Development of hydrophobic paper substrates using silane and sol-gel based processes and deriving the best coating technique using machine learning strategies.

ABSTRACT: Low energy surface coatings have found wide range of applications for generating hydrophobic and superhydrophobic surfaces. Most of the studies have been related to use of a single coating material over a single substrate or using a single technique. The degree of hydrophobicity is highly dependent on fabrication processes as well as materials being coated and as such warrants a high-level study using experimental optimization leading to the evaluation of the parametric behavior of coatings and their application techniques. Also, a single platform or system which can predict the required set of parameters for generating hydrophobic surface of required nature for given substrate is of requirement. This work applies the powerful machine learning algorithms (Levenberg Marquardt using Gauss Ne

SUBMITTER: Manoharan K 

PROVIDER: S-EPMC8167096 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature