Influence prediction of alkylamines upon electrical percolation of AOT-based microemulsions using artificial neural networks

Lago Antonio Montoya, Oscar Adrían Moldes, Antonio Cid Samamed, Conzalo Astray, Juan Francisco Gálvez, Juan Carlos Mejuto

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

Simulations for the electrical percolation of AOT/iC8/H2O W/o microemulsions added with alkylamines have been carried out by means of multilayer perceptron. Five variables have been elected as inputs: Amine concentration, molecular weight, log P, hydrocarbon chain length (as number of carbons), and pKa. As a result, a neural model consisting in five input neurons, two middle layers (with fifteen and ten neurons respectively) and one output neuron was chosen because of its better performance, with a RMSE of 0.54°C for the prediction set, with R2= 0.9976.

Original languageEnglish
Pages (from-to)473-476
Number of pages4
JournalTenside Surfactants Detergents
Volume52
Issue number6
DOIs
Publication statusPublished - 1 Nov 2015

Keywords

  • Additive
  • Alkylamine
  • AOT
  • Artificial neural networks
  • Conductivity
  • Isooctane
  • Microemulsions
  • Multilayer perceptron
  • Percolation
  • Prediction
  • Simulation

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