Artificial intelligence has great potential for accelerating the design and engineering of chemical processes. Recently, we have shown that transformer-based language models can learn to auto-complete chemical process flowsheets using the SFILES 2.0 string notation. Also, we showed that language translation models can be used to translate Process Flow Diagrams (PFDs) into Process and Instrumentation Diagrams (P&IDs). However, artificial intelligence methods require big data and flowsheet data is currently limited. To mitigate this challenge of limited data, we propose a new data augmentation methodology for flowsheet data that is represented in the SFILES 2.0 notation. We show that the proposed data augmentation improves the performance of artificial intelligence-based process design models. In our case study flowsheet data augmentation improved the prediction uncertainty of the flowsheet autocompletion model by 14.7%. In the future, our flowsheet data augmentation can be used for other machine learning algorithms on chemical process flowsheets that are based on SFILES notation.
Retrosynthesis prediction enhanced by in-silico reaction data augmentation
College of Computer Science and Technology, Zhejiang University（浙江大学计算机科学与技术学院）；College of Chemical and Biological Engineering, Zhejiang University（浙江大学化学工程与生物工程学院）
Comprehensive pKa Data Augmentation from Limited Real Data through an Engineered Models-Quantum Framework
Department of Chemistry, Tsinghua University（清华大学化学系）；Department of Chemical Engineering, Tsinghua University（清华大学化学工程系）；School of Science, China Pharmaceutical University（中国药科大学理学院）
A universal augmentation framework for long-range electrostatics in machine learning interatomic potentials
Department of Chemistry, UC Berkeley, California 94720, United States（化学系，伯克利大学，加利福尼亚州，94720，美国）；Bakar Institute of Digital Materials for the Planet, UC Berkeley, California 94720, United States（地球数字材料研究所，伯克利大学，加利福尼亚州，94720，美国）；The Institute of Science and Technology Austria, Am Campus 1, 3400 Klosterneuburg, Austria（奥地利科学与技术研究所）
