Das Kumar, Sen Gupta, Sen Basu. 2005. Prediction of surface tension of organic liquids using artificial neural networks. Indian Chem Eng 47(4):219-223.
Latest Updates: Kumar 2005 RSS
Escobedo and Mansoori (AIChE J. 42(5): 1425, 1996)Found original paper: check Escobedo 1996
The proposed 1996 paper relates the surface tension of mixtures to bulk-phase concentrations and properties (i.e. densities). Surface tension of pure organic fluids σ:
The two ρ are densities: liquid and vapour.
They introduced parachor (
P), a new expression, derived from statistical mechanics (from Macleod equation) which represents the experimental surface tension of 94 different organic compounds within 1.05 AAD% (average absolute deviations).
(Kumar 2005) It expresses the surface tension of a liquid in equilibrium with its own vapour. Historical reference for parachor cited here: Macleod, Sugden, Quayle, Escobedo.
Prediction of Surface Tension of Organic Liquids Using Artificial Neural Networks
D. Kumar, S. Gupta and S. Basu. Indian Chem Engr., Section A, Vol. 47, No. 4, October – December 2005.
A forward-feed back propagation neural network, based on the Levenberg-Marquardt optimization and gradient descent with momentum weight and bias method was used. The input parameters, e.g., density, refractive index and parachor, to the neural network were chosen from the previous studies on theoretical prediction of surface tension.