Designing of high entropy alloys with high hardness: a metaheuristic approach

Abstract

The near-infinite compositional space of high-entropy-alloys (HEAs) is a huge resource-intensive task for developing exceptional materials. In the present study, an algorithmic framework has been developed to optimize the composition of an alloy with chosen set of elements, aiming to maximize the hardness of the former. The influence of phase on hardness prediction of HEAs was thoroughly examined. This study aims to establish generalized prediction models that aren’t confined by any specific set of elements. We trained the HEA identification model to classify HEAs from non-HEAs, the multi-labeled phase classification model to predict phases of HEAs also considering the processing route involved in the synthesis of the alloy, and the hardness prediction model for predicting hardness and optimizing the composition of the given alloy. The purposed algorithmic framework uses twenty-nine alloy descriptors to compute the composition that demonstrates maximum hardness for the given set of elements along with its phase(s) and a label stating whether it is classified as HEA or not.

Predictive analytics of wear performance in high entropy alloy coatings through machine learning

“…Similar to ML, Deep Learning (DL) has also proved to be an effective prediction method rooted in the datadriven approach [16,18]. Among the two methods, ML is mostly preferred for structured data, due to its exceptional ability to detect complex patterns.…”

“…DL is a subset of ML, that utilizes neural networks to solve complex problems [20]. DL requires large volumes of data and more computational resources for training complex models compared to ML methods [18,21,22]. Recent advances in ML for predicting tribological properties of HEAs, such as wear, and friction characteristics have created new prospects in material science.…”

First-principles calculations of mechanical properties of TiZrNbTaMo series biological refractory high-entropy alloys

“…High-entropy alloys (HEAs) 1,2 break the traditional concept of single-principal element design by focusing on configurational entropy rather than mixing enthalpy. This approach creates multi-principal metallic materials with excellent mechanical, physical, and chemical properties, expanding the potential for new material development [3][4][5] . In biomedical implant materials, HEAs have a hardness similar to bone, higher specific strength, better corrosion and wear resistance.…”