Computer‐Aided Molecular and Process Design

Abstract

Increasing energy prices, tighter environmental regulation, and global competition urge the industry to optimize its processes for converting chemicals and energy. This optimization is far from trivial. Often, the key to major breakthrough relies not only on optimal process conditions but also on selecting suitable molecules as solvents, catalysts, or heat transfer fluids. This selection is highly coupled with the process itself: Choosing the right molecule is a crucial lever for process performance. However, the molecular search space is vast: more than 200 000 000 molecules have already been reported in the CAS registry. The search for the best molecule is thus the search for the needle in the haystack. The ultimate success of a process is only ensured if a molecule is selected based on its optimal process performance. Traditionally, however, the selection of a molecule and the design of the process have been approached sequentially and independently. Computer-aided molecular and process design (CAMPD) methods have been developed to tackle this challenge and systematically tailor molecules for a given application. Thereby, CAMPD can contribute to the transition towards a more sustainable energy and chemical industry, for example, by identifying energy-efficient carbon capture materials, sustainable working fluids for heat pumps, or green solvents for production processes. What is required for a successful application of CAMPD? The basis of a CAMPD problem is a computer-aided molecular design (CAMD) formulation that allows treating the molecular structure as a degree of freedom in an optimization problem. The CAMD formulation is linked with a property model that enables predicting all molecule properties required to evaluate the constraints and objective functions. To reflect the process performance, classical CAMD methods used simplified property-based indicators as the objective function. Recent CAMPD methods integrate detailed process models to assess process performance directly. The recent development of CAMPD/CAMD includes using advanced physically-based and data-driven property models. Moreover, the scope of predicted properties moves beyond the thermodynamic properties to environmental properties such as global warming potential. After decades of CAMPD/CAMD development, these tools have become available for industrial use by implementing CAMPD in flowsheet simulators. Thereby, the effort and required expert knowledge are greatly reduced to set up and solve a CAMPD problem. However, including such new tools in the daily workflow usually takes time. The urge to develop new sustainable processes hopefully will enhance the application of these CAMPD tools. In this special issue of Chemie Ingenieur Technik, authors from industry and academia present their latest developments and applications of CAMPD in energy and chemical engineering. The special issue cannot provide a comprehensive picture of this rapidly developing field. Thus, we aim to provide the reader with an impression of the current status and possible future directions of CAMPD. We hope readers will find inspiration in this special issue and thank all authors for their highly appreciated contributions! Norbert Asprion André Bardow Jonas Mairhofer Johannes Schilling