Presentation Information
[O13-1]Thin film combinatorial studies of hard magnetic magnetic materials
*Nora M. Dempsey1 (1. Institut Néel, CNR (France))
Keywords:
High throughput experimentation,ML-driven data analysis
Combinatorial studies based on the preparation and characterisation of compositionally graded thin films are being used for the screening and optimization of a range of functional materials, including hard magnetic materials [1,2]. When combined with Machine Learning (ML), such high-throughput film-based studies hold much potential to guide data driven design of new materials [3,4]. In this talk I will present our on-going studies of the effect of element substitution and annealing conditions on both structural and magnetic properties of compositionally graded RE-TM films based on different high anisotropy phases. I will then outline recent developments around high throughput characterisation as well as data handling and analysis. I will finish up by briefly outlining the potential of combining high throughput experimentation and ML-driven data analysis for the accelerated development of functional magnetic materials with reduced dependence on critical elements [5].
[1] ML Green et al., J. Appl. Phys. 113 (2013) 231101
[2] Y. Hong et al., J. Mater. Res. Technol. 18 (2022) 1245
[3] A.G. Kusne et al. Sci. Rep. 4 (2014) 6367
[4] A. Ludwig, npj Comput. Mater. 5 (2019) 70
[5] Kovacs et al., Front. Mater. 9 (2023) 1094055
[1] ML Green et al., J. Appl. Phys. 113 (2013) 231101
[2] Y. Hong et al., J. Mater. Res. Technol. 18 (2022) 1245
[3] A.G. Kusne et al. Sci. Rep. 4 (2014) 6367
[4] A. Ludwig, npj Comput. Mater. 5 (2019) 70
[5] Kovacs et al., Front. Mater. 9 (2023) 1094055