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2
Generative artificial intelligence in chemical engineering
Generative artificial intelligence
Machine learning in process systems engineering: Challenges and opportunities
Machine learning in process systems engineering
Data-driven Product-Process Optimization of N-isopropylacrylamide Microgel Flow-Synthesis
Data-driven Product-Process Optimization
A review and perspective on hybrid modeling methodologies
Hybrid modeling
Empirical assessment of ChatGPT’s answering capabilities in natural science and engineering
ChatGPT
Deep reinforcement learning for process design: Review and perspective
Deep reinforcement learning
Molecular Design of Fuels for Maximum Spark-Ignition Engine Efficiency by Combining Predictive Thermodynamics and Machine Learning
Molecular design
Graph machine learning for design of high-octane fuels
Molecular design
Toward automatic generation of control structures for process flow diagrams with large language models
Piping and Instrumentation Diagrams (P&IDs)
Digitization of chemical process flow diagrams using deep convolutional neural networks
Flowsheet digitization
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