Recent advances in ultra-low field MRI have attracted attention from both academic and industrial MR communities for its potential in democratizing MRI applications. One of the most striking features on those advances is shielding-free imaging by actively sensing and eliminating the electromagnetic interference (EMI). In this study, we review the analytical approaches for EMI estimation/elimination, and investigate their theoretical basis and relations with parallel imaging reconstruction. We provide further understanding of the existing approaches, formulating EMI estimation as convolution in k-space or multiplication in spectrum-space. We further propose to use tailored convolutional kernel to adaptively fit the varying EMI coupling across the acquisition window. These methods were evaluated with both simulation study and human brain imaging. The results show that using tailored convolutional kernel can achieve more robust performance against system and acquisition imperfections.

We have prepared trityl radicals with protons at the positions of the -COOH group in the phenyl rings and examined their EPR spectra, which show large - hyperfine couplings, and their dynamic nuclear polarization (DNP) Zeeman field profiles . By assessing these polarizing agents for high-field and Overhauser effect DNP, we gain insight into the roles that these hyperfine couplings and other molecular properties play in the DNP performance of these radicals. Interestingly, we do not observe OE DNP in any of the three molecules we examined. This suggests that hyperfine couplings by themselves are not sufficient to support OE DNP. In this case the electron spin density is ∼75 % localized on the central carbon atom rather than being distributed uniformly over the aromatic rings. This is in contrast to BDPA where the distribution is delocalized. Our findings do not suggest that any of these radicals are particularly well-suited to high-field DNP. Furthermore, we emphasize that polarizing agents can be extremely sensitive to their solvent environment, even obscuring the intrinsic magnetic properties of the radical.

At ultra-high fields, especially at 14 T, head coil arrays face significant challenges with coupling between elements. Although passive decoupling methods can reduce this coupling, the decoupling elements can cause destructive interference to the RF field of the head array, thus reducing the B efficiency. The B loss due to this effect can be even higher than that due to inter-element coupling. In this study, we develop a novel passive decoupling method to improve the performance of head coil arrays at 14 T. Specifically, passive dipole antennas were utilized to decouple the 16-channel sleeve antenna array, with their positioning optimized to minimize destructive interference with the array's RF field by increasing their distance from the active antennas. We used electromagnetic simulations to optimize the position of the passive dipoles to obtain the best performance of the array. In addition, we introduced a 16-channel dipole antenna array to compare the array performance when evaluating the sleeve antenna array performance using a human body model. We also constructed the optimized sleeve antenna array and measured its S-parameters to verify the effectiveness of the decoupling strategy. Our results show that the improved passive decoupling method can well reduce the destructive interference of the decoupling elements to the RF field. The sleeve antenna array developed under this method exhibits higher B efficiency and better transmission performance.

This study reports a deep learning approach that utilises message passing neural networks (MPNNs) for predicting chemical shifts in C NMR spectra of small molecules. MPNNs were trained on two distinct datasets: one with approximately 4000 labelled structures and another with over 40,000. To reduce stochastic variation, an ensemble framework was implemented, which is simple to deploy on multiple nodes of a High-Performance Computing facility. The results emphasise the critical role of training set size and diversity. While prediction performance was comparable on test sets drawn from each dataset, the ensemble trained on the larger dataset retained its accuracy when these sets were crossed over, and when applied to a further collection of approximately 12,000 previously unseen structures introduced after all development work had been completed. In contrast, the ensemble trained on the smaller dataset showed a notable decline in generalisation ability. This difference is attributed to the greater diversity of atomic environments captured in the larger dataset. The larger dataset also enabled more robust modelling of various error properties, providing a quantitative foundation for spectral assignment and verification. This was achieved in two ways. First, a clear relationship was observed between prediction errors and the frequency of different node feature vectors in the training data, allowing error estimates to be associated with individual nodes based on their type. These estimates can be used as weights in a modified cityblock distance metric when assigning observed to predicted shifts. Second, the mean absolute prediction error calculated at the structure level is well-fitted by a Gaussian kernel cumulative distribution. This enabled a probabilistic assessment of whether the predicted shifts and assigned observations are consistent with originating from the same molecular structure.

