The magic angle spinning (MAS) technique of solid state NMR requires samples to be rapidly rotated within a magnetic field. The rotation rate speed record is 150 kHz, or 9 million RPM, and hence MAS turbines hold the world rotation speed record for extended objects. The containers holding the samples are made of the strongest materials known, to be able to withstand the excessive centrifugal forces. To overcome the speed limit, this paper delineates a way to do so using an optical tweezers setup
To increase experimental efficiency, information can be encoded in parallel by taking advantage of highly resolved NMR spectra. Here we demonstrate parallel encoding of optimal diffusion parameters by selectively using a resonance for each molecule in the sample. This yields a factor of n decrease in experimental time since n experiments can be encoded into a single measurement. This principle can be extended to additional experimental parameters as a means to further improve measurement time.
We use the theory of magnetostatic reciprocity to compute manufacturable solutions of complex magnet geometries, establishing a quantitative metric for the placement and subsequent orientation of discrete pieces of permanent magnetic material. This leads to self-assembled micro-magnets, adjustable magnetic arrays, and an unbounded magnetic field intensity in a small volume, despite realistic modelling of complex material behaviours.
We have assembled a few off-the-shelf electronic chips and a popular Arduino Uno microcomputer board in an automatic system that performs so-called tuning and matching of an arbitrary NMR probe head at very low cost. This removes the tedium of doing the job by hand, the bane of many NMR analysts. It also brings accuracy and repeatability into the process, which is so necessary for high throughput analysis or when working with low-field permanent magnesystems with excessive magnetic field drift.
Aage, N., Mortensen, N. A., and Sigmund, O.: Topology optimization of metallic devices for microwave applications, Int. J. Numer. Meth. Eng., 83, 228-248, https://doi.org/10.1002/nme.2837, 2010. a
Andkjær, J., Nishiwaki, S., Nomura, T., and Sigmund, O.: Topology optimization of grating couplers for the efficient excitation of surface plasmons, J. Opt. Soc. Am. B, 27, 1828–1832, https://doi.org/10.1364/JOSAB.27.001828, 2010. a, b
Gersborg-Hansen, A., Bendsøe, M. P., and Sigmund, O.: Topology optimization of heat conduction problems using the finite volume method, Struct. Multidiscip. O., 31, 251–259, https://doi.org/10.1007/s00158-005-0584-3, 2006. a
Guest, J. K., Prévost, J. H., and Belytschko, T.: Achieving minimum length scale in topology optimization using nodal design variables and projection functions, Int. J. Numer. Meth. Eng., 61, 238–254, https://doi.org/10.1002/nme.1064, 2004. a
Jones, D. and Tamiz, M.: Practical Goal Programming, in: International Series In Operations Research and Management Science, vol. 141, edited by: Hillier, F. S., Springer, New York, Dordrecht, Heidelberg, London, https://doi.org/10.1007/978-1-4419-5771-9, 2010. a
Jouda, M., Kamberger, R., Leupold, J., Spengler, N., Hennig, J., Gruschke, O., and Korvink, J. G.: A comparison of Lenz lenses and LC resonators for NMR signal enhancement, Concept. Magn. Reson. B, 47, e21357, https://doi.org/10.1002/cmr.b.21357, 2017. a, b, c
Spengler, N., While, P. T., Meissner, M. V., Wallrabe, U., and Korvink, J. G.: Magnetic Lenz lenses improve the limit-of-detection in nuclear magnetic resonance, PLOS ONE, 12, e0182779, https://doi.org/10.1371/journal.pone.0182779, 2017. a, b
Lazarov, B. S. and Sigmund, O.: Filters in topology optimization based on Helmholtz-type differential equations, Int. J. Numer. Meth. Eng., 86, 765–781, https://doi.org/10.1002/nme.3072, 2011. a
Piggott, A., Lu, J., Lagoudakis, K., Petykiewicz, J., Babinec, T. M., and Vuckovic, J.: Inverse design and demonstration of a compact and broadband on-chip wavelength demultiplexer, Nat. Photonics, 9, 374–377, https://doi.org/10.1038/nphoton.2015.69, 2015. a
Wadhwa, S., Jouda, M., Deng, Y., Nassar, O., Mager, D., and Korvink, J. G.: Data set for Topologically optimized magnetic lens for magnetic resonance applications, Repository KITopen, Karlsruhe Institute of Technology, https://doi.org/10.5445/IR/1000124281, 2020. a
Wang, F., Lazarov, B. S., and Sigmund, O.: On projection methods, convergence and robust formulations in topology optimization, Struct. Multidiscip. O., 43, 767–784, https://doi.org/10.1007/s00158-010-0602-y, 2011. a
Zhou, S. and Li, Q.: Topology optimization, Level set method, Variational method, Navier–Stokes flow, Maximum permeability, Minimum energy dissipation, J. Comput. Phys., 227, 10178–10195, https://doi.org/10.1016/j.jcp.2008.08.022, 2008. a
Magnetic resonance detectors require a high degree of precision to be useful. Their design must e.g. carefully weigh field strength and field homogeneity to find the best compromise. Here we show that inverse computational design is a viable method to find such a
trade-off. Apart from the electromagnetic field solution, the simulation program also determines the boundary between insulating and conducting material and moves the material boundaries around until the compromise is best satisfied.
Magnetic resonance detectors require a high degree of precision to be useful. Their design must...