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000904184 1001_ $$0P:(DE-HGF)0$$aFleitmann, Lorenz$$b0
000904184 245__ $$aCOSMO-susCAMPD: Sustainable solvents from combining computer-aided molecular and process design with predictive life cycle assessment
000904184 260__ $$aAmsterdam [u.a.]$$bElsevier Science$$c2021
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000904184 520__ $$aSustainable 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.
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000904184 7001_ $$0P:(DE-HGF)0$$aKleinekorte, Johanna$$b1
000904184 7001_ $$0P:(DE-HGF)0$$aLeonhard, Kai$$b2
000904184 7001_ $$0P:(DE-Juel1)172023$$aBardow, André$$b3$$eCorresponding author$$ufzj
000904184 773__ $$0PERI:(DE-600)1501538-5$$a10.1016/j.ces.2021.116863$$gVol. 245, p. 116863 -$$p116863 -$$tChemical engineering science$$v245$$x0009-2509$$y2021
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