Despite inherent sensitivity constraints, nuclear magnetic resonance (NMR) plays an indispensable role in probing molecular structures and dynamics across scientific disciplines. Remarkably, while extensive efforts have targeted instrumental and experimental sensitivity improvements, comparatively little focus has been dedicated to sensitivity enhancement through signal analysis. Amidst this present gap, the matrix pencil method (MPM) has emerged as a versatile algorithm that offers tunable filtering and phasing capabilities. Extensive prior research has established the MPM as an adept fitting tool in signal analysis. Here, the efficacy of the MPM is investigated by precisely modeling noisy data to separate information-bearing signals from noise, thereby expanding its utility in various magnetic resonance applications. Simulated data is used to confirm the ability of the MPM to discern and separate signals from noise. Comparative analyses against standard Fourier-based filtering methods highlight the superior performance of the matrix pencil filter (MPF) in preserving signal fidelity without introducing aliasing artifacts. A variety of experimental data is then explored to demonstrate the proficiency of the MPF in characterizing signal components and correcting phase distortions. Collectively, these case studies underscore the filtering capacity of the MPM, portending its use for analytical sensitivity improvements in a wide range of NMR applications.

Rabi oscillations (transient nutations) are a phenomenon that has proven itself well in EPR for identifying electron spin quantum numbers and electron-spin transitions. They are successfully applied when the Rabi frequency significantly exceeds the spin relaxation rates and therefore does not depend on these rates. However, the short transverse relaxation time, being comparable to or even shorter than the dead time of EPR spectrometers, makes it difficult to observe Rabi oscillations and their frequency depends not only on the intensity of the short microwave pulse, but also on its shape and relaxation rates. Two techniques are considered that are suitable for this case, in which Rabi oscillations are detected by monitoring the FID amplitude as a function of pulse duration or microwave field amplitude. We describe the FID-detected Rabi oscillations analytically or numerically for rectangular or shaped pulses, respectively. The description is confirmed by EPR experiments using DPPH as a model sample.

In this paper, we introduce a compact, single-sided stray field sensor for NMR relaxometry applications. The sensor consists of four main components: the magnet, the RF coil, the spectrometer, and the translation stage. Our proposed magnet, an improved design of the Profile NMR-MOUSE, is designed for low weight, compactness, and magnetic field homogeneity, achieved through various shim strategies using a mixed genetic algorithm. The magnet comprises eight NdFeB blocks, generating a magnetic field of 0.424T within the sensitive region, positioned 12 mm above the magnet surface. For high spatial resolution measurements, we optimized the sensor performance by using a custom-designed rf coil, providing maximum sensitivity, lateral selectivity, and a dead time of less than 20µs. Moreover, we utilized 3D-printed structures to precisely align the sensitive slice within the object, using an experimental approach based on CPMG measurements. The presented setup achieved a spatial resolution of 50µm, with resolution changes proportional to acquisition time. We demonstrate the sensor's versatility and high resolution with measurements on materials such as cosmetics, elastomers, glue, and wood, verifying the good performance of our design, our alignment strategy, and the measuring scheme.

Magnetic Resonance Imaging (MRI) and Magnetic Resonance Spectroscopy (MRS) of non-proton nuclei (X-nuclei) typically require additional proton imaging for anatomical reference and B shimming. Therefore, two RF systems exist, necessitating cable traps to block the unwanted common-mode current at both Larmor frequencies of H and X-nuclei. This study introduces a frequency-independent dual-tuned cable trap that combines a standard solenoid cable trap with a float solenoid trap to independently tune high and low frequencies without compromising performance. The methods involved theoretical analysis, electromagnetic simulations, and bench tests. Two design approaches were evaluated: a float cable trap for H, a non-float cable trap for X-nuclei, and vice versa. Results showed that the design with the float trap for X-nuclei and non-float for H had superior performance, with high common-mode current suppression ability at both frequencies. Bench tests confirmed these findings, demonstrating effectiveness across various static fields and X-nuclei. The proposed frequency-independent dual-tuned cable trap provides a compact and efficient solution for multinuclear MRI and MRS, enhancing safety, image quality, and flexibility.

