A new framework to automate, augment, and accelerate steps in computer-aided molecular design is presented. The problem is tackled in three stages: (1) composition design, (2) structure determination, and (3) extended design. Composition identification and structure determination are decoupled to achieve computational efficiency. Using approximate group-contribution methods in the first stage, molecular compositions that fit design targets are identified. In the second stage, isomer structures of solution compositions are determined systematically, and structure-based property corrections are used to refine the solution pool. In the final stage, the design is extended beyond the scope of group-contribution methods by using problem-specific property models. At each design stage, novel optimization models and graph theoretic algorithms generate a large and diverse pool of candidates using an assortment of property models. The wide applicability and computational efficiency of the proposed methodology are illustrated through three case studies.

In this work, we propose a new methodology for mixture design. By projecting the problem on the space of individual component properties, the methodology exploits a natural problem decomposition and capitalizes on fast methods for pure compound design and mixture fraction design. We demonstrate the proposed methodology through application to two illustrative examples and then to two problems from the mixture design literature concerning the purification of ibuprofen. In all cases, the proposed approach finds optimal solutions while exploring a small number of feasible molecular structures. © 2016 American Institute of Chemical Engineers AIChE J, 62: 1514–1530, 2016

High levels of emissions of ozone-depleting substances and greenhouse gases from supermarkets around the world can be attributed to the leakage of hydrofluorocarbons (HFCs) and the generation of electric power required for retail food refrigeration. Indirect refrigeration loops are ideally suited for reductions mandated by regulation standards because they reduce leakage and can lead to significantly lower total energy consumption. Hence, the design and identification of fluids that boost refrigeration performance while meeting safety and environmental guidelines is of considerable interest. Using a recently developed molecular design methodology (Samudra and Sahinidis, AIChE J., published online Apr 25, 2013, 10.1002/aic.14112) as our starting point, in this work, we developed a model and search technique for identifying ideal secondary refrigerants. Accurate property models that predict characteristic refrigerant properties guided the search for molecules. We also included environmental and safety metrics [biodegradability and lethal concentration (LC 50 )], along with performance criteria for heattransfer efficiency, to analyze the candidate molecules. We identified a number of novel molecules as well as known compounds that have not been used as secondary refrigerants.

Miniaturization technologies have led to a dramatic increase in electronics cooling requirements, which traditional cooling approaches are unable to fulfill. Thus, it is necessary to identify working fluids that enhance cooling performance and meet environmental and safety requirements. In this work, we develop a computer-aided molecular design approach to identify working fluids that have better heat transfer performance than the industrial refrigerant HFE 7200. We use group contribution methods as the major property estimation tool along with additional accurate property models. We derive a metric to measure the cooling performance of a two-phase cooling system consisting of microchannel heat sinks. Utilizing metrics for biodegradability and lethal concentration (LC50) enables additional analysis of the candidate molecules. Finally, we provide predictions of chemical stability to minimize the risk of potential chemical transformation. As a result of this work, we identify a number of novel cooling fluids that fall into four organic families.