Large language models for reticular chemistry

Attention Is All You Need

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Learning Transferable Visual Models From Natural Language Supervision

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Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer

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Reticular synthesis and the design of new materials

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BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension

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Design and synthesis of an exceptionally stable and highly porous metal-organic framework

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Porous, Crystalline, Covalent Organic Frameworks

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Exceptional chemical and thermal stability of zeolitic imidazolate frameworks

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SMILES, a chemical language and information system. 1. Introduction to methodology and encoding rules

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Hydrogen Storage in Microporous Metal-Organic Frameworks

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LLaMA: Open and Efficient Foundation Language Models

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Chain-of-Thought Prompting Elicits Reasoning in Large Language Models

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Training language models to follow instructions with human feedback

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A homochiral metal–organic porous material for enantioselective separation and catalysis

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SciBERT: A Pretrained Language Model for Scientific Text

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Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks

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Selective binding and removal of guests in a microporous metal–organic framework

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Water Adsorption in Porous Metal–Organic Frameworks and Related Materials

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Metal− organic frameworks with exceptionally high capacity for storage of carbon dioxide at room temperature

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Llama 2: Open Foundation and Fine-Tuned Chat Models

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Designed Synthesis of 3D Covalent Organic Frameworks

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Conductive MOF electrodes for stable supercapacitors with high areal capacitance

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A Survey of Large Language Models

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A Survey of Large Language Models

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Metal–Organic Frameworks as Efficient Materials for Drug Delivery

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Zirconium‐Metalloporphyrin PCN‐222: Mesoporous Metal–Organic Frameworks with Ultrahigh Stability as Biomimetic Catalysts

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RASPA: molecular simulation software for adsorption and diffusion in flexible nanoporous materials

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Algorithms and tools for high-throughput geometry-based analysis of crystalline porous materials

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Multiple Functional Groups of Varying Ratios in Metal-Organic Frameworks

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Scientific discovery in the age of artificial intelligence.

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Lost in the Middle: How Language Models Use Long Contexts

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Sparks of Artificial General Intelligence: Early experiments with GPT-4

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Scaling Instruction-Finetuned Language Models

Chung, H. W., Hou, L., Longpre, S., Zoph, B., Tay, Y., Fedus, W., Li, Y., Wang, X., Dehghani, M., Brahma, S., et al. (2022) · arXiv · doi:10.48550/arxiv.2210.11416 · Cited by 1,441 · see citing works

Large-scale screening of hypothetical metal–organic frameworks

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Recent Advances in Natural Language Processing via Large Pre-trained Language Models: A Survey

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Emergent Abilities of Large Language Models

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A Comprehensive Overview of Large Language Models

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On Faithfulness and Factuality in Abstractive Summarization

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Tree of Thoughts: Deliberate Problem Solving with Large Language Models

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Multimodal learning with transformers: A survey

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Autonomous chemical research with large language models

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Retrieval-Augmented Generation for Large Language Models: A Survey

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Advances, Updates, and Analytics for the Computation-Ready, Experimental Metal–Organic Framework Database: CoRE MOF 2019

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Self-Consistency Improves Chain of Thought Reasoning in Language Models

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Augmenting large language models with chemistry tools

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Rapid Production of Metal−Organic Frameworks via Microwave-Assisted Solvothermal Synthesis

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Computation-Ready, Experimental Metal–Organic Frameworks: A Tool To Enable High-Throughput Screening of Nanoporous Crystals

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Solvent-free synthesis of a microporous metal–organic framework

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Computational structure characterisation tools in application to ordered and disordered porous materials

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Postsynthetic Covalent Modification of a Neutral Metal−Organic Framework

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Tuning the Adsorption Properties of UiO-66 via Ligand Functionalization

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The power of generative AI: A review of requirements, models, input–output formats, evaluation metrics, and challenges

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Weaving of organic threads into a crystalline covalent organic framework

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Understanding the diversity of the metal-organic framework ecosystem

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The growing energy footprint of artificial intelligence

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Towards Mitigating LLM Hallucination via Self Reflection

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Machine learning the quantum-chemical properties of metal–organic frameworks for accelerated materials discovery

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ChatGPT Chemistry Assistant for Text Mining and the Prediction of MOF Synthesis

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Carbon dioxide capture from open air using covalent organic frameworks

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Towards Reasoning in Large Language Models: A Survey

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Sustainable AI: Environmental Implications, Challenges and Opportunities

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Large Language Models for Mathematical Reasoning: Progresses and ChallengesPreprint

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Leveraging large language models for predictive chemistry

Jablonka, K. M., Schwaller, P., Ortega-Guerrero, A., & Smit, B. (2024) · Nature Machine Intelligence · doi:10.1038/s42256-023-00788-1 · Cited by 378 · see citing works

