Frequency multiplexing enables parallel multi-sample EPR.

Electron paramagnetic resonance (EPR) spectroscopy stands out as a powerful analytical technique with extensive applications in the fields of biology, chemistry, physics, and material sciences. It proves invaluable for investigating the molecular structure and reaction mechanisms of substances containing unpaired electrons, such as metal complexes, organic and inorganic radicals, and intermediate states in chemical reactions. However, despite their remarkable capabilities, EPR systems face significant limitations in terms of sample throughput, as current commercial systems only target the analysis of one sample at a time. Here we introduce a novel scheme for conducting ultra-high frequency continuous-wave EPR (CW EPR) targeting the EPR spectroscopy of multiple microliter volume samples in parallel. Our proof-of-principle prototype involves two decoupled detection cells equipped with high qualty factor Q = 104 solenoidal coils tuned to 488 and 589 MHz, ensuring a significant frequency gap for effective radio frequency (RF) decoupling between the channels. To further enhance electromagnetic decoupling, an orthogonal alignment of the coils was adopted. The paper further presents an innovative radiofrequency circuit concept that utilizes a single physical RF channel to simultaneously conduct parallel EPR on up to eight cells. Parallel EPR experiments on two BDPA samples, each with a sample volume of 18.3 µL, registered signal-to-noise ratios of 255 and 252 for the two EPR measurement cells, with no observable coupling. The showcased prototype, built using cost-effective commercially available fabrication technology, is readily scalable and represents an initial step with promising potential for advancing sample screening with high-throughput parallel EPR.

Artificial intelligence-driven shimming for parallel high field nuclear magnetic resonance.

Rapid drug development requires a high throughput screening technology. NMR could benefit from parallel detection but is hampered by technical obstacles. Detection sites must be magnetically shimmed to ppb uniformity, which for parallel detection is precluded by commercial shimming technology. Here we show that, by centering a separate shim system over each detector and employing deep learning to cope with overlapping non-orthogonal shimming fields, parallel detectors can be rapidly calibrated. Our implementation also reports the smallest NMR stripline detectors to date, based on an origami technique, facilitating further upscaling in the number of detection sites within the magnet bore.

A field focusing butterfly stripline detects NMR at higher signal-to-noise ratio.

We present a compact tuned magnetic resonance detector that merges the conductor topology of a butterfly coil with that of a stripline, thereby increasing the magnetic field intensity B1 per unit current, which increases the detection signal-to-noise ratio for mass-limited samples by a factor of 2. The s-parameter measurements further reveal improved radiofrequency shielding through the suppression of B1 outside the coil when operated within an array of similar detectors. Simulations additionally show a sharper B1 fall-off for the butterfly stripline outside the sensitive sample region. Our design is compatible with 2D planar manufacturing procedures, such as printed circuit board technology, and surface micromachining.

Optimal control flow encoding for time-efficient magnetic resonance velocimetry.

Phase contrast velocimetry relies on bipolar gradients to establish a direct and linear relationship between the phase of the magnetic resonance signal, and the corresponding fluid motion. Despite its utility, several limitations and drawbacks have been reported, the most important being the extended echo time due to the encoding after the excitation. In this study, we elucidate a new approach based on optimal control theory that circumvents some of these disadvantages. An excitation pulse, termed FAUCET (flow analysis under controlled encoding transients), is designed to encode velocity into phase already during the radiofrequency excitation. As a result of concurrent excitation and flow encoding, and hence elimination of post-excitation flow encoding, FAUCET achieves a shorter echo time than the conventional method. This achievement is a matter of significance not only because it decreases the loss of signal due to spin-spin relaxation and B0 inhomogeneity, but also because a shorter echo time is always preferred in order to reduce the dimensionless dephasing parameter and the required residence time of the flowing sample in the detection coil. The method is able to establish a non-linear bijective relationship between phase and velocity, which can be employed to enhance the resolution over a specific range of velocities, for example along flow boundaries. A computational comparison between the phase contrast and optimal control methods reveals that the latter's encoding is more robust against remnant higher-order-moment terms of the Taylor expansion for faster voxels, such as acceleration, jerk, and snap.

