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@article{Jonuzaj:2016:10.1002/aic.15122,
author = {Jonuzaj, S and Akula, PT and Kleniati, PM and Adjiman, CSJ},
doi = {10.1002/aic.15122},
journal = {AIChE Journal},
pages = {1616--1633},
title = {The formulation of optimal mixtures with generalized disjunctive programming: a solvent design case study},
url = {http://dx.doi.org/10.1002/aic.15122},
volume = {62},
year = {2016}
}

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TY  - JOUR
AB  - Systematic approaches for the design of mixtures, based on a computeraided mixture/blend design (CAMbD) framework, have the potential to deliver better products and processes. In most existing methodologies the number of mixture ingredients is fixed (usually a binary mixture) and the identity of at least one compound is chosen from a given set of candidate molecules. A novel CAMbD methodology is presented for formulating the general mixture design problem where the number, identity and composition of mixture constituents are optimized simultaneously. To this end, generalized disjunctive programming is integrated into the CAMbD framework to formulate the discrete choices. This generic methodology is applied to a case study to find an optimal solvent mixture that maximizes the solubility of ibuprofen. The best performance in this case study is obtained with a solvent mixture, showing the benefit of using mixtures instead of pure solvents to attain enhanced behavior.
AU  - Jonuzaj,S
AU  - Akula,PT
AU  - Kleniati,PM
AU  - Adjiman,CSJ
DO  - 10.1002/aic.15122
EP  - 1633
PY  - 2016///
SN  - 0001-1541
SP  - 1616
TI  - The formulation of optimal mixtures with generalized disjunctive programming: a solvent design case study
T2  - AIChE Journal
UR  - http://dx.doi.org/10.1002/aic.15122
UR  - https://aiche.onlinelibrary.wiley.com/doi/10.1002/aic.15122
UR  - http://hdl.handle.net/10044/1/28248
VL  - 62
ER  -

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Prof Claire S. Adjiman FREng

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