Literature DB >> 27298439

Non-ionic surfactant phase diagram prediction by recursive partitioning.

Gordon Bell1.   

Abstract

A model has been designed to predict the phase which forms in water for a non-ionic surfactant, at a given concentration and temperature. The full phase diagram is generated by selecting enough data points to cover the region of interest. The model estimates the probability for each one of 10 possible phases and selects the one with the highest likelihood. The probabilities are based on the recursive partitioning of a dataset of 10 000 known observations. The model covers alkyl chain length and branching, ethoxylate head length and number, and end capping of one or more of the ethoxylate chains. The relationship between chemical structure, shape and phase behaviour is discussed.This article is part of the themed issue 'Soft interfacial materials: from fundamentals to formulation'.
© 2016 The Author(s).

Entities:  

Keywords:  model; phase diagram; surfactant

Year:  2016        PMID: 27298439      PMCID: PMC4920284          DOI: 10.1098/rsta.2015.0137

Source DB:  PubMed          Journal:  Philos Trans A Math Phys Eng Sci        ISSN: 1364-503X            Impact factor:   4.226


  2 in total

Review 1.  Molecular simulation of liquid crystals: progress towards a better understanding of bulk structure and the prediction of material properties.

Authors:  Mark Richard Wilson
Journal:  Chem Soc Rev       Date:  2007-06-27       Impact factor: 54.564

2.  The application of artificial neural networks in the prediction of microemulsion phase boundaries in PEG-8 caprylic/capric glycerides based systems.

Authors:  Ljiljana Djekic; Svetlana Ibric; Marija Primorac
Journal:  Int J Pharm       Date:  2008-05-13       Impact factor: 5.875

  2 in total
  2 in total

1.  Soft interfacial materials: from fundamentals to formulation.

Authors:  N J Brooks; M E Cates; P S Clegg; A Lips; W C K Poon; J M Seddon
Journal:  Philos Trans A Math Phys Eng Sci       Date:  2016-07-28       Impact factor: 4.226

2.  An Improved Comparison of Chemometric Analyses for the Identification of Acids and Bases With Colorimetric Sensor Arrays.

Authors:  Michael James Kangas; Christina L Wilson; Raychelle M Burks; Jordyn Atwater; Rachel M Lukowicz; Billy Garver; Miles Mayer; Shana Havenridge; Andrea E Holmes
Journal:  Int J Chem       Date:  2018-04-25
  2 in total

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