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Molecule superstructures for computer-aided molecular and process design
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DOI：10.1039/d2me00230b.png)
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Abstract
En 中文
Integrated molecular and process design optimizes process variables together with molecules as an additional degree of freedom. The integrated design needs to represent the molecule in a machine-readable way that can be operated on by an optimization algorithm. For this purpose, group-contribution methods have been established as property models in molecular design applications. The underlying molecular representation for a group-contribution method is the number of occurrences of different pre-defined groups within the molecule. However, this way of encoding a molecule omits information about the structure of the molecule and thus limits the molecular detail available during design. In this work, we present a graph-based molecular representation approach that encodes the full structure of the molecule during optimization. This approach unlocks additional higher-fidelity property prediction methods for integrated molecular and process design while still allowing the use of gradient-based optimization algorithms. The framework is applied in a case study that designs the working fluid for an organic Rankine cycle using the heterosegmented gc-PC-SAFT equation of state as property prediction model. The molecular superstructure representation is shown to enable the efficient integration of advanced property models into molecular design.
Keywords:
ASSOCIATING FLUID THEORY
WASTE-HEAT-RECOVERY
EQUATION-OF-STATE
WORKING-FLUID
INTEGRATED SOLVENT
CHEMICAL-PRODUCT
PHASE-EQUILIBRIA
OPTIMIZATION
SELECTION
SYSTEMS
Journal
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3.2
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940
Citations:
2.4K
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