ANN prediction of corrosion behaviour of uncoated and biopolymers coated cp-Titanium substrates

Abstract

The present study focuses on biopolymer surface modification of cp-Titanium with Chitosan, Gelatin and Sodium Alginate. The biopolymers were spin coated onto cp-Titanium substrate and further subjected to Electrochemical Impedance Spectroscopic (EIS) characterisation. Artificial Neural Network (ANN) was developed to predict the Open Cicuit Potential (OCP) values and Nyquist plot for bare and bioploymer coated cp-Titanium substrate. The experimental data obtained was utilised for ANN training. Two input paramters, i.e., substrate condition (coated or uncoated) and time period were considered to predict the OCP values. Back propogation Levenberg-Marquardt training algorithm was utilised in order to train ANN and to fit the model. For Nyquist plot, the network was trained to predict the imaginary impedance based on real impedance as a function of immersion periods using the Back Propagation Bayesian algorithm. The biopolymer coated cp-Titanium substrate shows the enhanced corrosion resistance compared to uncoated substrtaes. The ANN model exhibits excellent comparsion with the experimental results in both the cases indicating that the developed model is very accurate and efficiently predicts the OCP values and Nyquist plot.

TO/TMMP-TMTGE Double-Healing Composite Containing a Transesterification Reversible Matrix and Tung Oil-Loaded Microcapsules for Active Self-Healing

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Synthesis and structures of divalent Co, Ni, Zn and Cd complexes of mixed dichalcogen and dipnictogen ligands with corrosion inhibition properties: experimental and computational studies

“…The observed slight initial uctuation of OCP can be attributed to the delayed dissolution of iron oxide layers (Fe 2 O 3 and Fe 3 O 4 ) that pose as the native protective oxide layers for the steel, and formation of defensive lms by the studied complexes in the electrolytic medium. 55 At complete dissolution of the oxide layers and adsorption of studied molecules on the steel surface, the steady-state potential becomes relatively stable. The OCPs of the systems are generally stable with differentials not more than 3 mV over the entire 30 min waiting period, suggesting that the systems had assumed a sufficiently stable OCP before electrochemical perturbation.…”

Deep learning with digital holographic microscopy discriminates apoptosis and necroptosis

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