Matrix microstructure and texture controlling is an important way to optimize Goss ({110}) abnormal grain growth (AGG) in high magnetic induction grain-oriented silicon (Hi-B) steel during primary recrystallization. In the present work, a matrix with homogeneous grain size and favorable texture components was obtained through two-stage normalized annealing followed by primary recrystallization. Furthermore, secondary recrystallization was performed for sharp Goss orientation by slow heating and purified annealing. It was found that plenty of island grains, which occurred and disappeared gradually, accompanied the process of AGG. Through analyzing the evolution of microstructure and texture, we realized that the formation of island grains was related to the large-size grains in matrix, and the elimination of that was attributed to the special grain boundaries which satisfied both coincident site lattice (CSL) and high-energy (HE) models. It was essential to control grain size and favorable orientations in matrix comprehensively for the high-efficient abnormal growing of sharp Goss orientation, through which excellent magnetic properties could be obtained simultaneously.

Quasi in situ observations of the early stage of secondary recrystallization in Fe-3.25 wt.% Si high-permeability grain-oriented silicon steel indicate that large matrix grains locally impede the migration of secondary recrystallized grain boundaries. A critical grain-size criterion for identifying potential pinning grains is proposed, and a kinetic model incorporating the matrix grain-size distribution is developed. For the abnormal grain tracked at 1000 °C, the measured grain-size increment over 100 s was approximately 60 μm; the proposed pinning model predicted 47 μm, whereas the weighted-average model predicted 171 μm. Model calculations further suggest that matrix grain-size dispersion, pinning force, grain size, and relative grain-boundary energy jointly affect the early-stage growth of Goss grains. These results provide a framework for interpreting early secondary-recrystallization kinetics, while broader experimental validation is still required before the predicted parameter combinations can be used for process control.