An interpretable boosting-based predictive model for transformation temperatures of shape memory alloys

SH Zadeh, A Behbahanian, J Broucek, M Fan… - Computational Materials …, 2023 - Elsevier
In this study, we demonstrate how the incorporation of appropriate feature engineering
together with the selection of a Machine Learning (ML) algorithm that best suits the available …

Crystallographic and magnetic analysis of ordered-disordered Ni51Mn34Sn15 Heusler alloy obtained by mechanical alloying and annealing

F Popa, V Cebotari, TF Marinca, O Isnard… - Journal of Alloys and …, 2023 - Elsevier
Abstract Ni 51 Mn 34 Sn 15 Heusler alloy was prepared from elemental powders in a high
energy planetary ball mill under argon atmosphere for milling times up to 10 h. Alloy …

Elucidation of annealing effects on austenite–martensite and magnetic phase transitions in Mn2Ni1. 6Sn0. 4 ribbons synthesized from bulk alloys prepared by RF …

A Verma, JD Tanwar, JS Tawale, P Kushwaha… - Journal of Magnetism …, 2024 - Elsevier
We investigate the consequences of annealing on the structure, microstructure, magnetic,
and electrical transport of Mn 2 Ni 1.6 Sn 0.4 ribbons. The 40–60 μm thick ribbons were …

Microstructure, martensitic transformation kinetics, and magnetic properties of (Ni50Mn40In10)100−xCox melt-spun ribbons

A Bekhouche, S Alleg, K Dadda, MI Daoudi… - Journal of Thermal …, 2024 - Springer
The effect of Co-doping on the structure, microstructure, martensitic phase transformation
kinetics, and magnetic properties of the melt-spun (Ni50Mn40In10) 1− xCox (x= 1, 2, and 3) …

Investigation of the crystallization behavior of iron-based metallic glasses for electrical devices

FJ Römer - 2022 - pure.unileoben.ac.at
The ongoing environmental crisis requires a significant reduction in power consumption.
Hysteresis and eddy current losses are the two main types of losses in transformers and …