Performance prediction of sintered NdFeB magnet using multi-head attention regression models

Q Liang, Q Ma, H Wu, R Lai, Y Zhang, P Liu, T Qi - Scientific Reports, 2024 - nature.com
The preparation of sintered NdFeB magnets is complex, time-consuming, and costly. Data-
driven machine learning methods can enhance the efficiency of material synthesis and …

Machine Learning Application for Functional Properties Prediction in Magnetic Materials

VA Milyutin, NN Nikulchenkov - Physics of Metals and Metallography, 2024 - Springer
Machine learning (ML) has proven to be a powerful tool, significantly speeding up and
simplifying the development of new materials while enhancing their functional …

Synthetic dual image generation for reduction of labeling efforts in semantic segmentation of micrographs with a customized metric function

MOV Stern, D Hohs, A Jansche… - arxiv preprint arxiv …, 2024 - degruyter.com
Training of semantic segmentation models for material analysis requires micrographs as the
inputs and their corresponding masks. In this scenario, it is quite unlikely that perfect masks …

[HTML][HTML] A data-driven approach to predict the saturation magnetization for magnetic 14: 2: 1 phases from chemical composition

AK Choudhary, D Hohs, A Jansche, T Bernthaler… - AIP Advances, 2024 - pubs.aip.org
14: 2: 1 phases enable permanent magnets with excellent magnetic properties. From an
application viewpoint, saturation polarization, Curie temperature, and anisotropy constant …

Synthetic dual image generation for reduction of labeling efforts in semantic segmentation of micrographs with a customized metric function

MO Volman Stern, D Hohs, A Jansche… - Methods in …, 2024 - degruyter.com
Training of semantic segmentation models for material analysis requires micrographs as the
inputs and their corresponding masks. In this scenario, it is quite unlikely that perfect masks …