This data corresponds to the following paper: Title: Maximizing NMR Sensitivity: A Guide to Receiver Gain AdjustmentJournal: NMR in BiomedicineAuthors: Josh P. Peters, Frank D. Sönnichsen, Jan-Bernd Hövener and Andrey N. Pravdivtsev The python script is provided: "SNR_script.py"All neccessary information about its usage is provided in the script. The data is organized with respect to the main figures 1 to 7 and SI figures S1 to S5.A description of acquisition parameters and conditions is provided here or in the manuscript text. Figure 1:- Overflow experiments of 1H and BB-channel on the 9.4 T machine. Figure 2 & 3:- Receiver gain sweep data with signal and SNR maps on the 9.4 T machine.A list of the corresponding experiment IDs and RG values can be found in "Combined_analysis_9.4.xlsx"The extracted SNR and signal values are provided there as well. Figure 4:- Alternating RG starting with RG 18 (17) followed by RG 0.25 (18) and so on. A 5° pulse was used.The thermal was acquired with 1 average, RG 18 and a 90° pulse. Figure 5:- 13C receiver gain sweep data vs SNRThe corresponding data is found in the Figure S3 to S5 folders. Figure 6:- 15N receiver gain sweep data vs SNRThe corresponding data is found in the Figure S3 to S5 folders. Figure 7:- Receiver gain sweep data vs signal and SNR on the 1 T machineA list of the corresponding experiment IDs and RG values can be found in "Combined_analysis_1.xlsx"The extracted SNR and signal values are provided there as well. Figure S1:- Overflow experiment of the 13C-channel on the 1 T machine. Figure S2:- Constant signal experiment with varying pulse and receiver gain. Details can be found in Supporting information.A list of the corresponding experiment IDs and RG values can be found in "Combined_analysis.xlsx" Figure S3:- Receiver gain sweep data vs signal and SNR on the 7 T machineA list of the corresponding RG values and results can be found in "Combined_analysis_7.xlsx"The extracted SNR and signal values are provided there as well. Figure S4:- Receiver gain sweep data vs signal and SNR on the 11.7 T machineA list of the corresponding RG values and results can be found in "Combined_analysis_11.7.xlsx"The extracted SNR and signal values are provided there as well. Figure S5:- Receiver gain sweep data vs signal and SNR on the 14.1 T machineA list of the corresponding RG values and results can be found in "Combined_analysis_14.1.xlsx"The extracted SNR and signal values are provided there as well.

Novel methods and technology drive the rapid advances of nuclear magnetic resonance (NMR). The primary objective of developing novel hardware is to improve sensitivity and reliability (and possibly to reduce cost). Automation has made NMR much more convenient, but it may lead to trusting the algorithms without regular checks. In this contribution, we analyzed the signal and signal-to-noise ratio (SNR) as a function of the receiver gain (RG) for 1H, 2H, 13C, and 15N nuclei on five spectrometers. On a 1 T benchtop spectrometer (Spinsolve, Magritek), the SNR showed the expected increase as a function of RG. Still, the 1H and 13C signal amplitudes deviated by up to 50% from supposedly RG-independent signal intensities. On 7, 9.4, 11.7, and 14.1 T spectrometers (Avance Neo, Bruker), the signal intensity increases linearly with RG as expected, but surprisingly a drastic drop of SNR is observed for some X-nuclei and fields. For example, while RG = 18 provided a 13C SNR similar to that at a maximum RG of 101 at 9.4 T, at RG = 20.2 the determined SNR was 32% lower. The SNR figures are strongly system and resonance frequency dependent. Our findings suggest that NMR users should test the specific spectrometer behavior to obtain optimum SNR for their experiments, as automatic RG adjustment does not account for the observed characteristics. In addition, we provide a method to estimate optimal settings for thermally and hyperpolarized samples of a chosen concentration, polarization, and flip angle, which provide a high SNR and avoid ADC-overflow artefacts. 

We acknowledge funding from German Federal Ministry of Education and Research (BMBF) within the framework of the e:Med research and funding concept (01ZX1915C, 03WIR6208A hyperquant), DFG (555951950, 527469039, 469366436, HO-4602/2-2, HO-4602/3, HO-4602/4, EXC2167, FOR5042, TRR287). MOIN CC was founded by a grant from the European Regional Development Fund (ERDF) and the Zukunftsprogramm Wirtschaft of Schleswig-Holstein (Project no. 122-09-053).