MatSciBERT: A materials domain language model for text mining and information extraction

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ChatMOF: an artificial intelligence system for predicting and generating metal-organic frameworks using large language models

Kang, Y., & Kim, J. (2024) · Nature Communications · doi:10.1038/s41467-024-48998-4 · Cited by 268 · see citing works

Assessing the impact of generative AI on medicinal chemistry

Walters, W. P., & Murcko, M. (2020) · Nature Biotechnology · doi:10.1038/s41587-020-0418-2 · Cited by 262 · see citing works

MM-LLMs: Recent Advances in MultiModal Large Language Models

Zhang, D., Yu, Y., Dong, J., Li, C., Su, D., Chu, C., & Yu, D. (2024) · Findings of the Association for Computational Linguistics ACL 2024 · doi:10.18653/v1/2024.findings-acl.738 · Cited by 260 · see citing works

Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks

Wang, Y., Mishra, S., Alipoormolabashi, P., Kordi, Y., Mirzaei, A., Naik, A., Ashok, A., Dhanasekaran, A. S., Arunkumar, A., Stap, D., et al. (2022) · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing · doi:10.18653/v1/2022.emnlp-main.340 · Cited by 247 · see citing works

MOF Synthesis Prediction Enabled by Automatic Data Mining and Machine Learning**

Luo, Y., Bag, S., Zaremba, O. T., Cierpka, A., Andreo, J., Wuttke, S., Friederich, P., & Tsotsalas, M. M. (2022) · Angewandte Chemie International Edition · doi:10.1002/anie.202200242 · Cited by 246 · see citing works

Principles of Designing Extra-Large Pore Openings and Cages in Zeolitic Imidazolate Frameworks

Yang, J., Zhang, Y., Liu, Q., Trickett, C. A., Gutiérrez‐Puebla, E., Monge, Á., Cong, H., Aldossary, A., Deng, H., & Yaghi, O. M. (2017) · Journal of the American Chemical Society · doi:10.1021/jacs.7b02272 · Cited by 244 · see citing works

Standard Practices of Reticular Chemistry

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Characterization and comparison of pore landscapes in crystalline porous materials

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14 examples of how LLMs can transform materials science and chemistry: A reflection on a large language model hackathon

Jablonka, K. M., Ai, Q., Al-Feghali, A., Badhwar, S., Bocarsly, J. D., Bran, A. M., Bringuier, S., Brinson, L. C., Choudhary, K., Circi, D., et al. (2023) · Digital Discovery · doi:10.1039/d3dd00113j · Cited by 218 · see citing works

Prediction of water stability of metal–organic frameworks using machine learning

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Using Machine Learning and Data Mining to Leverage Community Knowledge for the Engineering of Stable Metal–Organic Frameworks

Nandy, A., Duan, C., & Kulik, H. J. (2021) · Journal of the American Chemical Society · doi:10.1021/jacs.1c07217 · Cited by 200 · see citing works

The Impact of Large Language Models on Scientific Discovery: a Preliminary Study using GPT-4Preprint

AI4Science, M., & Quantum, M. (2023) · arXiv.org · doi:10.48550/arxiv.2311.07361 · Cited by 199 · see citing works

Crystal structure generation with autoregressive large language modeling

Antunes, L. M., Butler, K. T., & Grau‐Crespo, R. (2024) · Nature Communications · doi:10.1038/s41467-024-54639-7 · Cited by 194 · see citing works

Digital Reticular Chemistry

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ChatGPT Research Group for Optimizing the Crystallinity of MOFs and COFs

Zheng, Z., Zhang, O., Nguyen, H. L., Rampal, N., Alawadhi, A. H., Rong, Z., Head-Gordon, T., Borgs, C., Chayes, J. T., & Yaghi, O. M. (2023) · ACS Central Science · doi:10.1021/acscentsci.3c01087 · Cited by 172 · see citing works

A GPT‐4 Reticular Chemist for Guiding MOF Discovery**

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Two-dimensional Stiefel-Whitney insulators in liganded Xenes

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Accelerated end-to-end chemical synthesis development with large language models

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An automatic end-to-end chemical synthesis development platform powered by large language models

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MOFSimplify, machine learning models with extracted stability data of three thousand metal–organic frameworks

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Position: Levels of AGI for Operationalizing Progress on the Path to AGIPreprint

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Fine-tuning large language models for chemical text mining

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MOFX-DB: An Online Database of Computational Adsorption Data for Nanoporous Materials

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Shaping the Water-Harvesting Behavior of Metal–Organic Frameworks Aided by Fine-Tuned GPT Models

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Using Machine Learning for Green Substitution of Industrial Chemicals: Integrating Functionality, Hazard, and Life Cycle Impact

