Imperial College London
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Prof Claire S. Adjiman FREng

Faculty of Engineering, Department of Chemical Engineering

Professor of Chemical Engineering
 
 
 
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Contact

 

+44 (0)20 7594 6638c.adjiman Website

 
 
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Location

 

608Roderic Hill BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Jonuzaj:2018:10.1016/j.compchemeng.2018.01.016,
author = {Jonuzaj, S and Gupta, A and Adjiman, CSJ},
doi = {10.1016/j.compchemeng.2018.01.016},
journal = {Computers and Chemical Engineering},
pages = {401--421},
title = {The design of optimal mixtures from atom groups using Generalized Disjunctive Programming},
url = {http://dx.doi.org/10.1016/j.compchemeng.2018.01.016},
volume = {116},
year = {2018}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - A comprehensive computer-aided mixture/blend design methodology for formulating a gen-eral mixture design problem where the number, identity and composition of mixture constituentsare optimized simultaneously is presented in this work.  Within this approach, Generalized Dis-junctive Programming (GDP) is employed to model the discrete decisions (number and identitiesof  mixture  ingredients)  in  the  problems.   The  identities  of  the  components  are  determined  bydesigning molecules from UNIFAC groups.  The sequential design of pure compounds and blends,and  the  arbitrary  pre-selection  of  possible  mixture  ingredients  can  thus  be  avoided,  making  itpossible  to  consider  large  design  spaces  with  a  broad  variety  of  molecules  and  mixtures.   Theproposed  methodology  is  first  applied  to  the  design  of  solvents  and  solvent  mixtures  for  max-imising  the  solubility  of  ibuprofen,  often  sought  in  crystallization  processes;  next,  antisolventsand antisolvent mixtures are generated for minimising the solubility of the drug in drowning outcrystallization; and finally, solvent and solvent mixtures are designed for liquid-liquid extraction.The  GDP  problems  are  converted  into  mixed-integer  form  using  the  big-M  approach.   Integercuts are included in the general models leading to lists of optimal solutions which often containa combination of pure and mixed solvents.
AU  - Jonuzaj,S
AU  - Gupta,A
AU  - Adjiman,CSJ
DO  - 10.1016/j.compchemeng.2018.01.016
EP  - 421
PY  - 2018///
SN  - 1873-4375
SP  - 401
TI  - The design of optimal mixtures from atom groups using Generalized Disjunctive Programming
T2  - Computers and Chemical Engineering
UR  - http://dx.doi.org/10.1016/j.compchemeng.2018.01.016
UR  - http://hdl.handle.net/10044/1/56673
VL  - 116
ER  -
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