Abstract:-The ability to predict the key physical and chemical properties of polymeric materials from their repeat-unit structure and chain-length architecture prior to synthesis is of great value for the design of polymerbased chemical products, with new functionalities and improved performance. Computer aided molecular design (CAMD) methods can expedite the design process by establishing input-output relations between the type and number of functional groups in a polymer repeat unit and the desired macroscopic proper… Show more
“…Our example assumed particular PO and AI to illustrate details of step 1 to step 4 and part of step 5. On-going developments of polymer property methods 37 for computer-aided polymer design 38,39 suggest that similar considerations can be made for identifying promising polymer structures. The possibilities of the example case may be expanded with potential for improved results.…”
A systematic design strategy is given for computer-aided design of microparticle drug-delivery systems produced by solvent evaporation. In particular, design of solvents, polymer material, and external phase composition are considered for the case when the active ingredient is known. The procedure is based on fundamental thermodynamic relations and group contributions to properties of pure species (solvent, active ingredient and polymer) and their mixtures. The method is intended for pharmaceuticals with complex molecular structures, for which limited experimental information is known. Case studies of solvent design are given.
“…Our example assumed particular PO and AI to illustrate details of step 1 to step 4 and part of step 5. On-going developments of polymer property methods 37 for computer-aided polymer design 38,39 suggest that similar considerations can be made for identifying promising polymer structures. The possibilities of the example case may be expanded with potential for improved results.…”
A systematic design strategy is given for computer-aided design of microparticle drug-delivery systems produced by solvent evaporation. In particular, design of solvents, polymer material, and external phase composition are considered for the case when the active ingredient is known. The procedure is based on fundamental thermodynamic relations and group contributions to properties of pure species (solvent, active ingredient and polymer) and their mixtures. The method is intended for pharmaceuticals with complex molecular structures, for which limited experimental information is known. Case studies of solvent design are given.
“…A multiscale model-based approach for predicting physical properties of polymer repeat unit by combined CAMD technique based on GC plus method with atomistic simulations has also been put in use. 63 The molecular simulations were capable of providing the physical properties of the polymer as a function of size (number of repeat units) and operational variables such as the temperature and the pressure.…”
This paper provides a review of the available literature on computational schemes for rational solvent design, with a focus on solvent extraction and crystallization (the two most common unit operations) in pharmaceutical industry. The computer-aided design of solvents is important as a cost-effective tool, especially with the regular development of new pharmaceutical molecules. Also, there is a need to minimize the amount and the number of solvents used with regard to environmental, health, and toxicological concerns. This review covers the properties of interest and the predictive methods for estimation of these properties in solvent design including the group contribution based methods, quantitative structure property prediction methods and molecular modeling methods. In addition, the various optimization approaches for rational solvent design such as outer approximation, branch and bound, simulated annealing, and genetic algorithm are also discussed.
“…To overcome this limitation, rigorous molecular dynamic (MD) simulation has been used to predict polymer properties. , However, only limited work focused on polymer design integrated with MD has been studied. For example, Satyanarayana et al integrated GC and MD into a multiscale computer-aided polymer design (CAPD) model for the design of polymer repeating units. Liang et al formulated the CAPD problem as an MINLP model, which was successfully applied to the design of tire rubber polymers.…”
In this paper, a computer-aided polymer design (CAPD) framework with a stochastic optimization model is proposed for the design of perfluorinated sulfonic acid proton exchange membrane (PFSA-PEM) with desired properties. First, the requirements and target characteristics are identified and converted to property constraints. Then, the polymer design model is formulated as a stochastic optimization problem in which the operation temperature is treated as a random variable. Subsequently, the formulated stochastic mixed integer nonlinear programming problem is solved by a two-stage strategy. In stage I, molecular dynamics is utilized to simulate the target properties for different structures and quantities of side chains, thus establishing the quantitative structure−property relationship. In stage II, the operation temperature is considered subject to a specified probability distribution. The optimization model is solved to obtain the optimal polymer structure over the operating temperature range. Finally, a case study of PFSA-PEM design is given to illustrate the application of the CAPD framework.
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