Depending on the molecular model, group contribution (GC) approaches based on the statistical associating fluid theory (SAFT) can be classified in homosegmented and heterosegmented GC approaches. In homosegmented GC approaches, molecules are modeled as chains composed of identical segments. Heterosegmented GC approaches, on the other hand, consider molecular chains composed of different segment types and thus maintain a more detailed picture of real molecules. Therefore, heterosegmented GC approaches are arguably more physically realistic and ought to give more accurate descriptions of thermodynamic properties. In this work, we evaluate the performance of a homosegmented and a heterosegmented GC approach based on the perturbed-chain polar SAFT (PCP-SAFT) equation of state (EoS). To ensure a meaningful comparison between both GC approaches, a dipole term for the heterosegmented GC approach is formulated. Group parameters of 22 functional groups were adjusted to pure component property data. The comparison between both GC approaches shows that the heterosegmented GC approach leads to significantly better agreement with experimental data for various chemical families.

Solvent-based separation systems have a substantial potential for improvement when the solvent and the process conditions are optimized simultaneously. The fully integrated design problem, however, leads to an optimization problem of prohibitive size and complexity owing to the many discrete degrees of freedom in selecting a solvent and the nonlinear nature of the process models. We here implement and extend the method of continuous molecular targeting−computer-aided molecular design (CoMT−CAMD) for the solvent and process optimization of a precombustion CO 2 -capture system with physical absorption. CoMT−CAMD is a deterministic procedure that does not require a preselection of solvent molecules. The process topology considered in our study includes all major process operations of an existing CO 2 -capture system: multistage absorption, desorption (two flash desorption stages with gas recycle) and CO 2 compression. We measure the process performance with a single economic objective function. The objective function captures the process trade-offs and evaluates the potential processsolvent on a common basis. The solvent is represented as the pure component parameters of the perturbed-chain statistical associating fluid theory (PC-SAFT). The optimization problem is formulated with the pure component parameters of the solvent (PC-SAFT parameters) and with the process variables as degrees of freedom. Necessary auxiliary properties of the optimized solvent such as the ideal gas heat capacity and the molar mass are predicted with quantitative structure property relationship models, based on the pure component PC-SAFT parameters. As a result, one gets a unified thermodynamic framework for fluid properties based on the PC-SAFT model. With CoMT−CAMD we obtain a list of the best performing physical solvents for the considered CO 2 -capture application. The resulting list of best performing solvents contains state-of-the-art solvents and new green solvent molecules.

Organic Rankine Cycles (ORCs) generate power from low temperature heat. To make the best use of the diverse low temperature heat sources, the cycle is tailored to each application. The objective is to maximize process performance by optimizing both process parameters and the working fluid. Today, process optimization and working fluid selection are typically addressed separately in a two-step approach: working fluids are selected using heuristic knowledge; subsequently, the process is optimized. Such an approach can lead to suboptimal solutions, since the optimal fluid might be excluded by the heuristics. We therefore present a framework for the holistic design of ORCs enabling the simultaneous optimization of the process and the working fluid based on process performance. The simultaneous optimization is achieved by exploiting the rich molecular picture underlying the PC-SAFT equation of state in a continuous-molecular targeting approach (CoMT-CAMD). To allow for the prediction of caloric properties, a quantitative structure–property relationship (QSPR) for the ideal gas heat capacity is proposed that relies on pure component parameters of PC-SAFT. The framework is used for the optimization of a geothermal ORC in a case study. A sound holistic design of process and working fluid is achieved.

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