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RESEARCH PAPER · Synthetic and Systems Biotechnology · 2024

Integrating chemistry knowledge in large language models via prompt engineering

Hongxuan Liu, Haoyu Yin, Zhiyao Luo, Xiaonan Wang

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Integrating chemistry knowledge in large language models via prompt engineeringOriginalArtificial intelligence enabled smart design and manufacturing of advanced materials: The endless Frontier in AI + era51Machine learning-assisted retrosynthesis planning: Current status and future prospects18The Role of Prompt Engineering in Improving Language Understanding and Generation3Enhanced Voice Phishing Detection Using an LLM-Based Framework for Data Augmentation and Classification8LLM-CDM: A Large Language Model Enhanced Cognitive Diagnosis for Intelligent Education14Zero-Shot Prediction of Conversational Derailment With Large Language Models2Emerging trends in the optimization of organic synthesis through high-throughput tools and machine learning17Chat-microreactor: A large-language-model-based assistant for designing continuous flow systems13Leveraging Prompt Engineering in Large Language Models for Accelerating Chemical Research29Visual Text Mining with Progressive Taxonomy Construction for Environmental Studies0AI foundational models in low-carbon energy and chemical engineering and the intelligent discovery platform for novel materials1Bridging language models and computational materials science: A prompt‐driven framework for material property prediction17Intelligent chemical synthesis based on microchemical engineering technology2Unlocking deep eutectic solvent knowledge through a large language model-driven framework and an interactive AI agent14The role of flow chemistry in self-driving labs19Unlocking the Potential of the Prompt Engineering Paradigm in Software Engineering: A Systematic Literature Review7High-Performance Polyimide Design: Machine Learning–Accelerated Multiobjective Optimization6Research on Key Technologies for Rapid Detection and Correction of Anomalies in Electric Vehicle Charging Pile Data Using Prompt Engineering0Process-Oriented Dual-Layer Knowledge GraphRAG for Reservoir Engineering Decision Support3Prompts for planning-AI integration: LLM prompt design for supporting sustainable urban development6Using Large Language Models for Process Analysis: Identifying Deviations by Comparing Process Models - A Test Report0An Automotive Fault Diagnosis Framework Based on Knowledge Graphs and Large Language Models5From Feature‐Based Chemical Similarity to Chemical Language Models—A Paradigm Shift in Computer‐Aided Molecular Design and Property Predictions8A survey on large language models in biology and chemistry8Domain-augmented large language models for automated root cause classification of offshore process incidents9Improving diagnostic accuracy in preoperative glioma classification: performance of knowledge-enhanced large language models compared with radiologists5A Cognitive Agentic AI Framework for Early-Phase Process Design and Optimization0Artificial Intelligence: Exploring Large Language Models for Calculating Forces in Trusses1Foundation Models and LLMs for Materials Science: A Review of Prompting, Fine-Tuning, and What Does Not Transfer0RETRACTED: Reshaping MOFs synthesis conditions mining with a dynamic multi-agents framework of large language model5Shifting the educational paradigm: Discovering concepts and connections0Exploring the Potential of Using ChatGPT in Chemistry Education6RLLM-SS: A knowledge-guided simplex search method integrating large language model and reinforcement learning for injection molding quality control2General-Purpose Models for the Chemical Sciences: LLMs and Beyond6Prompt Engineering Accelerates the Data‐Driven Discovery of Photocatalysts via an LLM‐Based Model Ensemble Strategy3Accelerating Catalyst Materials Discovery With Large Artificial Intelligence Models32Adaptive Artificial Intelligence for Students with Specific Learning Disabilities in Reading Science Content2Accelerating Catalyst Materials Discovery With Large Artificial Intelligence Models2New Era of AI in Chemical Process Safety: Foundation Models10A Bibliometric Analysis of Generative Artificial Intelligence in a Multidisciplinary Global Perspective0AutoSEE: An Artificial Intelligence Agent for Automated Solid Electrolyte Exploration2Automating AI Discovery for Biomedicine Through Knowledge Graphs and Large Language Models Agents0LLM‐Based Scientific Assistants for Knowledge Extraction: Which Design Choices Matter?0Feasibility Study on Reactor Preliminary Design via Fine-Tuning of Large Language Models0iS2C2: a cointelligent platform for mechanistic discovery of disease cellular crosstalk1Knowledge-augmented large language models to support automated HAZOP report generation1Question-Answering Agent Based on Prompt Engineering and RAG0Chemical reactor optimization leveraging distilled LLM enhanced by prompt design and fine-tuning strategy3Adaptive Fast-Slow Large Language Model Framework for Multidimensional Classification of Prenatal Ultrasound Reports: Comparative Study0EduChatQA: curriculum-aware hybrid retrieval and teacher-aligned prompting for textbook-grounded educational QA0Research progress of domain-specific large language models for chemical materials0Embodied Intelligence Robots: Flexible Task Planning Framework and Multimodal Fusion Perception0Comparing teacher-centered and student-centered agents based on prompt engineering: Effects on learning performance, cognitive load, flow experience, and empathy perception in physics learning0Structuring Student–AI Interaction in STEM Learning0Fine-Tuning DeepSeek-OCR-2 for Molecular Structure Recognition0Research on solid-state battery information mining based on large language models and chain-of-thought reasoning0

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  2. Machine learning-assisted retrosynthesis planning: Current status and future prospects

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  3. The Role of Prompt Engineering in Improving Language Understanding and Generation

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