complexes: From High-throughput Screening to Machine Learning354IP Analytics and Machine Learning Applied to Create Process Visualization Graphs for Chemical Utility Patents4When Cyclodextrins Met Data Science: Unveiling Their Pharmaceutical Applications through Network Science and Text-Mining24Machine‐Learning Microstructure for Inverse Material Design117Dataset of Solution-based Inorganic Materials Synthesis Recipes Extracted from the Scientific Literature2Audacity of huge: overcoming challenges of data scarcity and data quality for machine learning in computational materials discovery98Informatics 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 Review14Perspectives on manufacturing simulations of Li-S battery cathodes13Topic Modelling for Research Perception: Techniques, Processes and a Case Study1ULSA: unified language of synthesis actions for the representation of inorganic synthesis protocols28Smart Materials Prediction: Applying Machine Learning to Lithium Solid-State Electrolyte33Universal machine learning framework for defect predictions in zinc blende semiconductors56A review of the recent progress in battery informatics178Machine Learning for the Discovery, Design, and Engineering of Materials66Automating Materials Exploration with a Semantic Knowledge Graph for Li‐Ion Battery Cathodes37Quantifying the advantage of domain-specific pre-training on named entity recognition tasks in materials science163Recent advances and applications of deep learning methods in materials science1161BatteryBERT: A Pretrained Language Model for Battery Database Enhancement135Automatic Risks Detection and Comparison Techniques for General Conditions of Technical Documents in Purchasing Order1Challenges in Information-Mining the Materials Literature: A Case Study and Perspective21Dataset of solution-based inorganic materials synthesis procedures extracted from the scientific literature83Text-mined dataset of gold nanoparticle synthesis procedures, morphologies, and size entities56Unleashing the Power of Knowledge Extraction from Scientific Literature in Catalysis27Materials Discovery With Machine Learning and Knowledge Discovery40Machine-Learning Rationalization and Prediction of Solid-State Synthesis Conditions79An AI-Based Automatic Risks Detection Solution for Plant Owner’s Technical Requirements in Equipment Purchase Order5Band gap information extraction from materials science literature – a pilot study2Artificial intelligence in computational materials science8DATa: Domain Adaptation-aided deep Table detection using visual–lexical representations2Challenges, Opportunities, and Prospects in Metal Halide Perovskites from Theoretical and Machine Learning Perspectives53Computational modeling to assist in the discovery of supramolecular materials20Reconstructing orientation data from the images of IPF maps and ODF sections extracted from the literature: A data-collection method for machine learning9Toward autonomous laboratories: Convergence of artificial intelligence and experimental automation118Table understanding: Problem overview16SsciBERT: a pre-trained language model for social science texts41A high-quality dataset construction method for text mining in materials science20Deep learning of electrochemical CO 2 conversion literature reveals research trends and directions18Extracting 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 Science18Machine learning in energy chemistry: introduction, challenges and perspectives31MatSci-NLP: Evaluating Scientific Language Models on Materials Science Language Tasks Using Text-to-Schema Modeling32Text Visualization of Entire Corpus Through Single Document Input Tools0Unveiling the synthesis patterns of nanomaterials: a text mining and meta-analysis approach with ZIF-8 as a case study9Porous Molecular Materials1Interpretable Machine Learning Enabled Inorganic Reaction Classification and Synthesis Condition Prediction41LIBAC: An Annotated Corpus for Automated “Reading” of the Lithium-Ion Battery Research Literature10Extracting Accurate Materials Data from Research Papers with Conversational Language Models and Prompt Engineering10Small data machine learning in materials science866Domain knowledge discovery from abstracts of scientific literature on Nickel-based single crystal superalloys29Data quantity governance for machine learning in materials science228Fatigue database of additively manufactured alloys39Functional Material Systems Enabled by Automated Data Extraction and Machine Learning33Natural Language Processing Techniques for Advancing Materials Discovery: A Short Review18CKineticsDB─An Extensible and FAIR Data Management Framework and Datahub for Multiscale Modeling in Heterogeneous Catalysis5Using R to develop a corpus of full-text journal articles0ChemNLP: A Natural Language-Processing-Based Library for Materials Chemistry Text Data46Design principles for NASICON super-ionic conductors147Data driven design of compositionally complex energy materials13Questify: Your Intelligent Web Page Assistant for Quick Answers0Machine Learning Models for Classification of Sensitive Financial Documents6Extracting the Synthetic Route of Pd-Based Catalysts in Methanol Steam Reforming from the Scientific Literature7Reconstructing Materials Tetrahedron: Challenges in Materials Information Extraction0Artificial Intelligence for Surface‐Enhanced Raman Spectroscopy149Combining text mining, in situ characterization, and ab initio calculations to rationalize BiFeO3 crystallization pathways8Research activities in the dielectric ceramics: information from data mining in literature0Patterns Lead the Way to Far-from-Equilibrium Materials16Language models and protocol standardization guidelines for accelerating synthesis planning in heterogeneous catalysis68Quantitative Topic Analysis of Materials Science Literature Using Natural Language Processing24GPT-Assisted Learning of Structure–Property Relationships by Graph Neural Networks: Application to Rare-Earth-Doped Phosphors16Knowledge-Based Intelligent Text Simplification for Biological Relation Extraction5Text Mining the Literature to Inform Experiments and Rationalize Impurity Phase Formation for BiFeO312Automated electrosynthesis reaction mining with multimodal large language models (MLLMs)23Automated extraction of synthesis parameters of pulsed laser-deposited materials from scientific literature8Chemistry in a graph: modern insights into commercial organic synthesis planning2Flexible, 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 chalcogenides26Reconstructing the materials tetrahedron: challenges in materials information extraction23Understanding Hot Injection