## 2 Materials and Methods
### Data Processing  
All acquired JCS were zero-filled and Fourier transformed without apodization. Each spectrum was then shifted according to the frequency-adjusted averaging method previously described before summation [32]. Zero and first order phase corrections were applied with a baseline correction to each portion of the spectrum. Simulations of the expected JCS of each compound were carried out in MATLAB (2019a, Mathworks, Natick, MA, USA, 2019) using the SPINACH software library (v2.4.5157 SpinDynamics, Southhampton, UK, 2019) [51]. The SPINACH simulations used a scalar coupling connectivity model, spherical tensor Liouville space formalism (sphten-liov), and an IK-2 approximation for spin correlations. The simulation assumed all \({}^{1}\)H and \({}^{19}\)F nuclei to be spin-active with no effects from natural abundance \({}^{13}\)C. Chemical shifts were also included in the simulations, and those values were obtained from high field measurements. The simulated FIDs were modeled using the same experimental conditions in which the JCS were acquired using a dwell time of 100 \(\upmu\)s and 50 k points. The experimental spectra were collected using a tuned resonant circuit, which preferentially enhances certain frequencies. The instrument response of the tuned circuit without a sample is shown in Figure 2 and demonstrates that the \({}^{19}\)F response was \(\approx\)1.5x larger than the \({}^{1}\)H response. Therefore, the \({}^{19}\)F spectra were first normalized by a factor of 1.5 and then the entire JCS (both \({}^{19}\)F and \({}^{1}\)H) regions were normalized to the highest intensity peak. The best fits were obtained using a nonlinear least square fit set to minimize the \(R\)-factor, which is defined as  
\[R-\text{factor}=100\sqrt{\frac{\text{RSS}}{\sum_{j=1}^{n}\left(I_{j,exp} \right)^{2}}} \tag{3}\]  
where \(n\) is the number of data points, and \(I_{j,\text{exp}}\) is the intensity of the \(j^{\text{th}}\) data point. RSS is the residual sum of squares defined as  
\[\text{RSS}=\sum_{j=1}^{n}\left(I_{j,exp}-I_{j,sim}\right)^{2} \tag{4}\]  
where \(I_{j,\text{exp}}\) and \(I_{j,\text{sim}}\) are the intensities of the experimental and simulated spectra for the \(j^{\text{th}}\) data point in the spectrum. The nonlinear least squares fit optimized all \(J\)-couplings and the relaxation rates of F and H to the nearest 0.01 Hz. It was assumed that the \(T_{1}\) and \(T_{2}\) relaxation times were equivalent, which is an appropriate approximation at these magnetic fields [17]. The magnetic field, \(J\)-couplings, and relaxation rates were then manually adjusted for each molecule to achieve the smallest \(R\)-factor, using between 3-18 parameters depending on the molecule or mixture. The MATLAB simulation and optimization scripts are provided in the Supplementary Information. A summary of the fitting parameters is given in Tables 1 and 2. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Compound** & \begin{tabular}{c} **Parameters** \\ **Optimized** \\ \end{tabular} & \begin{tabular}{c} **\(B_{0}\)** \\ **(\(\mu\)T)** \\ \end{tabular} & \begin{tabular}{c} **\({}^{19}\)F Relaxation** \\ **Rates (Hz)** \\ \end{tabular} & \begin{tabular}{c} **\({}^{1}\)H Relaxation** \\ **Rates (Hz)** \\ \end{tabular} & \
\begin{tabular}{c} **RSS** \\ **(\%)** \\ \end{tabular} &
\begin{tabular}{c} **\(R\)-Factor** \\ **(\%)** \\ \end{tabular} \\ \hline Benzene+ Hexafluorobenzene & 3 & 51.64 & 0.31 & 0.31 & 0.26 & 14 \\ Monofluoobenzene & 12 & 51.55 & 0.20 & 0.20 & 0.14 & 9.0 \\
1,2-Difluorobenzene & 12 & 51.56 & 0.15 & 0.14 & 0.23 & 13 \\
1,3-Difluorobenzene & 12 & 51.59 & 0.14 & 0.14 & 0.98 & 19 \\
1,4-Difluorobenzene & 9 & 51.56 & 0.13 & 0.12 & 0.26 & 11 \\
1,2,4-Trifluorbenzene & 18 & 51.58 & 0.11 & 0.11 & 1.01 & 24 \\
1,2,4,5-Tetrafluorobenzene & 9 & 51.57 & 0.11 & 0.11 & 0.89 & 19 \\ Pentafluorobenzene & 12 & 51.56 & 0.11 & 0.11 & 0.37 & 15 \\ \hline \hline \end{tabular}
\end{table}