Due to their high strength and thermal stability, refractory complex concentrated alloys (RCCA) can be used in applications where components are exposed to extreme conditions. However, a thorough understanding of their properties and behavior during operation is necessary before they can be implemented. A team of scientists from the NOMATEN Centre of Excellence and Materials Research Laboratory at NCBJ combined experimental methods with computer simulations to study the MoTaW alloy.

The latest findings were published in the International Journal of Refractory Metals and Hard Materials, DOI: https://doi.org/10.1016/j.ijrmhm.2026.107772 

Refractory complex concentrated alloys (RCCA) typically consist of three or more high-melting-point metals, known as refractory metals. These include, for example, molybdenum, tantalum, tungsten, niobium, and hafnium. The crystalline structure of the material formed by their combination causes RCCA alloys to exhibit greater strength at high temperatures than traditional refractory alloys. They are therefore an excellent material for use in applications where components are exposed to very high temperatures.

A significant portion of existing research focuses on RCCA alloys containing niobium. Recently, scientists’ attention has turned to another candidate – the MoTaW alloy, composed of three elements. The high hardness and stability of this material have already been confirmed. However, its deformation under complex load is still not sufficiently well understood.

A group of specialists from the NOMATEN Centre of Excellence and Materials Research Laboratory at NCBJ undertook a detailed investigation of this property. The researchers combined an experimental approach – specifically nanoindentation testing – with computer modeling using machine learning methods. – Atomistic simulations are a powerful tool for understanding the relationships between composition, structure, and properties in complex alloys. However, for materials such as RCCS alloys, it is essential to know the potential describing the interactions between individual atoms. A new approach in this area is the use of machine learning, where the algorithm does not assume the form of the potential but learns it based on quantum mechanics – explains dr hab. Francisco Javier Dominguez Gutierrez, prof. NCBJ, the first author of the recently published paper.

In their work, the researchers used a method that allows for a precise understanding of the material’s properties while not being computationally intensive, which is often a challenge in large-scale simulations. This method has already proven effective for other RCCS alloys, making it applicable to the niobium-free alloy as well.

The research focused particularly on the mechanisms of deformation under contact loading. Both experimental measurements using the nanoindentation method and computer simulations yielded very similar results. – The work showed that the mechanism of plastic deformation in the MoTaW alloy strongly depends on the orientation of the crystalline structure, and the evolution of the resulting dislocations is crucial in the process of indentation-induced hardening. It is also important that our research has demonstrated the potential of simulations using machine learning to investigate the properties of complex RCCS alloys – concludes the author of the publication.

Materials research and the search for new alloys designed for extreme conditions will enable the development of many technologies, including nuclear and thermonuclear technologies. Such work also allows us to harness the potential of modern computational methods to obtain precise results with reduced computational resources.
The experimental part of the research was partially funded by the National Science Centre (NCN), grant number MINIATURA-7 2023/07/X/ST11/00862.