Quantum Dot Synthesis Outcomes Using Automated High-Throughput Experiment Platforms and Machine Learning24Accelerating materials language processing with large language models78MatNexus: A comprehensive text mining and analysis suite for materials discovery9Extracting accurate materials data from research papers with conversational language models and prompt engineering354CO 2 Reduction beyond Copper-Based Catalysts: A Natural Language Processing Review from the Scientific Literature11Crystal Structure Assignment for Unknown Compounds from X-ray Diffraction Patterns with Deep Learning31Effect of Al–5Ti–1B–La intermediate alloy on microstructure and mechanical properties of A356.2 aluminum alloy15Deep learning of experimental electrochemistry for battery cathodes across diverse compositions49A document-level information extraction pipeline for layered cathode materials for sodium-ion batteries16Named entity recognition in the perovskite field based on convolutional neural networks and MatBERT8Multiscale modeling for enhanced battery health analysis: Pathways to longevity45Evolution of Model-Based Materials Definitions5Applying Regular Expressions in Text Mining to Extract Information from Medical Expert Reports1Tackling Structured Knowledge Extraction from Polymer Nanocomposite Literature as an NER/RE Task with seq2seq4Predicting Emission Wavelengths in Benzobisoxazole-Based OLEDs with Gradient Boosted Ensemble Models3Versatile Deep Learning Pipeline for Transferable Chemical Data Extraction7Dielectric Ceramics Database Automatically Constructed by Data Mining in the Literature3PROCESSAMENTO DE LINGUAGEM NATURAL PARA RECONHECIMENTO DE ENTIDADES NOMEADAS EXTRAÍDAS DE CORPUS0MPNTEXT: An Interactive Platform for Automatically Extracting Metal-Polyphenol Networks and Their Applications from Scientific Literature3How Does a Generative Large Language Model Perform on Domain-Specific Information Extraction?─A Comparison between GPT-4 and a Rule-Based Method on Band Gap Extraction15Chemoinformatics for corrosion science: Data‐driven modeling of corrosion inhibition by organic molecules5Assessing Sustainable Development Goal Alignment in Local Food Systems: Insights from an Automated Text Analysis of the Organizational Literature0Construction and application of materials database under data-driven research paradigm3Domain-adaptive entity recognition: unveiling the potential of CSER in cybersecurity and beyond1Assessment of fine-tuned large language models for real-world chemistry and material science applications52Machine learning materials properties with accurate predictions, uncertainty estimates, domain guidance, and persistent online accessibility17Evolving research themes in six selected wood science journals: insights from text mining and latent dirichlet allocation6AI-Enhanced Techniques for Extracting Structured Data from Unstructured Public Procurement Documents1Named Entity Recognition from Materials Science Patent Documents Using Clue Word Tags0Machine Learning-Aided Inverse Design and Discovery of Novel Polymeric Materials for Membrane Separation95The amorphous state as a frontier in computational materials design74Data extraction from polymer literature using large language models77Deep reinforcement learning for inverse inorganic materials design59From text to insight: large language models for chemical data extraction142A global analysis of the rise, reign, and retreat of topics in research toward sustainable platform chemicals1Reconstructing Global Environmental Risk Narratives Using Large-Scale Text Mining of Scientific Dental Literature0Solid-state synthesizability predictions using positive-unlabeled learning from human-curated literature data8A Holistic Data-Driven Approach to Synthesis Predictions of Colloidal Nanocrystal Shapes14Dynamic in-context learning with conversational models for data extraction and materials property prediction1Local large language model‐assisted literature mining for on‐surface reactions13Using experimental data in computationally guided rational design of inorganic materials with machine learning7Coevolution of large language models with physical models boosts advanced battery research2Rapid Adaptation of Chemical Named Entity Recognition Using Few-Shot Learning and LLM Distillation15From pages to patterns: Towards extracting catalytic knowledge from structure and text for transition-metal complexes and metal-organic frameworks6Language models for materials discovery and sustainability: Progress, challenges, and opportunities26Recent advances in stimuli-responsive framework materials: Understanding their response and searching for materials with targeted behavior20Extracting Material Property Measurements from Scientific Literature with Limited Annotations5Building an end-to-end battery recipe knowledge base via transformer-based text mining10A knowledge acquisition automatizing framework from literature exemplified by Na+ activation energy prediction of NASICON solid-state electrolyte13127Chapter 6 Exploring the relationship between structure and properties in polymer blends using deep learning techniques0Artificial Intelligence‐Driven Development in Rechargeable Battery Materials: Progress, Challenges, and Future Perspectives53Artificial Intelligence for Materials Discovery, Development, and Optimization171Use of Large Language Models for Extracting and Analyzing Data from Heterogeneous Catalysis Literature18Chat-rgie: precision extraction of rice germplasm data using large language models and prompt engineering1A review on knowledge and information extraction from PDF documents and storage approaches5Specialized modeling, database, and AI for Li-ion and Na-ion battery materials1Text Mining for Process–Structure–Properties Relationships in Metals1Assessing the Performance of LLMs in Multimodal Information Extraction for Biological Research: A Case Study on LLPS0Community Relations Management (CoRM) Analytics: A Text Analytics Approach to Elevate Community Happiness0AI-Driven Literature Mining for Intelligent Synthesis Design0Machine learning pipelines for the design of solid-state electrolytes30MatSciES: Automated Knowledge Extraction and Summarization from Materials Science Literature with Large Language Models2Language Models Enable Data-Augmented Synthesis Planning for Inorganic Materials8Small Language Models With Sentence‐Level Corpus Offer Significant Potential for the Geoscience Community0A Data-Driven Semantic- and Knowledge-Guided Strategy for High-Entropy Design in Vanadium Phosphate Cathodes0Journal research data policies in materials science0

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