Modelling radiation resistant low activation High Entropy Alloys

Lead Research Organisation: Science and Technology Facilities Council
Department Name: Scientific Computing Department

Abstract

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Description A key achievement so far in this award is the development of a new approach for predicting high-temperature properties of high entropy alloys. The method has been applied to TaVCrW, with the resulting manuscript published in Physical Review B. Results using the approach have also been obtained for other compositions, and are also being developed into publications. The new method makes important advances in computational efficiency, while maintaining a high level of accuracy, and is well positioned for thermodynamic property prediction and high-throughput screening of other high entropy alloys.

In a separate study ( https://www.nature.com/articles/s41524-023-01073-w ) we have investigated the relative merits of different machine-learning methodologies in predicting technologically relevant properties of high entropy alloys, including moment tensor potentials, neural networks, and a study of the relevance and efficacy of active-learning in both of these approaches.

In another study, funded through this award, we delved into the behavior of the high entropy alloy TaTiVW when exposed to radiation, an essential consideration for its application in nuclear reactor structures. Through cutting-edge computational simulations, we uncovered that for TaTiVW radiation not result in formation of voids, such as occur in for example iron, which can lead to material degradation over time. Although further studies are needed to further explore this finding, these insights suggest that TaTiVW is potentially radiation resistant, offering promising prospects for developing more robust and sustainable nuclear reactors. The study is currently being written up as an article.
Exploitation Route High entropy alloys, and multi-principle component alloys in general, span a vast compositional space. Our new approach-- which provides a method for screening large numbers of compositions without sacrificing accuracy --will be of direct benefit to researchers in the modelling of high entropy alloys. Another key outcome was the development of interatomic potential optimization algorithms which can be leveraged in future work to study defect dynamics and to perform cascade simulations to screen materials for high radiation damage. Finally, discovering potential radiation resistance in TaTiVW could be a key finding which, on further study, has the potential to lead to development of new materials for advanced nuclear structural applications.
Sectors Aerospace

Defence and Marine

Energy
 
Description Our direct up-sampling methodology is freely available for academic use, and will accelerate the screening of new high entropy alloys for technological applications, including nuclear. Over the coming years we expect to see the benefits from this enabling technology within industry, through the development of new materials and and improved understanding of atomistic processes underpinning their properties. Society will benefit in the longer-term through development of next-generation fission and fusion reactors, providing a secure and clean source of energy.
First Year Of Impact 2023
 
Title Accelerated TU-TILD scheme for high-throughput determination of high-temperature properties of high entropy alloys 
Description Our new accelerated TU-TILD model draws together several innovations over the 'vanilla' TU-TILD, including a machine-learning interatomic potential-based approach, and a new technique known as 'direct up-sampling' which removes the need for a subset of expensive density functional theory calculations. Our new approach has been validated on TaVCrW, and is well positioned for thermodynamic property prediction and high-throughput screening of other high entropy alloys. 
Type Of Material Computer model/algorithm 
Year Produced 2021 
Provided To Others? No  
Impact The model has been developed and applied to TaVCrW, with the resulting manuscript published in Physical Review B. 
URL https://journals.aps.org/prb/abstract/10.1103/PhysRevB.105.214302
 
Title Interatomic potentials to model TaVCrW; development of methodologies to compute thermodynamic properties 
Description Mathematical models (machine-learned moment tensor potentials) have been developed to describe the high temperature vibrations of TaVCrW. 
Type Of Material Computer model/algorithm 
Year Produced 2020 
Provided To Others? No  
Impact Within the TU-TILD approach these models enable the calculation of thermodynamic properties of high entropy alloys up to the melting point. These high temperature calculations will enable the prediction of properties such as heat capacity, thermal expansion, and thermal conductivity, as a function of composition. Such calculations will guide experimental work; accelerating the screening of the huge compositional space of high entropy alloys. The application of these models in accessing non-stochiometric HEA compositions will be explored in the forthcoming paper, "Thermodynamic properties up to the melting point of refractory multi-component alloys using machine-learning potentials", to be submitted to Physical Review B. 
 
Description Collaboration with Roger Smith, Pooja Goddard, and Ying Zhou, Loughborough University 
Organisation Loughborough University
Country United Kingdom 
Sector Academic/University 
PI Contribution The EPSRC project is based on a collaboration between myself, at Daresbury Laboratory, STFC, and Roger Smith and Pooja Goddard at Loughborough University. Ying is the postdoctoral fellow in this project, and my contribution is to supervise Ying in her calculations of the thermodynamic properties of high entropy alloys.
Collaborator Contribution My partners at Loughborough University provide complementary expertise in computational material science, and support for postdoctoral researcher Ying Zhou, who is based at Loughborough.
Impact The collaboration has led to computational material science research soon to be published in peer-reviewed journals. The results of this research have been presented in two invited talks by myself in 2020, at the Thomas Young Centre ( https://www.thomasyoungcentre.org/events/multi-scale-modelling-of-alloys-high-entropy-alloys-heas-and-molten-salts-using-meamfit-and-high-temperature-properties/ ), and the Nuclear Institute ( https://www.nuclearinst.com/write/MediaUploads/NI_Modelling_Seminar_Brochure.pdf )
Start Year 2019
 
Description Invited talks to present research at Imperial College and the Nuclear Institute 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Invited talks given at the Thomas Young Centre ( https://www.thomasyoungcentre.org/events/multi-scale-modelling-of-alloys-high-entropy-alloys-heas-and-molten-salts-using-meamfit-and-high-temperature-properties/ ) and the Nuclear Insitute ( https://www.nuclearinst.com/write/MediaUploads/NI_Modelling_Seminar_Brochure.pdf ) to disseminate research findings and raise the profile of the project.
Year(s) Of Engagement Activity 2020
 
Description Scientific talks to disseminate research outcomes and raise profile of project 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Invited talk at Stuttgart University ( https://www.imw.uni-stuttgart.de/en/news/news/Materials-Science-Colloquium-Summer-Semester-2021-00005/ ), and talk at 2nd World Congress on High Entropy Alloys (HEA 2021), providing opportunity to disseminate our calculations of high temperature properties of TaVCrW, and our new methodology using machine-learning potentials to accelerate the efficiency of these calculations.
Year(s) Of Engagement Activity 2021
URL https://www.imw.uni-stuttgart.de/en/news/news/Materials-Science-Colloquium-Summer-Semester-2021-0000...