Property estimation models, important basis for the design and simulation of chemical products and processes in which the efficacy could be improved by taking advantage of machine learning.

Important issues are highlighted in this paper published in the AIChE journal. Congratulations to the Global Team of PSE for SPEED for participating in this project. Congratulations to all authors (Abdulelah S. Alshehri, Anjan K. Tula, Fengqi You, Rafiqul Gani) for an excellent contribution to improve property estimation models that are essential for chemical product and process design.

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