Artificial intelligence based analysis of nanoindentation load–displacement data using a genetic algorithm

Burleigh, Abraham; Lau, Miu Lun; Burrill, Megan; Olive, Daniel T.; Gigax, Jonathan; Li, Nan; Saleh, Tarik A.; Pellemoine, Frédérique; Bidhar, Sujit; Long, Min; Ammigan, Kavin; Terry, Jeff

doi:10.1016/j.apsusc.2022.155734

Cited by 6 publications

(1 citation statement)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This approach provides valuable data to evaluate the mechanical behavior of the films and to improve their suitability for specific applications. The interaction between the indenter and the film surface was sim- [38].…”

Section: Instruments and Methodsmentioning

confidence: 99%

Effect of deposition time on properties of the ZnO by USD Method

Madaoui,

Azibi,

Djabrouhou

et al. 2024

Rev. Mex. Fís.

View full text Add to dashboard Cite

This investigation aims to improve the properties of 304 L stainless steel (SS) substrates for use in corrosion, mechanical, and biomedical applications by depositing ZnO thin films. The ultrasonic spraying technique was used to prepare ZnO thin films with depositional times of 1, 4, and 9 minutes. XRD and Raman studied the surface characteristics of ZnO samples. XRD analysis revealed a hexagonal structure with an average crystallite size of 22 nm for ZnO. Indentation nano measurements indicated an increase in the hardness of the films examined. To determine the type of conductivity and estimate the charge carrier density, potentiodynamic polarization, electrochemical impedance spectroscopy (EIS), and Mott-Schottky analysis were performed. The thin film deposited for 9 minutes was found to be the most effective in improving corrosion resistance.

show abstract

Section: Instruments and Methodsmentioning

confidence: 99%