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A Hybrid Machine Learning Framework for Predicting Hydrogen Storage Capacities in Metal Hydrides: Unsupervised Feature Learning with Deep Neural Networks

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Prompt Engineering Accelerates the Data‐Driven Discovery of Photocatalysts via an LLM‐Based Model Ensemble Strategy

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An imidazole-based halogen-bonded organic framework for selective adsorption of aliphatic amine vapors

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Large language model-driven decision-making for single-atom Fenton-like catalysts toward wastewater treatment

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Atomic-Level Electron Crystallography of Metal–Organic Frameworks Via Resin-Peeled Ultramicrotomy

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Shaping Metal–Organic Frameworks Toward Practical Applications: From 0D to 3D

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Are we there yet? Adventures on a road trip through machine learning as a computational chemist

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DeepSeek-LLM with Adaptive RAG for Pharmaceutical Dissolution Prediction

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Data-driven machine learning assisted prediction of metal node types in metal-organic frameworks for guiding linker design and targeting inverse C3H8/C3H6 separation

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Metal–organic frameworks: defining new spaces for chemistry

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Uncovering the Multifunctional Roles of Metal‐Organic Frameworks in Protecting Lithium Metal Anodes Assisted by Large Language Models

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MaterialBrain: High-Performance Material Synthesis Extraction via Human–AI-Curated Few-Shot Large Language Models

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AI-powered oriented synthesis of naphthalenediimide-based MOFs for photochromic encryption and ammonia sensing

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MOFReasoner: think like a scientist—a reasoning large language model via knowledge distillation

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Coordination Polymers Assembled from Flexible Tricarboxylate Linkers: Hydrothermal Synthesis, Structural Diversity, and Catalytic Features

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Chat-RFB: a flow battery chat system leveraging knowledge graphs and large language models

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An interpretable machine learning framework for predicting Curie temperature of lead-based piezoelectric ceramics

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Precision Chemical Design for Reticular Spintronics

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From Chatbots to Chemists: Autonomous Agents for Heterogeneous Catalysis

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An automated evaluation agent for Q&A pairs and reticular synthesis conditions

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ChatMolData: A Multimodal Agent for Automatic Molecular Data Processing

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Evaluating and advancing large language models for nanofiltration membrane knowledge tasks

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Material design accelerated by large language models: end-to-end empowerment from knowledge mining to intelligent design

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Heterogeneous data-driven resolution generation for software systems via large language models

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MOF and COF-based drug delivery system for Parkinson's disease: Mechanism, future and development of artificial intelligence

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Structural Engineering of a Zn 4 O-Based Metal–Organic Framework via Geometric Deformation of Secondary Building Units for Enhanced Trace Benzene Adsorption

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Integrated Photosensitive Fragments and Catalytically Active Sites into Zirconium Metal–Organic Frameworks for CO 2 Photoreduction

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Developing an AI Course for Synthetic Chemistry Students

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Design, Synthesis, and Photocatalytic Applications of sp2-Carbon-Conjugated Organic Frameworks

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Usability and extensibility: imperatives for next-generation LLM agents in chemistry

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The Future of Reticular Chemistry: From Structural Discovery to Programmable Matter and Artificial Intelligence

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Molecular Simulations of Water in Metal–Organic Frameworks: Challenges for Computational Screening and the Value of Fundamental Insights

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Surface Mounted Metal–Organic Frameworks for Advanced Sensing: Construction Strategies, Recent Applications, and Emerging Opportunities With Artificial Intelligence

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Hybrid-linking organic frameworks: design strategies, synergistic properties, and emerging applications

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Carboxylate-Ligand-Based Coordination Polymers and Metal Complexes: From Structural Diversity and Supramolecular Descriptors to Function-Oriented Design

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Machine Learning in Materials Science: Data-Driven Discovery and Functional Applications

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From Scientific Copilots to Tool-Grounded Autonomy: AI Agents in Simulation-Driven Materials Discovery

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Precise identification of the atomic-scale spatial distribution of Al sites within zeolite

Liu, C., & Chen, F. (2025) · Science China Materials · doi:10.1007/s40843-025-3339-0

Automated construction of inorganic materials databases and materials discovery based on large language models

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Metal‐Organic Frameworks

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The Interaction of Generative Artificial Intelligence with Computational Intelligence on the Knowledge Economy: A Text Mining Approach

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Role of Large Language Models and Retrieval-Augmented Generation for Accelerating Crystalline Material Discovery: A Systematic Review

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LLMs, RAG systems, and agents in crystalline materials discovery and characterization: A systematic review

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Research progress of domain-specific large language models for chemical materials

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Leveraging Chemistry Foundation Models to Facilitate Structure Focused Retrieval Augmented Generation in Multi-Agent Workflows for Catalyst and Materials DesignPreprint

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Large Language Models (LLMs) for Materials Design

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