Investigating the impact of nano copper on the electrical conductivity of aluminum: A comprehensive study utilizing artificial neural networks

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,

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Publication Details

Journal
World Journal of Advanced Engineering Technology and Sciences
Published
2024-10-20
DOI
https://doi.org/10.30574/wjaets.2024.13.1.0389
Citations
1
Primary Topic
Anodic Oxide Films and Nanostructures
Type
article
Field-Weighted Citation Impact
0.12
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article

Investigating the impact of nano copper on the electrical conductivity of aluminum: A comprehensive study utilizing artificial neural networks

Ali Bahadori manizani, Leila Shafieian
1 citations
World Journal of Advanced Engineering Technology and Sciences
Anodic Oxide Films and Nanostructures
0.12
article

Investigating the impact of nano copper on the electrical conductivity of aluminum: A comprehensive study utilizing artificial neural networks

Ali Bahadori manizani, Leila Shafieian
article en
1 citations

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,

World Journal of Advanced Engineering Technology and SciencesVol. 13(1)
Openalex Percentile: Top 59%
Anodic Oxide Films and Nanostructures
0.12
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