No abstract

In this study, iron titanate (FT) and manganese‐doped iron titanate (MFT) nanoparticles were synthesised from a natural mineral, ilmenite ore, using a simple and effective method. X‐ray diffraction analysis confirmed the reduction of crystallite size from 56 to 29 nm with an increase in Mn doping concentration from 0% to 2%. Doping of Mn transformed the agglomerated fine particles into nanosphere‐like morphology with dimensions less than 200 nm. Magnetization studies revealed that FT and MFT were hard ferrimagnetic materials, and beyond 0.8% Mn dopant concentration, reduction in magnetic saturation value of 1.46–1.41 emu g−1 was observed. Resistivity of FT decreased from ≈19 to ≈2 K Ω‐cm with doping Mn and tuning of such electrical property through doping concentration can lead to their application in fabricating spintronic devices. This work suggests a new pathway to synthesise magnetic–semiconducting nanostructures at large scale and in an environment friendly manner from ilmenite ore.

No abstract

MRSI is a non-invasive in-vivo technique for mapping tissue concentrations in clinical and neuro-scientific research. Although, in vivo MRSI has made progress with respect to spatial resolution, acquisition time and the number of detectable metabolites; frequency and phase drifts in the acquired data are still a persisting problem, resulting in SNR losses, broadening of spectral peaks and deformities in line spectra of metabolites. In this abstract, we show how rosette MRSI sampling trajectories offer the possibility to perform frequency and phase drift correction which is otherwise not possible to do in most other commonly used cartesian and non-cartesian sampling trajectories.

Purpose Frequency drift correction is an important postprocessing step in MRS that yields improvements in spectral quality and metabolite quantification. Although routinely applied in single‐voxel MRS, drift correction is much more challenging in MRSI due to the presence of phase‐encoding gradients. Thus, separately acquired navigator scans are normally required for drift estimation. In this work, we demonstrate the use of self‐navigating rosette MRSI trajectories combined with time‐domain spectral registration to enable retrospective frequency drift corrections without the need for separately acquired navigator echoes. Methods A rosette MRSI sequence was implemented to acquire data from the brains of 5 healthy volunteers. FIDs from the center of k‐space (k=0$$ k=0 $$ FIDs) were isolated from each shot of the rosette acquisition, and time‐domain spectral registration was used to estimate the frequency offset of each k=0$$ k=0 $$ FID relative to a reference scan (the first k=0$$ k=0 $$ FID in the series). The estimated frequency offsets were then used to apply corrections throughout k$$ k $$‐space. Improvements in spectral quality were assessed before and after drift correction. Results Spectral registration resulted in significant improvements in signal‐to‐noise ratio (12.9%) and spectral linewidths (18.5%). Metabolite quantification was performed using LCModel, and the average Cramer‐Rao lower bounds uncertainty estimates were reduced by 5.0% for all metabolites, following field drift correction. Conclusion This study demonstrated the use of self‐navigating rosette MRSI trajectories to retrospectively correct frequency drift errors in in vivo MRSI data. This correction yields meaningful improvements in spectral quality.