Lab scale additive manufacturing of Fe-Nd-B based powders was performed to realize bulk nanocrystalline Fe-Nd-B based permanent magnets. For fabrication a special inert gas process chamber for laser powder bed fusion was used. Inspired by the nanocrystalline ribbon structures, well-known from melt-spinning, the concept was successfully transferred to the additive manufactured parts. For example, for Nd16.5-Pr1.5-Zr2.6-Ti2.5-Co2.2-Fe65.9-B8.8 (excess rare earth (RE) = Nd, Pr; the amount of additives was chosen following Magnequench (MQ) powder composition) a maximum coercivity of µ0Hc = 1.16 T, remanence Jr = 0.58 T and maximum energy density of (BH)max = 62.3 kJ/m3 have been achieved. The most important prerequisite to develop nanocrystalline printed parts with good magnetic properties is to enable rapid solidification during selective laser melting. This is made possible by a shallow melt pool during laser melting. Melt pool depths as low as 20 to 40 µm have been achieved. The printed bulk nanocrystalline Fe-Nd-B based permanent magnets have the potential to realize magnets known so far as polymer bonded magnets without polymer.
29 November 2018 in Physica Status Solidi (RRL) – Rapid Research Letters
Permanent magnets based on FePrCuB were realized on a laboratory scale through additive manufacturing (laser powder bed fusion, L-PBF) and book mold casting (reference). A well-adjusted two-stage heat treatment of the as-cast/as-printed FePrCuB alloys produces hard magnetic properties without the need for subsequent powder metallurgical processing. This resulted in a coercivity of 0.67 T, remanence of 0.67 T and maximum energy density of 69.8 kJ/m3 for the printed parts. While the annealed book-mold-cast FePrCuB alloys are easy-plane permanent magnets (BMC magnet), the printed magnets are characterized by a distinct, predominantly directional microstructure that originated from the AM process and was further refined during heat treatment. Due to the higher degree of texturing, the L-PBF magnet has a 26% higher remanence compared to the identically annealed BMC magnet of the same composition.
The TM14RE2B-based phases (TM = transition metal, RE = rare earth metal; hereafter called 14:2:1) enable permanent magnets with outstanding magnetic properties. Novel chemical compositions that represent new 14:2:1 phases necessitate that they do not demagnetize at application-specific operating temperatures. Therefore, an accurate knowledge of the Curie temperature (Tc) is important. For magnetic 14:2:1 phases, we present a machine learning model that predicts Tc by using merely chemical compositional features. Hyperparameter tuning on bagging and boosting models, as well as averaging predictions from individual models using the voting regressor, enables a low mean-absolute-error of 16 K on an unseen test set. The training set and a test set have been constructed by randomly splitting, in an 80:20 ratio, of a database that contains 449 phases (270 compositionally unique) mapped with their Tc, taken from distinct publications. The model correctly identifies the relative importance of key substitutional elements that influence Tc, especially in an Fe base such as Co, Mn, and Al. This paper is expected to serve as a basis for accurate Curie temperature predictions in the sought-after 14:2:1 permanent magnet family, particularly for transition metal substitution of within 20% in an Fe or Co base.