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RandomShimDB: A subset of the NMR magnet shimming database ShimDB

Becker, Moritz ORCID iD icon 1
1 Institut für Mikrostrukturtechnik (IMT), Karlsruher Institut für Technologie (KIT)


Zugehörige Institution(en) am KIT Institut für Mikrostrukturtechnik (IMT)
Publikationstyp Forschungsdaten
Publikationsdatum 09.11.2022
Erstellungsdatum 19.04.2022
Identifikator DOI: 10.5445/IR/1000152278
KITopen-ID: 1000152278
HGF-Programm 43.35.04 (POF IV, LK 01) Correlative Data Science
Lizenz Creative Commons Namensnennung – Weitergabe unter gleichen Bedingungen 4.0 International
Liesmich

RandomShimDB: A subset of the NMR magnet shimming database ShimDB

RandomShimDB is a subset of the NMR magnet shimming database ShimDB and contains over 15000 instances. Data is aquired on a Spinsolve 80 Carbon spectrometer (Magritek GmbH, Aachen, Germany, www.magritek.com) on 5%vv H2O in D2O and a water solution with CuSO4 (5mmol/L).

RandomShimDB is part of "Acquisitions with random shim values enhances AI-driven NMR shimming" by M. Becker et al. [1].

The acquisition procedure was as follows. The manufacturer's automated shimming technique, based on the downhill simplex method, was used to obtain a reference spectrum. Then, the shims X, Y, Z and Z2 were varied. The dataset parameters were obtained by relative offsets from the reference shim values in a range R with weighting W, following Gaussian noise sampling. For each combination, the raw FID, acquisition parameters, and the shim values were stored.

Topic Parameter Value
Dataset parameters Shims X,Y,Z,Z2
Weightings W [1.2, 1.0, 2.0, 18.0]
Shim range R +/- 50
Sample I H2O+CuSO4
Sample II 5vol% H2O in D2O
Nr. spectra {5000,10000}
Acquisition parameters Nucleus 1H
Bandwidth 5 kHz
Points 32768
Repetition time 2000 ms
Phase correction phi_0

We strongly encourage researchers to extend ShimDB with their own subsets to stimulate developments. We offer to include raw data or links to your publications into ShimDB.

Files format

Each folder in RandomShimDB contains the following files:

  • data.1d -> the raw FID.
  • shims.par -> Shim values, where only linear shims are non-zero.
  • acqu.par -> Acquisition parameters.
  • proc.par -> Processing parameters.

The RandomShimDB root folder also contains the reference starting shims (ReferenceShims.par).

Data loading

We deliver a python script utils_IO.py alongside ShimDB to easily load the database into numpy array structure using the nmrglue packages[2].

The following python libraries and packages are required: os, numpy, glob, nmrglue (>= v0.9.dev0)

References

[1] M. Becker, S. Lehmkuhl, S. Kesselheim, J. G. Korvink, and M. Jouda, “Acquisitions with random shim values enhance AI-driven NMR shimming,” J. Magn. Reson., p. 107323, 2022, doi: https://doi.org/10.1016/j.jmr.2022.107323.

[2] J. J. Helmus and C. P. Jaroniec, “Nmrglue: An open source Python package for the analysis of multidimensional NMR data,” J. Biomol. NMR, vol. 55, no. 4, pp. 355–367, 2013, doi: https://doi.org/10.1007/s10858-013-9718-x.

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