Dynamic nuclear polarization (DNP) enhanced magic angle spinning (MAS) solid-state NMR carried out at 25 K enables rapid acquisition of multi-dimensional C-N correlation spectra for protein structure studies and resonance assignment. Under commonly used DNP conditions, solvent deuteration reduces H-N cross polarization (CP) efficiencies, necessitates more careful optimization, and requires longer high-power N radio-frequency pulses. The sensitivity of 2D heteronuclear correlation experiments is potentially impaired. Here we show that 2D N-C experiments based on C-N transferred echo double resonance (TEDOR) methods outperform 2D experiments based on CP transfers in a fully deuterated solvent, and are competitive with CP-based experiments when the solvent is only partially deuterated. Additionally, we show that optimization of TEDOR-based 2D experiments is simpler than optimization of CP-based experiments under 25 K MAS conditions.

In magic angle spinning (MAS) experiments involving uniformly C/N labeled proteins, C-C and C-N dipolar recoupling experiments are now routinely used to measure direct dipole-dipole couplings that constrain distances and torsion angles and determine molecular structures. When the distances are short (<4 Å), the direct couplings dominate the evolution of the spin system, and the C-C and C-N J-couplings (scalar couplings) are ignored. However, for structurally interesting >4 Å distances, the dipolar and J-couplings are generally of comparable magnitude, and the variation in J must be included in order to optimize the precision of the experiment. This problem is circumvented in cases with well resolved spectra by using frequency-selective dipolar recoupling methods where the effects of J-couplings are refocused. However, for larger molecules with more spectral crowding, the requisite pulse length to achieve selectivity becomes long and leads to unacceptable sensitivity losses during the pulse or the spectral overlap precludes selective excitation. In this paper, we address this problem with two approaches aimed at facilitating higher precision internuclear distance measurements in systems that are not fully resolved. Namely, (1) we describe an approach for high precision measurements of specific J-couplings using the in-phase anti-phase (IPAP) sequence which is integrated into a non-selective dipolar recoupling technique and (2) we utilize the measured J-couplings to implement a double quantum filter experiment capable of providing the resolution necessary for frequency selective dipolar recoupling techniques without resorting to multidimensional spectroscopy. We illustrate these methods using a 7-peptide segment from the amyloidogenic Sup-35p protein, U-C/N-GNNQQNY, where we have measured 25 of the 27 possible one bond C-C J-couplings.

Magnetic resonance imaging (MRI) stands as one of the most powerful noninvasive and non-destructive imaging techniques, finding extensive utility in medical and industrial applications. Its ability to acquire signals from multiple nuclei grants it additional levels of strength by providing multi-dimensional datasets of the object under test. However, this typically requires dedicated hardware to detect each nucleus. In this paper, we report on the use of a digital lock-in amplifier to perform simultaneous multi-nuclear MRI with a single physical radio frequency (RF) channel. While we showcase this concept by demonstrating the results of fully parallel (TX and RX) H and F MRI images, we emphasize that it is not limited to two nuclei but can accommodate more nuclei with no extra cost on the hardware or scan time. The scalability is virtually unlimited, constrained only by the processing speed of the digital unit. Furthermore, we demonstrate that the quality of parallel imaging with SNR of 54 is comparable to the commercial single channel with SNR of 43. Thus with no reduction in imaging quality, the proposed concept promises a tremendous reduction in scan time, system complexity, and hardware costs.

