Modeling of Surfactant-Enhanced Drying of Poly(styrene)-p-xylene Polymeric Coatings Using Machine Learning Technique

Abstract

In this work, a machine learning technique based on a regression tree model was used to model the surfactant enhanced drying of poly(styrene)-p-xylene coatings. The predictions of the developed model based on regression trees are in excellent agreement with the experimental data. A total of 16,258 samples were obtained through experimentation. These samples were separated into two parts: 12,960 samples were used for the training of the regression tree, and the remaining 3298 samples were used to test the tree’s prediction accuracy. MATLAB software was used to grow the regression tree. The mean squared error between the model-predicted values and actual outputs was calculated to be 8.8415 × 10−6. This model has good generalizing ability; predicts weight loss for given values of time, thickness, and triphenyl phosphate; and has a maximum error of 1%. It is robust and for this system, can be used for any composition and thickness for this system, which will drastically reduce the need for further experimentations to explain diffusion and drying.

Modeling of Triphenyl Phosphate Surfactant Enhanced Drying of Polystyrene/p-Xylene Coatings Using Artificial Neural Network

“…This prediction was based on input variables such as time, the amount of triphenyl phosphate (TPP) used as a surfactant, and the initial thickness of the coating. In a previous study, a regression tree was used for the same system [9]. While an ANN has more parameters than a regression tree, its flexibility allows for capturing complex non-linear relationships.…”

“…Overall, understanding and optimizing the drying mechanism is essential for achieving consistent product quality, energy efficiency, and cost-effective manufacturing. Our previous research groups studied the effect of various surfactants, including anionic, non-ionic, and fluorosurfactants, to minimize the residual solvent and enhance the drying rate of organic and water-based coatings [6][7][8][9]. Triphenyl phosphate (TPP) was used as a plasticizer in one of the studies to modify the drying behavior of the poly(styrene)-p-xylene system in order to minimize the residual solvent [8].…”

“…The amount of plasticizer present significantly impacts the amount of residual solvent left after drying. A machine learning technique based on a regression tree model was also used to develop a drying model for a poly(styrene)-p-xylene system enhanced by triphenyl phosphate as the surfactant [9]. The predictions of the developed model based on regression trees were obtained by MATLAB software (R2014a).…”