Lenz Lenses in a Cryoprobe: Boosting NMR Sensitivity Toward Environmental Monitoring of Mass-Limited Samples.

Nuclear magnetic resonance (NMR) spectroscopy is commonly employed in a wide range of metabolomic research. Unfortunately, due to its relatively low sensitivity, smaller samples become challenging to study by NMR. Cryoprobes can be used to increase sensitivity by cooling the coil and preamplifier, offering sensitivity improvements of ∼3 to 4x. Alternatively, microcoils can be used to increase mass sensitivity by improving sample filling and proximity, along with decreased electrical resistance. Unfortunately, combining the two approaches is not just technically challenging, but as the coil decreases, so does its thermal fingerprint, reducing the advantage of cryogenic cooling. Here, an alternative solution is proposed in the form of a Lenz lens inside a cryoprobe. Rather than replacing the detection coil, Lenz lenses allow the B1 field from a larger coil to be refocused onto a much smaller sample area. In turn, the stronger B1 field at the sample provides strong coupling to the cryocoil, improving the signal. By combining a 530 I.D. Lenz lens with a cryoprobe, sensitivity was further improved by 2.8x and 3.5x for 1H and 13C, respectively, over the cryoprobe alone for small samples. Additionally, the broadband nature of the Lenz lenses allowed multiple nuclei to be studied and heteronuclear two-dimensional (2D) NMR approaches to be employed. The sensitivity improvements and 2D capabilities are demonstrated on 430 nL of hemolymph and eight eggs (∼350 µm O.D.) from the model organismDaphnia magna. In summary, combining Lenz lenses with cryoprobes offers a relatively simple approach to boost sensitivity for tiny samples while retaining cryoprobe advantages.

Acquisitions with random shim values enhance AI-driven NMR shimming.

Shimming is still an unavoidable, time-consuming and cumbersome burden that precedes NMR experiments, and aims to achieve a homogeneous magnetic field distribution, which is required for expressive spectroscopy measurements. This study presents multiple enhancements to AI-driven shimming. We achieve fast, quasi-iterative shimming on multiple shims simultaneously via a temporal history that combines spectra and past shim actions. Moreover, we enable efficient data collection by randomized dataset acquisition, allowing scalability to higher-order shims. Application at a low-field benchtop magnet reduces the linewidth in 87 of 100 random distortions from ∼ 4 Hz to below 1 Hz, within less than 10 NMR acquisitions. Compared to, and combined with, traditional methods, we significantly enhance both the speed and performance of shimming algorithms. In particular, AI-driven shimming needs roughly 1/3 acquisitions, and helps to avoid local minima in 96% of the cases. Our dataset and code is publicly available.

All-optical thermometry using a single multimode fiber endoscope and diamond nanoparticles containing nitrogen vacancy centers.

Photoluminescence (PL) spectra from diamond nanoparticles containing negative nitrogen vacancy centers were measured by using a single multimode fiber endoscope combined with a high-sensitivity spectroscopy system. A laser light spot was produced at the distal end of the endoscope and the PL spectra from a temperature-controlled ensemble of diamond nanoparticles were measured. After calibrating the sensitivity and wavelength of the spectroscopy system, the temperature dependence of the zero-phonon line peak wavelength similar to those previously reported was obtained.

Sample-centred shimming enables independent parallel NMR detection.

Two major technical challenges facing parallel nuclear magnetic resonance (NMR) spectroscopy, at the onset, include the need to achieve exceptional [Formula: see text] homogeneity, and good inter-detector radiofrequency signal decoupling, and have remained as technical obstacles that limit high throughput compound screening via NMR. In this contribution, we consider a compact detector system, consisting of two NMR 'unit cell' resonators that implement parallel [Formula: see text] shimming with parallel radiofrequency detection, as a prototype NMR environment, pointing the way towards achieving accelerated NMR analysis. The utility of our approach is established by achieving local field correction within the bore of a 1.05T permanent magnet MRI. Our forerunner platform suppresses signal cross-coupling in the range of [Formula: see text] dB to [Formula: see text] dB, under a geometrically decoupled scheme, leading to a halving of the necessary inter-coil separation. In this permanent magnet environment, two decoupled parallel NMR detector sites simultaneously achieve narrow spectral linewidth, overcoming the spatial inhomogeneity of the magnet from 400 to 28 Hz.