Slice-selective refocusing pulses are powerful building blocks in contemporary magnetic resonance experiments, but their use in quantitative applications is complicated by the site-dependent signal loss they introduce. One source of this attenuation is the spin relaxation that occurs during such pulses, which causes losses that depend on the specific longitudinal and transverse relaxation time constants for a given resonance. This dependence is complicated both by any amplitude shaping of the radiofrequency pulse, and by the presence of the spatial encoding pulsed field gradient. The latter causes the net signal measured to be the weighted sum of signal contributions from a continuous range of offsets from resonance. In general, each offset will make a different contribution to the overall signal, and will be attenuated by a different mixture of longitudinal and transverse relaxation that is dictated by the different trajectories that the nuclear magnetisations take during experiments. Despite this complex behaviour, we present evidence from experiments and numerical simulations showing that in practical experimental applications a relatively simple empirical function can be used to accurately predict relaxational attenuation during slice-selective refocusing pulses. This approach may be of practical use in correcting for relaxational losses in quantitative applications of slice-selective pulse methods such as Zangger-Sterk pure shift NMR.

DNP-NMR and EPR experiments that operate at or greater than L-band (i.e., ν(e) = 1-2 GHz) are typically limited to maximum sample volumes of several hundred µL. These experiments rely on well-known resonator designs for DNP/EPR irradiation such as the loop-gap resonator and Alderman-Grant coil, where their maximum volumes limit further application to imaging experiments and high-throughput screening beyond L-band. Herein, we demonstrate a birdcage (BC) resonator design that can accommodate several mL of sample while operating around 1.5 GHz. The sample volume is maximized by using two identical BC resonators in a stacked configuration. Simulations are used to optimize the BC design and the performance is validated experimentally with liquid-state Overhauser-DNP-NMR experiments. This BC design exploits just the parasitic capacitance of conductive rings and features no fixed tuning capacitors. An enhancement of -77 is achieved on a 10 mM 4-Amino-TEMPO in HO sample for a 5 mL sample volume. The associated sample heating is minimal due to the low-E-fields generated and the large sample mass with +3.4 K when driving 100 W for several seconds.

Ultrahigh field systems (≥ 7 T) can increase the signal-to-noise ratio of magnetic resonance imaging (MRI), improving imaging performance compared to systems with lower fields. However, these enhancements heavily rely on a high B magnetic field homogeneity level, which can be achieved through superconducting shimming. This paper presents a novel two-stage superconducting shimming method designed to achieve precise shimming for a 7 T MRI superconducting magnet. In the initial stage, detailed measurements and fittings were conducted to determine the current polarity and the axial or circumferential positions of the shim fields. Subsequently, an optimization strategy was implemented to determine the optimal shim currents with a flexible target field. The second stage involves an iterative process to fine-tune the current of a specific shim coil, identified as having the most significant impact on field homogeneity. The overall fitness of 99.5% underscores the precision in determining the current polarity and position of the shim fields. Significantly, the calibrated shim system substantially improves the peak-to-peak and Root Mean Square Error (RMSE) field homogeneities from 107.42 ppm and 37.00 ppm to 11.12 ppm and 3.26 ppm, respectively, representing improvements of 89.65% and 91.19%. Furthermore, the simulation results of the fine-tuning stage demonstrate additional enhancements in peak-to-peak field homogeneity, to 9.9 ppm by reducing the current of the Z2 shim coil by 51.3 mA. Additionally, the shimmed magnetic field exhibited high time stability, with a maximum variation of only 27 µT observed within 48 h. Thus, the proposed two-stage superconducting shimming framework effectively addresses the challenge of imperfect B magnetic fields, enhancing peak-to-peak and RMSE field homogeneity. The stepwise optimized approach also mitigates deviations caused by shim-to-shim coupling, demonstrating its efficacy in achieving precise shimming in ultrahigh-field MRI systems.

