PREDICTING THE PROPERTIES OF NOVEL METAL-COMPOSITE MATERIALS USING ARTIFICIAL INTELLIGENCE
Abstract
The development of novel metal-composite materials requires extensive experimentation to determine their mechanical, thermal, and chemical properties. Traditional methods involve costly and time-consuming laboratory testing, which can significantly delay the material design process. This study explores the application of artificial intelligence (AI) to predict material properties based on composition and processing parameters, reducing reliance on physical experimentation. Machine learning (ML) models, including artificial neural networks (ANNs) and support vector machines (SVMs), were trained using extensive material datasets. The results indicate that AI models can accurately predict key properties such as tensile strength, hardness, and thermal conductivity, thereby accelerating material development and reducing research costs..
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