Net-phase flow NMR for compact applications.

The net phase of the NMR signal is proposed as a robust mechanism for the encoding of fluid flow velocity into phase, showing local bijectivity. While magnitude-based or imaging-based methods suffer from loss of signal, by increasing the flow rate, the present method enables us to maintain the high SNR even for the case of fast flow. In addition, it is shown that a well-engineered flow channel is also necessary, which is not the case for traditional cylindrical flow channels. In this contribution, we report on implementing this approach in a low-cost NMR-based flowmeter for use in a low field (1 T) setting, for example, for monitoring reaction flow industrial processes.

Deep regression with ensembles enables fast, first-order shimming in low-field NMR.

Shimming in the context of nuclear magnetic resonance aims to achieve a uniform magnetic field distribution, as perfect as possible, and is crucial for useful spectroscopy and imaging. Currently, shimming precedes most acquisition procedures in the laboratory, and this mostly semi-automatic procedure often needs to be repeated, which can be cumbersome and time-consuming. The paper investigates the feasibility of completely automating and accelerating the shimming procedure by applying deep learning (DL). We show that DL can relate measured spectral shape to shim current specifications and thus rapidly predict three shim currents simultaneously, given only four input spectra. Due to the lack of accessible data for developing shimming algorithms, we also introduce a database that served as our DL training set, and allows inference of changes to 1H NMR signals depending on shim offsets. In situ experiments of deep regression with ensembles demonstrate a high success rate in spectral quality improvement for random shim distortions over different neural architectures and chemical substances. This paper presents a proof-of-concept that machine learning can simplify and accelerate the shimming problem, either as a stand-alone method, or in combination with traditional shimming methods. Our database and code are publicly available.

Integrated impedance sensing of liquid sample plug flow enables automated high throughput NMR spectroscopy.

A novel approach for automated high throughput NMR spectroscopy with improved mass-sensitivity is accomplished by integrating microfluidic technologies and micro-NMR resonators. A flow system is utilized to transport a sample of interest from outside the NMR magnet through the NMR detector, circumventing the relatively vast dead volume in the supplying tube by loading a series of individual sample plugs separated by an immiscible fluid. This dual-phase flow demands a real-time robust sensing system to track the sample position and velocities and synchronize the NMR acquisition. In this contribution, we describe an NMR probe head that possesses a microfluidic system featuring: (i) a micro saddle coil for NMR spectroscopy and (ii) a pair of interdigitated capacitive sensors flanking the NMR detector for continuous position and velocity monitoring of the plugs with respect to the NMR detector. The system was successfully tested for automating flow-based measurement in a 500 MHz NMR system, enabling high resolution spectroscopy and NMR sensitivity of 2.18 nmol s1/2 with the flow sensors in operation. The flow sensors featured sensitivity to an absolute difference of 0.2 in relative permittivity, enabling distinction between most common solvents. It was demonstrated that a fully automated NMR measurement of nine individual 120 µL samples could be done within 3.6 min or effectively 15.3 s per sample.

Magnetostatic reciprocity for MR magnet design.

Electromagnetic reciprocity has long been a staple in magnetic resonance (MR) radio-frequency development, offering geometrical insights and a figure of merit for various resonator designs. In a similar manner, we use magnetostatic reciprocity to compute manufacturable solutions of complex magnet geometries, by establishing a quantitative metric for the placement and subsequent orientation of discrete pieces of permanent magnetic material. Based on magnetostatic theory and non-linear finite element modelling (FEM) simulations, it is shown how assembled permanent magnet setups perform in the embodiment of a variety of designs and how magnetostatic reciprocity is leveraged in the presence of difficulties associated with self-interactions, to fulfil various design objectives, including self-assembled micro-magnets, adjustable magnetic arrays, and an unbounded magnetic field intensity in a small volume, despite realistic saturation field strengths.