In this work, the nutation of the spins of unpaired electrons in the nitroxide biradical of bis‑methano[60]fullerene was experimentally studied. Nutation frequencies were found in a wide range of microwave field power. To interpret the obtained results, numerical calculations of the nutation of biradicals were carried out for a set of parameters of the spin-spin interaction of a pair of unpaired electrons and for different values of the Rabi frequency of the microwave field. At comparing numerical results with experimental data, we also used the results of analytical calculations of nutation for some model situations. As a result of the analysis of experimental data on nutation, an estimate of the exchange and dipole-dipole interactions for the studied biradical was obtained. They are consistent with the results obtained from analysis of the shape of the EPR spectrum for a given biradical.

In this paper, we numerically optimize broadband pulse shapes that maximize Hahn echo amplitudes. Pulses are parameterized as neural networks (NN), nonlinear amplitude limited Fourier series (FS), and discrete time series (DT). These are compared to an optimized choice of the conventional hyperbolic secant (HS) pulse shape. A power constraint is included, as are realistic shape distortions due to power amplifier nonlinearity and the transfer function of the microwave resonator. We find that the NN, FS, and DT parameterizations perform equivalently, offer improvements over the best HS pulses, and contain a large number of equivalent optimal maxima, implying the flexibility to include further constraints or optimization goals in future designs.

In porous media MR studies, discriminating between oil and water presents a challenge because MR lifetimes are often similar and spectra overlap. Low saturations might suggest an experimental strategy of increasing the static field for increased sensitivity, but susceptibility effects are exacerbated at higher field. Overhauser dynamic nuclear polarization, effective at low static field, was employed with water and oil-soluble nitroxide to selectively enhance water and oil signals. We employ a home-built 2 MHz ceramic magnet to achieve selective enhancement of water and oil, in bulk, and in a rock core. For imaging, we employ a 705 kHz ceramic magnet with a 4 gauss/cm constant gradient configuration to image the hyperpolarized signal. A rock core flooding experiment was undertaken to highlight the advantages of Overhauser enhancement. A simple phase cycling technique may be employed to cancel the thermally polarized H signal to isolate the enhanced signal of interest.

Extracting parameters such as chemical shifts and coupling constants from proton NMR spectra is often a first step in using spectra for compound identification and structure determination. This can become challenging when scalar couplings between protons are comparable in size to chemical shift differences (strongly coupled), as is often the case with low-field (bench top) spectrometers. Here we explore the potential utility of AI methods, in particular neural networks, for extracting parameters from low-field spectra. Rather than seeking large experimental sets of spectra for training a network, we chose quantum mechanical simulation of sets, something that is possible with modern software packages and computer resources. We show that application of a network trained on 2-D J-resolved spectra and applied to a spectrum of iduronic acid, shows some promise, but also meets with some obstacles. We suggest that these may be overcome with improved pulse sequences and more extensive simulations.

To improve transmit B field homogeneity and longitudinal coverage of a human head RF array, we developed a novel eight-element transceiver (TxRx) array using composite elements based on paired folded-end dipoles.

3D iDOSY-HMBC (3D incorporated Diffusion Ordered SpectroscopY-Heteronuclear Multiple Bond Correlation) pulse sequences were modified to incorporate convection compensation element. No additional delays were required, and convection compensation was directly constructed within the existing delay periods in 3D iDOSY-HMBC pulse sequence. Convection compensation was achieved by pulsed field gradient double echo, thus avoiding the intensity loss normally related to stimulated echo methods. The incorporated convection compensation element improves the usability of 3D iDOSY-HMBC. In case of elevated temperatures, thermal convection leads to loss of resolution in DOSY-dimension or even to severe decrease of signal intensity, thus making convection uncompensated 3D iDOSY-HMBC infeasible. Aforementioned problems can be circumvented via utilization of the presented convection compensated 3D iDOSY-HMBC-versions.