Abstract
Cu-rich cell boundary phase is difficult to pre-cipitate evenly,resulting in a generally poor demagneti-zation curve squareness for Fe-rich Sm2Co17-type magnet,which is a key factor limiting the further improvement of magnetic energy product.In this study,we report that nanoscale strip-like ordered micro-domains distributed in 1∶7H disordered matrix phase of the solid solution pre-cursor is a new factor significantly affecting the precipi-tation and distribution of the cell boundary phase.Long strip-like and continuous micro-twin structure with twin boundaries neatly perpendicular to the C-axis is observed after sintering treatment.After solution treatment,sequential and long strip-like micro-twins gradually trans-form into disordered state along the basal plane,forming narrow disordered 1∶7H(TbCu7-type structure)phase between the separated strip-like ordered micro-domains.This disordering transformation takes place via broken down of the long strip-like ordered micro-domains,which is accomplished by narrowing along the width direction followed by reduction of the length.Furthermore,a new model revealing the effect of the ordered micro-domains on the formation of the cell boundary phase is proposed.Antiphase boundaries enriched in Cu have already existed in the precursor with long strip-like ordered micro-do-mains.Therefore,the Cu-rich cell boundary phase acting as strong pinning centers cannot be precipitated homoge-neously and distributed continuously after aging,resulting in a poor demagnetization curve squareness of Sm2Co17-type magnet.Our results indicate that significant broken down of the nanoscale ordered micro-domains in solution precursor is the key factor improving the distribution of cell boundary phase in Sm2Co17-type magnets.
基金项目
National Key R&D Program of China(2021YFB3503102)
Zhejiang Provincial Key R&D Program(2021C01191)
Science and Technology Innovation 2025 Major Project of Ningbo(2020Z037)
Ningbo Key R&D Program(20222ZDYF020027)
Ningbo Natural Science Foundation(2021J216)
NETL
NSTL
万方数据