Selective excitation enables encoding and measurement of multiple diffusion parameters in a single experiment.

Band selectivity to address specific resonances in a spectrum enables one to encode individual settings for diffusion experiments. In a single experiment, this could include different gradient strengths (enabling coverage of a larger range of diffusion constants), different diffusion delays, or different gradient directions (enabling anisotropic diffusion measurement). In this report, a selective variant of the bipolar pulsed gradient eddy current delay (BPP-LED) experiment, enabling selective encoding of three resonances, was implemented. As proof of principle, the diffusion encoding gradient amplitude was assigned a range dependent on the selected signal, thereby allowing the extraction of the diffusion coefficient for water and a tripeptide (Met-Ala-Ser) with optimal settings in a single experiment.

Topologically optimized magnetic lens for magnetic resonance applications.

Improvements to the signal-to-noise ratio of magnetic resonance detection lead to a strong reduction in measurement time, yet as a sole optimization goal for resonator design, it would be an oversimplification of the problem at hand. Multiple constraints, for example for field homogeneity and sample shape, suggest the use of numerical optimization to obtain resonator designs that deliver the intended improvement. Here we consider the 2D Lenz lens to be a sufficiently broadband flux transforming interposer between the sample and a radiofrequency (RF) circuit and to be a flexible and easily manufacturable device family with which to mediate different design requirements. We report on a method to apply topology optimization to determine the optimal layout of a Lenz lens and demonstrate realizations for both low- (45 MHz) and high-frequency (500 MHz) nuclear magnetic resonance.

ArduiTaM: accurate and inexpensive NMR auto tune and match system.

We introduce a low-complexity, low-cost, yet sufficiently accurate automatic tune and match system for NMR and MRI applications. The ArduiTaM builds upon an Arduino Uno embedded system that drives a commercial frequency synthesiser chip to perform a frequency sweep around the Larmor frequency. The generated low-power signal is fed to the NMR coil, after which the reflected waves are detected using a directional coupler and amplified. The signal shape is then extracted by means of an envelope detector and passed on to the Arduino, which performs a dip search while continuously generating actuator control patterns to adjust the tune and match capacitors. The process stops once the signal dip reaches the Larmor frequency. The ArduiTaM works readily with any spectrometer frequency in the range from 1 to 23 T. The speed of the ArduiTaM is mainly limited by the clock of the Arduino and the capacitor actuation mechanism. The Arduino can easily be replaced by a higher-speed microcontroller, and varactors can replace stepper-motor controlled variable capacitors. The ArduiTaM is made available in open source, and so is easily duplicated.

Geometrically-differential NMR in a stripline front-end.

A major challenge facing the development of portable, low-cost NMR is the development of robust yet sensitive transceivers, for which several trade-offs in scalability, performance and complexity are usually necessary. Here we report on a stripline-based NMR detector that overcomes previous limitations. It features a sensitivity of 5.7×10-4 TA-1Ω-0.5 over a sample volume of 10 mm × 10 mm × 3 mm, an exceptionally high B1 homogeneity of A450/A90=98.4%, intrinsic electromagnetic shielding of 27 dB from environmental influences, and a total signal gain of 68 dB in the presence of a noise factor of 1.28, without any exterior shielding. The new dual-coil arrangement offers a downscalable geometry optimised for gap magnets, and it is voltage-tunable and plug-in compatible with commercial software-defined radio spectrometer boards. Exceptionally, it features both common-mode and novel differential-mode NMR measurement abilities.

Gradient-Induced Mechanical Vibration of Neural Interfaces During MRI.

