2026-10-14T20:10:05Zhttps://www.radar-service.eu/oai/OAIHandler10.35097/14332026-10-09T11:00:51Zradar4kit
https://dx.doi.org/10.35097/1433
Becker, Moritz
RandomShimDB: A subset of the NMR magnet shimming database ShimDB
Karlsruhe Institute of Technology
2023
Engineering
dataset
Dataset
info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-sa/4.0/legalcode
# RandomShimDB: A subset of the NMR magnet shimming database ShimDB
RandomShimDB is a subset of the NMR magnet shimming database [ShimDB](https://github.com/mobecks/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](https://github.com/mobecks/ShimDB) to easily load the database into numpy array structure using the [nmrglue packages](https://github.com/jjhelmus/nmrglue)[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.
10.5445/IR/1000152278
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