Tailoring texture of γ-Y2Si2O7 by strong magnetic field alignment and two-step sintering

In this study, a well-dispersed γ-Y2Si2O 7 ethanol-based suspension with 30 vol% solid loading was prepared by adding 1 dwb% polyethylene imine dispersant, which allows feeble magnetic γ-Y2Si2O7 particles with anisotropic magnetic susceptibility to rotate in a 12 T strong magnetic field during slip casting, resulting in the development of a strong texture in green bodies. Pressureless sintering gives rise to more pronounced grain growth in the textured sample than in the untextured sample prepared without the magnetic field due to the rapid migration of the grain boundaries of the well-oriented grains, which was revealed by constant-heating-rate sintering kinetics. It was found that the use of two-step sintering is very efficient not only for inhibiting the grain growth but also for enhancing the texture. This implies that controlled grain growth is crucial for enhancing texture development in γ-Y2Si2O7.

Characterization of anomalous relaxation using the time-fractional Bloch equation and multiple echo T2 *-weighted magnetic resonance imaging at 7T

PURPOSE To study the utility of fractional calculus in modeling gradient-recalled echo MRI signal decay in the normal human brain. METHODS We solved analytically the extended time-fractional Bloch equations resulting in five model parameters, namely, the amplitude, relaxation rate, order of the time-fractional derivative, frequency shift, and constant offset. Voxel-level temporal fitting of the MRI signal was performed using the classical monoexponential model, a previously developed anomalous relaxation model, and using our extended time-fractional relaxation model. Nine brain regions segmented from multiple echo gradient-recalled echo 7 Tesla MRI data acquired from five participants were then used to investigate the characteristics of the extended time-fractional model parameters. RESULTS We found that the extended time-fractional model is able to fit the experimental data with smaller mean squared error than the classical monoexponential relaxation model and the anomalous relaxation model, which do not account for frequency shift. CONCLUSIONS We were able to fit multiple echo time MRI data with high accuracy using the developed model. Parameters of the model likely capture information on microstructural and susceptibility-induced changes in the human brain.