Computational Prediction of Emulsion Characteristics

by M. Negash, N. Briggs, J. Weston, S. Crossley, J. Harwell, C. Aichele, D. Resasco, and B. J. Neely,

Work was performed at: Oklahoma State University and the University of Oklahoma

 

Scientific Achievement

Demonstrated the capability to provide predictions of emulsion characteristics computationally.

Significance and Impact

Computational predictions avoid the current need for experimental work to determine emulsion characteristics and provides impetus toward the development of computer-assisted molecular design of emulsions.

Research Details

  • A database containing emulsion characteristics for 24 molecules including average droplet size, fraction, and emulsion type was assembled.
  • A linear Quantitative Structure-Property Relationship (QSPR) modeling approach was utilized.
  • This work demonstrates significant dependence of emulsion characteristics on molecular structural descriptors.

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Computational Prediction of Emulsion CharacteristicsQSPR modeling approach and results for average emulsion droplet size

 

 

 

Figure: QSPR modeling approach and results for average emulsion droplet size

 

Reference:

"Quantitative structure-property relationship (QSPR) models for emulsion characterization," in AIChE Annual Meeting, Atlanta, November 16, 2014.

 

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Collaborations among:

The University of Oklahoma

Oklahoma State Univerisy

The Univerisy of Tulsa

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