OBJECTIVE: Resonant vibrations of implanted structures during a magnetic resonance imaging (MRI) procedure pose a risk to the patient in the form of soft tissue irritation and degradation of the implant. In this paper, the mechanical behavior of implant structures in air, water, and viscoelastic materials was explored. METHODS: The static and dynamic transfer functions of various test samples in air and immersed in both water and hydrogels were analyzed. The laser-based acquisition method allowed for high-angular-resolution (10  µDeg) and high-dynamic-range (0-6 kHz) measurements. Additional MRI experiments were conducted to investigate the dependence of vibration strength on magnetic resonance (MR) sequence parameters in combination with the obtained transfer functions. RESULTS: The largest forces were found to be in the micronewton to millinewton range, which is comparable to forces applied during implantation. Of additional concern was the damping introduced by viscoelastic tissue, which was less than expected, leading to an underdamped system. In contrast to current wisdom, the imaging experiments demonstrated drastically different vibration amplitudes for identical gradient slew rates, but different timing parameters TR, mainly due to resonant amplification. CONCLUSION: The results showed that a safe force-free MR procedure depends not only on the gradient slew rate, but also and more drastically on the choice of secure timing parameters. SIGNIFICANCE: These findings delineate design improvements to achieve longevity of implants and will lead to increased patient safety during MRI. A prudent choice of mechanical characteristics of implanted structures is sufficient to avoid resonant excitation due to mismatched MR sequence parameters.

Motion prediction enables simulated MR-imaging of freely moving model organisms.

Magnetic resonance tomography typically applies the Fourier transform to k-space signals repeatedly acquired from a frequency encoded spatial region of interest, therefore requiring a stationary object during scanning. Any movement of the object results in phase errors in the recorded signal, leading to deformed images, phantoms, and artifacts, since the encoded information does not originate from the intended region of the object. However, if the type and magnitude of movement is known instantaneously, the scanner or the reconstruction algorithm could be adjusted to compensate for the movement, directly allowing high quality imaging with non-stationary objects. This would be an enormous boon to studies that tie cell metabolomics to spontaneous organism behaviour, eliminating the stress otherwise necessitated by restraining measures such as anesthesia or clamping. In the present theoretical study, we use a phantom of the animal model C. elegans to examine the feasibility to automatically predict its movement and position, and to evaluate the impact of movement prediction, within a sufficiently long time horizon, on image reconstruction. For this purpose, we use automated image processing to annotate body parts in freely moving C. elegans, and predict their path of movement. We further introduce an MRI simulation platform based on bright field videos of the moving worm, combined with a stack of high resolution transmission electron microscope (TEM) slice images as virtual high resolution phantoms. A phantom provides an indication of the spatial distribution of signal-generating nuclei on a particular imaging slice. We show that adjustment of the scanning to the predicted movements strongly reduces distortions in the resulting image, opening the door for implementation in a high-resolution NMR scanner.

A multi-purpose, rolled-up, double-helix resonator.

Multilayer flexible substrates offer a means to combine high lateral precision and resolution with roll-up processes, allowing layer-based manufacturing to reach into the third dimension. Here we explore this combination to achieve an otherwise hard-to-manufacture resonator geometry: the double-helix. The use of commercial flexPCB technology enabled optimal winding connections and a versatile adjustment to various operation fields, sample volumes and resonance numbers. The sensitivity of the design is shown to greatly benefit from the fabrication method, though optimal electrical connections and several radially-wound windings, and was measured to outperform an equivalent solenoid despite the known geometrical disadvantage.

Broadband and multi-resonant sensors for NMR.

It has always been of considerable interest to study the nuclear magnetic resonance response of multiple nuclei simultaneously, whether these signals arise from internuclear couplings within the same molecule, or from uncoupled nuclei within sample mixtures. The literature contains numerous uncorrelated reports on techniques employed to achieve multi-nuclear NMR detection. This paper consolidates the subset of techniques in which single coil detectors are utilized, and highlights the strengths and weaknesses of each approach, at the same time pointing the way towards future developments in the field of multi-nuclear NMR. We compare the different multi-nuclear NMR techniques in terms of performance, and present a guide to NMR probe designers towards application-based optimum design. We also review the applicability of micro-coils in the context of multi-nuclear methods. Micro-coils benefit from compact geometries and exhibit lower impedance, which provide new opportunities and challenges for the NMR probe designer.