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[HTML][HTML] Data-driven design of high bulk modulus high entropy alloys using machine learning
In the current research, machine learning (ML) models were used as a tool for predicting the
bulk modulus of High Entropy Alloys (HEAs). ML was employed to optimize HEA …
bulk modulus of High Entropy Alloys (HEAs). ML was employed to optimize HEA …
A Comprehensive Review on Hot Deformation Behavior of High-Entropy Alloys for High Temperature Applications
In contrast to conventional alloys, multicomponent high-entropy alloys (HEAs) have
emerged as promising candidates in the field of advanced materials because of their unique …
emerged as promising candidates in the field of advanced materials because of their unique …
Machine learning approaches for predicting and validating mechanical properties of Mg rare earth alloys for light weight applications
In this work, we have attempted to predict the mechanical behaviour of light weight Mg
based rare earth alloys fabricated through different mechanical and thermal processes. Our …
based rare earth alloys fabricated through different mechanical and thermal processes. Our …
[HTML][HTML] Development of robust machine learning models for predicting flexural strengths of fiber-reinforced polymeric composites
Fiber-reinforced composites are widely used in engineering applications due to their
excellent physical and chemical properties. However, evaluating their flexural properties …
excellent physical and chemical properties. However, evaluating their flexural properties …