From the start of a synthetic chemist's training, experiments are conducted based on recipes
from textbooks and manuscripts that achieve clean reaction outcomes, allowing the scientist …

Process intensification offers the potential to drastically reduce the energy consumption and
cost of producing chemicals from both bulk and distributed feedstocks. This review article …

In this paper, we survey the main superstructure-based approaches in process system
engineering, with a particular emphasis on the existing literature for automated …

It is well-documented how artificial intelligence can have (and already is having) a big
impact on chemical engineering. But classical machine learning approaches may be weak …

Current and future challenges of optimization in the process industry are discussed. The gap
between academic research and industrial workflow is analyzed. Moreover, issues arising …

Olefins production in the UK is the most emission-intensive sector of the chemical industry.
Bringing thermocatalytic and electrocatalytic processes together, this paper compares nine …

Managing electricity demand has become a key consideration in power grid operations.
Industrial demand response (DR) is an important component of demand-side management …

Bayesian optimization (BO) is a powerful technology for optimizing noisy expensive-to-
evaluate black-box functions, with a broad range of real-world applications in science …

The paper tackles the issue of managing physical assets in asset-intensive industries, where
continuity plans are crucial for business operations during disruptions. However, resource …

Currently, digitalization provides new challenges and opportunities for the process industry.
A frequently used keyword in this context is digital twin. In this work, the term digital twin is …