Preparation of multifunctional Al alloys substrates based on micro/nanostructures and surface modification. (15th May 2017) - Li, Xuewu; Liu, Cong; Shi, Tian; Lei, Yongjie; Zhang, Qiaoxin; Zhou, Chen; Huang, Xingjiu
Abstract: Aluminum alloys (Al alloys) are vulnerable to penetrating and peeling failures in seawater. Preparing a coating to isolate the substrate from corrosive mediums is an effective anticorrosion method. Enlightened by the lotus leaf effect, a liquid-repelling Al alloy surface with enhanced corrosion resistance has been prepared via a facile one-step deposition process. Results indicate that the fabricated flower-like micro/nanostructures with nano-ridges on petals can achieve excellent superamphiphobicity after fluoroalkylsilane modification. The as-prepared surface is also found with good chemical stability. Furthermore, superior anticorrosion behavior of the resultant sample in seawater is investigated by electrochemical tests. Due to trapped air in such structures, the solid-air-liquid interfaces can help to resist the seawater penetration by reducing interface interactions between corrosive ions and the superamphiphobic surface. Finally, an optimized two-layer perceptron artificial neural network (ANN) is set up to model and predict the relationship between preparation conditions and anticorrosion parameters. This work provides a great potential to extend the applications of Al alloys in many areas especially for marine engineering fields. Graphical abstract: Flower-like micro/nanostructures with nano-ridges on petals are attained on Al alloys surfaces by manipulating the one-step electrodeposition process. After fluoroalkylsilane modification, a superamphiphobic surface with good chemical stability is confirmed. Besides, greatly improved corrosion resistance in seawater is also achieved by reducing interface interactions between corrosive ions and resultant surfaces. Highlights: Flower-like micro/nanostructures with nano-ridges on petals are electrodeposited. Fluoroalkylsilane modification renders as-prepared structures superamphiphobicity. Improved corrosion resistance is investigated by electrochemical tests. Effect of deposition conditions on corrosion resistance is modeled by a neural network.