COSMO-susCAMPD: Sustainable Solvents from Combining Computer-Aided Molecular and Process Design with Predictive Life Cycle Assessment

Open access
Date
2021-12-14Type
- Journal Article
Citations
Cited 8 times in
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Cited 10 times in
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ETH Bibliography
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Abstract
Sustainable solvents are crucial for chemical processes and can be tailored to applications by computer-aided molecular and process design (CAMPD). Recent CAMPD methods consider not only economics but also environmental hazards and impacts. However, holistic environmental assessment needs to address the complete life cycle of solvents. Here, we propose a CAMPD framework integrating Life Cycle Assessment (LCA) of solvents from cradle-to-grave: COSMO-susCAMPD. The framework builds on the COSMO-CAMPD method for predictive design of solvents using COSMO-RS and pinch-based process models. Cradle-to-grave LCA is enabled by combining predictive LCA from cradle-to-gate using an Artificial Neural Network with gate-to-grave Life Cycle Inventory data from the process models. The framework is applied to design solvents in a hybrid extraction-distillation process. The results highlight the need for cradle-to-grave LCA as objective function: Heuristics, economics, or cradle-to-gate LCA lead to suboptimal solvent choices. COSMO-susCAMPD thus enables the holistic environmental design of solvents using cradle-to-grave LCA. Show more
Permanent link
https://doi.org/10.3929/ethz-b-000491510Publication status
publishedExternal links
Journal / series
Chemical Engineering ScienceVolume
Pages / Article No.
Publisher
ElsevierSubject
Predictive thermodynamics; Artificial neural network; Pinch-based process models; Extraction-distillation; γ-valerolactoneOrganisational unit
09696 - Bardow, André / Bardow, André
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Show all metadata
Citations
Cited 8 times in
Web of Science
Cited 10 times in
Scopus
ETH Bibliography
yes
Altmetrics