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RESEARCH PAPER · Journal of the American Chemical Society · 2024

Large Language Models for Inorganic Synthesis Predictions

Seong-Min Kim, Yousung Jung, Joshua Schrier

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Large Language Models for Inorganic Synthesis PredictionsOriginalOptical materials discovery and design with federated databases and machine learning9A critical reflection on attempts to machine-learn materials synthesis insights from text-mined literature recipes16Application of Self-Evolving AI Agents in Chemical Research: A Novel Intelligent Assistance System2From text to insight: large language models for chemical data extraction142Large Language Model for Automating the Analysis of Cryoprotectants5AI agents in chemical research: GVIM – an intelligent research assistant system13Design of CO 2 -philic molecular units with large language models5Harnessing Large Language Models to Collect and Analyze Metal–Organic Framework Property Data Set102Large language models for reticular chemistry133Explainable Synthesizability Prediction of Inorganic Crystal Polymorphs Using Large Language Models28Explainable Synthesizability Prediction of Inorganic Crystal Polymorphs Using Large Language Models1How to accelerate the inorganic materials synthesis: from computational guidelines to data-driven method?9A Multiagent-Driven Robotic AI Chemist Enabling Autonomous Chemical Research On Demand167Two‐Dimensional Covalent Organic Frameworks in Organic Electronics58Two‐Dimensional Covalent Organic Frameworks in Organic Electronics3Developing ChemDFM as a large language foundation model for chemistry47Leveraging Prompt Engineering in Large Language Models for Accelerating Chemical Research29From Manual Training to Domain-Specific Adaptation through Constrained Prompt Engineering and Self-Training0Intelligent Systems for Inorganic Nanomaterial Synthesis38Language models for materials discovery and sustainability: Progress, challenges, and opportunities26Empowering Generalist Material Intelligence with Large Language Models29Copper only SOD repeat proteins likely act as an extracellular superoxide dismutase in oyster antioxidant defense10Accurate prediction of synthesizability and precursors of 3D crystal structures via large language models33Large language models for batteries31Materials informatics: A review of AI and machine learning tools, platforms, data repositories, and applications to architectured porous materials41Annotated textual dataset PV600 of perovskite bandgaps for information extraction from literature6High-Performance Polyimide Design: Machine Learning–Accelerated Multiobjective Optimization6Synthesis-Aware Materials Redesign via Large Language Models12Data-driven framework for accelerated design of cerium alloy surrogates for uranium hydriding behavior0Uncovering the Multifunctional Roles of Metal‐Organic Frameworks in Protecting Lithium Metal Anodes Assisted by Large Language Models2Towards Fully-Automated Materials Discovery via Large-Scale Synthesis Dataset and Expert-Level LLM-as-a-Judge1A survey on large language models in biology and chemistry8Exploring materials data through collaboration: 2024 KRICT ChemDX Hackathon0Language Models Enable Data-Augmented Synthesis Planning for Inorganic Materials8Large Language Models (LLMs) for Materials Design1430 years of AI for electrocatalysis: Where we are and what’s next?12Data-driven exploration of AB 2 X 4 (X = O, S, Se, Te) spinel chemical space0Digitalisation of inorganic chemistry with LLMs1Large language models for porous materials: from text mining to autonomous laboratory6Leveraging large language models (LLMs) to enhance student inquiry in a nanochemistry teaching laboratory: a Fenton-like oxidation using recyclable ferrite nanoparticle (NP) catalysts0Bridging theory and experiment in materials discovery: Machine-learning-assisted prediction of synthesizable structures3Knowledge-driven autonomous materials research via collaborative multi-agent and robotic system11Augmenting Large Language Models for Automated Discovery of F-Element Extractants8DiffSyn: a generative diffusion approach to materials synthesis planning8General-Purpose Models for the Chemical Sciences: LLMs and Beyond6AI-assisted quantitative deciphering of molecular configuration and steric effects for high-performance zinc battery electrolytes4AI‐Guided Co‐Optimization of Advanced Field‐Effect Transistors: Bridging Material, Device, and Fabrication Design0Boosting Computational Catalysis and Chemical Reactivity with Artificial Intelligence12Use of Machine Learning and Large Language Models in Chemical Information Extraction0MDCrow: automating molecular dynamics workflows with large language models23Can You Help ChatGPT Get an “A” in Organic Chemistry? Teaching Effective Prompting of Large Language Models for Reaction Prediction3Structured Multimaterial Fibers Enabling Intelligent Robots1The rise of generative AI for metal-organic framework design and synthesis21Sustainable Materials Design With Multi‐Modal Artificial Intelligence1A multimodal large language model for materials science22Closed-loop workflow of high-entropy materials discovery: efficient and accurate synthesizability prediction via domain-specific local LLMs1Multi-agent artificial intelligence designs novel catalysts for ultrafast water purification4Triboinformatics: Machine Learning, Artificial Intelligence, and Data Science for Tribological Applications0Artificial Intelligence for Materials Science: Transforming Research Paradigms6Polymer informatics: Integrating data‐driven strategies, advanced machine learning, and automated synthesis for next‐generation polymer design2Materials by machines: A review on intuition and knowledge-driven learning for rapid discovery and optimization0Enhancing Generalization in Synthesizability Prediction of Structurally Dissimilar Materials0Can LLMs Solve Solubility Tasks? The SoluBench Benchmark for Pure and Mixed Solvent Systems0Leveraging large language models to address data scarcity in machine learning for graphene synthesis1MatterChat: how a structure-aware multimodal LLM bridges atomic structures and scientific reasoning in materials science0AI for Accelerated Materials Discovery: From Generative Design to Autonomous Realization2Generative Models in Inorganic Crystals Discovery and Inverse Design0Closed‐Loop Solid‐State Synthesis Planning for Materials Discovery With Large Language Models1Artificial Intelligence for Advanced Functional Materials: Progress and Emerging Frontiers0LLM-guided prediction of riboswitch–ligand binding affinity under data-limited conditions0Analyzing GPT-5 performance in general chemistry0

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