Collaborative Research: Dynamics of Short Range Order in Multi-Principal Element Alloys

NON-TECHNICAL SUMMARY

Nearly all metals used in practice are alloys, meaning that they are a mixture of different types of metal atoms. Depending on the alloy, different atomic types arrange in either an ordered or disordered way within a crystal. Alloys where the different atoms have a disordered or random arrangement can benefit from improved properties including increased strength or corrosion resistance.

It has recently been proposed that in some disordered alloys the actual atomic arrangement could be more subtle, appearing to be ordered (or non-random) over short distances and disordered over longer distances. This phenomenon, known as short range ordering, is implicated in the exceptional properties of a recently developed group of alloys known as multi-principal element alloys (MPEAs) that have particular promise for next-generation applications in power generation and national defense.

However, one difficulty is that short range ordering remains problematic to measure. This research will use a microscope called an atom probe to detect the types and locations of individual atoms, but with an uncertainty that can make the measurement of subtle ordering inconclusive. Here, artificial intelligence will be used to detect any short range ordering present within the data.

Using this new means of analysis, the project will then test the idea that short range ordering in stable conditions is independent of how the alloy was made. In doing so, this project will have a broad impact on understanding how to engineer short range ordering in alloys by means of their processing, all of which has implications for how MPEAs will develop as next-generation materials.

Alongside the research, artificial intelligence teaching modules will be created to expose and educate middle and high school students in the use of this emerging technology. These will be disseminated through a workshop for secondary school teachers on how to integrate materials-centric examples into physics, chemistry, and physical science classrooms.

TECHNICAL SUMMARY

Multi-principal element alloys (MPEAs), often called high-entropy alloys, are an emerging alloy class with initial evidence of exceptional mechanical properties and significant compositional design flexibility. However, the rational design of MPEAs is hindered by a lack of fundamental knowledge about the chemical short range order (SRO), which are the local correlations in the distribution of atomic species.

This project will characterize the evolution of SRO in a model CrCoNi MPEA to evaluate two hypotheses; first, that SRO in MPEAs reaches a stable state that is independent of the fabrication conditions, and second, that the relaxation time to the stable SRO is governed by diffusion kinetics (which themselves depend on the SRO). Samples will be fabricated by vacuum arc melting, direct current sintering, and high-pressure torsion consolidation to generate measurably different initial SRO states.

SRO characterization will be done by atom probe tomography (APT) cross-correlated with electron scattering for a pair distribution function as well as energy filtered high resolution transmission electron microscopy imaging. The APT datasets will be analyzed by a machine learning approach where the data is modeled as a sample from an underlying pairwise-interaction Markov point process.

Experimental data from a series of isothermal annealing experiments will be used to calibrate a mathematical model for the mutual interactions of the SRO and the self-diffusivity. The model will be used to develop time-temperature-SRO diagrams for MPEAs to be integrated into service. The project is expected to deliver: (1) Maturation of a fundamental scientific understanding of MPEAs’ compositional stability from which these materials can be deployed into service in extreme environments. (2) A robust machine learning APT analysis method that expands the technique to address high solute clustering characteristics in alloys. (3) The development of the next-generation STEM workforce at the graduate level as well as through secondary school teachers via a materials camp that instructs how to incorporate materials into the physics, chemistry, and physical science curriculum.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.