The paper presents a scaling approach to the analysis of coercivity. The Widom-based procedure of coercivity scaling has been tested for non-oriented electrical steel. Due to insufficient results, the scaling procedure was improved relating to the method proposed by Van den Bossche. The modified procedure of coercivity scaling gave better results, in comparison to the original approach. The influence of particular parameters and a range of measurement data used in the estimations on the final effect of the coercivity scaling were discussed.

Despite of extensive researches for decades, there are many unclear aspects for recrystallization phenomenon in the cold rolled Ni-based alloys. Hence, different thermal cycles were conducted in order to determine microstructural evolutions and its effect on the magnetic and mechanical properties of a 90% cold-rolled thin sheet of a Ni-Fe-Cu-Mo alloy (~80 μm). The obtained results revealed that the recrystallization was started at a temperature of 550°C and was completed after 4 hours. An increase in the number of annealing twins was observed with an increase in annealing temperature, which was due to a bulging and long-range migration of grain boundaries during the discontinuous recrystallization. Ordering transformation occurred in the temperature range of 400-600°C and as a result, hardness, yield strength, and UTS were increased, while with an increase in the annealing temperature these mechanical properties were decreased. Maximum toughness was obtained by annealing at 550°C for 4 hours, while the highest elongation was obtained after annealing at 1050°C, where other mechanical properties including toughness, hardness, yield strength, and UTS were decreased due to the grain growth and secondary recrystallization. Moreover, coercivity and remanence magnetization were decreased from 4.5 Oe and 3.8 emu/g for the cold rolled sample to below 0.5 Oe and 0.15 emu/g for the sample annealed at 950°C, respectively.

We investigated the effect of pre-sintering process on the penetration behavior of Dy in a NdFeB sintered magnet which was grain boundary diffusion treated with Cu/Al mixed Dy source. The pre-sintering of a magnet was performed at 900oC in vacuum and then the pre-sintered body was dipped in the solutions of DyH2, DyH2 + Cu, and DyH2 + Al, respectively. The dipped pre-sintered body were then fully sintered 4 hours at 1060oC followed by a subsequent annealing. The pre-sintering apparently improved the diffusivity of Dy atoms. The penetration of Dy into the magnet extended almost to 2,000 μm from the surface, about four times deeper than that of the normally sintered and diffusion treated one, when the DyH2 + Al solution was used as a Dy source. However, the resulting increase of coercivity was about 4 kOe, somewhat lower than that of the normally treated one, mostly due to excessive oxide formation that hindered to make a continuous Nd-rich grain boundary phase and a core-shell type structure.

Artificial intelligence operated with machine learning was performed to optimize the amount of metalloid elements (Si, B, and P) subjected to be added to a Fe-based amorphous alloy for enhancement of soft magnetic properties. The effect of metalloid elements on magnetic properties was investigated through correlation analysis. Si and P were investigated as elements that affect saturation magnetization while B was investigated as an element that affect coercivity. The coefficient of determination R2 (coefficient of determination) obtained from regression analysis by learning with the Random Forest Algorithm (RFR) was 0.95 In particular, the R2 value measured after including phase information of the Fe-Si-B-P ribbon increased to 0.98. The optimal range of metalloid addition was predicted through correlation analysis method and machine learning.