Idler coil inductively couples to parent coil to create double resonance circuit while eliminating lead inductance losses.
A magnetic resonance imaging apparatus calculates temperature and accuracy from dual-substance spectra in a single measurement.
A TD-NMR method determines component quantities in solid mixtures using T1 saturation recovery curves and linear combination fitting.
A miniature stochastic nuclear magnetic resonance system uses active shims to correct bias field inhomogeneity for precise spin density measurement.
A reconstruction device shifts readout points in k-space to correct gradient switching dilatation artifacts.
Optimized saddle coil assembly produces uniform magnetic fields for precise magic angle adjustment in solid-state NMR systems.
An external standard reference system inserts containers with known metabolites into the MRI coil to enable precise quantitative analysis.
Symmetrical multi-banded RF pulses saturate bound water spins without increasing direct saturation of mobile water, reducing preparation time.
Adiabatic tip-down and matched flip-back pulses separate mobile and bound spin pools, resolving inadequate tissue-blood contrast from phase dispersion.
Organic base additives shift NMR signals to separate overlapping terephthalic acid peaks, resolving measurement precision issues in molecular weight analysis.
Iteratively updating initial radiofrequency pulse profiles on an optimal phase surface resolves hardware limitations in magnetic resonance experiments.
Nuclear quadrupole resonance signals undergo frequency modulation via time-varying magnetic fields to identify target chemical nuclei.
Error lookup tables automate spectroscopic quantification by replacing iterative calculations with pre-computed values.
A subspace imaging framework reconstructs high-resolution magnetic resonance spectra using learned spectral features and ultrashort echo time acquisitions.
Conductive heating of dry food samples enables rapid time-domain NMR measurements without altering chemical structures.
Machine learning models replace manual pipelines to improve metabolite quantification accuracy despite increased processing complexity.
A quantitative nuclear magnetic resonance method determines protein concentration using diffusion filters to eliminate water and formulation component resonances.
A 3D radial spoiled GRE imaging technique uses frequency-modulated hyperbolic-secant pulses to enable ultra-short echo times.
A multi-dimensional NMR method uses PSYCHE elements and EPSI readout to extract scalar coupling constants from proton networks.
An unsupervised neural network learns optimal regularization parameters from unlabeled NMR relaxation signals to produce accurate time spectra.