Investigating the impact of nano copper on the electrical conductivity of aluminum: A comprehensive study utilizing artificial neural networks
University of California. Santa Cruz, Silicon Valley Extension, Santa Clara, CA.
Research Article
World Journal of Advanced Engineering Technology and Sciences, 2024, 13(01), 937–943.
Article DOI: 10.30574/wjaets.2024.13.1.0389
Publication history:
Received on 27 July 2024; revised on 07 October 2024; accepted on 10 October 2024
Abstract:
Nanotechnology has emerged as a transformative field in material science, offering unprecedented opportunities to enhance the electrical properties of conventional materials through the incorporation of nano-sized particles. In this extensive study, we explore the effects of varying weight percentages (1%, 2%, and 3%) and lengths (30 nm, 60 nm, 150 nm, and 250 nm) of nano copper on the electrical conductivity of aluminum (Al) across different temperatures (20°C, 50°C, and 100°C). Additionally, we investigate the predictive capabilities of Artificial Neural Networks (ANN) in forecasting the electrical conductivity variations of Al based on these parameters. Through a detailed analysis of experimental results and ANN modeling,
Keywords:
ANN; Predictive model; Nano Technology; Electrical Conductivity; Nano particle size
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Copyright © 2024 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0