Polymer colloids are complex materials that have the potential to be used in a vast array of
applications. One of the main reasons for their continued growth in commercial use is the …

This “white paper” is a concise perspective of the potential of machine learning in the
process systems engineering (PSE) domain, based on a session during FIPSE 5, held in …

The knowledge of mixtures' phase equilibria is crucial in nature and technical chemistry.
Phase equilibria calculations of mixtures require activity coefficients. However, experimental …

The term hybrid modeling refers to the combination of parametric models (typically derived
from knowledge about the system) and nonparametric models (typically deduced from data) …

This work reports the results of a perspective workshop held in summer 2021 discussing the
current status and future needs for multiscale modeling in reaction engineering. This …

Recent developments in data science and machine learning have inspired a new wave of
research into data-driven modeling for mathematical optimization of process applications …

Given the hesitance surrounding the direct implementation of black-box tools due to safety
and operational concerns, fully data-driven deep-neural-network (DNN)-based digital twins …

One of the main environmental impacts of amine-based carbon capture processes is the
emission of the solvent into the atmosphere. To understand how these emissions are …

The intensification of catalytic reactors is expected to play a crucial role to address the
challenges that the chemical industry is facing in the transition to more sustainable …

We propose a novel method enabling autocompletion of chemical flowsheets. This idea is
inspired by the autocompletion of text. We represent flowsheets as strings using the text …