Neural network analysis of liquid–liquid extraction of phenol from wastewater using TBP solvent

The process of liquid–liquid extraction of phenol from wastewater is complicated by the presence of many variables acting simultaneously in an unknown non-linear fashion for the determination of the final extraction efficiency. In practice, it is quite difficult to develop a model for predicting various properties of such process. The present work reports on a neural network technique that enables us to construct relationship that will be employed to develop a quantitative method for the estimation of the extraction efficiency as a function of time and other process extraction parameters. The model is shown to be in excellent agreement with the experimental data and can be used to optimize the parameters of liquid–liquid phenol extraction with tributyl of phosphate (TBT).