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.

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.

Electrostatic Self-Assembly of Composite Nanofiber Yarn.

Electrospinning polymer fibers is a well-understood process primarily resulting in random mats or single strands. More recent systems and methods have produced nanofiber yarns (NFY) for ease of use in textiles. This paper presents a method of NFY manufacture using a simplified dry electrospinning system to produce self-assembling functional NFY capable of conducting electrical charge. The polymer is a mixture of cellulose nanocrystals (CNC), polyvinyl acrylate (PVA) and poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS). When treated with ethylene glycol (EG) to enhance conductivity, fibers touching the collector plate align to the applied electrostatic field and grow by twisting additional nanofiber polymers injected by the jet into the NFY bundle. The longer the electrospinning continues, the longer and more uniformly twisted the NFY becomes. This process has the added benefit of reducing the electric field required for NFY production from >2.43 kV cm-1 to 1.875 kV cm-1.