where F s (q) and F e (q) are form factors from a simulation and experiment, respectively, ∆F e (q) is the error of the experimental form factor, and summation goes over the experimentally available N q points. Also, a quality measure based on differences in the simulated and experimental form factors across the available q-range is defined in the SIMtoEXP program . However, the lobe heights in the simulated form factors depend on the simulation box size, as shown in Fig. ; consequently, the quality measure defined in SIMtoEXP would also depend on the simulation box size. In contrast, locations of the form factor minima (or, in precise terms: the minima of the absolute value of the form factor) are independent of the simulation box size (Fig. ). Here we use only the location of the first form factor minimum for quality evaluation, because (due to fluctuations) the location of the second minimum is difficult to detect automatically in some experimental data sets, such as the POPE data in Figs. . The first minimum correlates well with the thickness of a membrane (Fig. ), although the correlation of the second minima would be even stronger (Fig. ). In practise, we first filter the fluctuations from the form factor data using the Savitzky-Golay filter (window length 30 and polynomial order 1) and locate the first minimum at q > 0.1 Å -1 from both simulation (FF sim min ) and experiment (FF exp min ). The quality of a form factor is then defined as the Euclidean distance between the minima locations: FF q = |FF sim min -FF exp min | × 100. The quality evaluation of form factors is implemented in /Scripts/BuildDatabank/QualityEvaluation.py in the NMRlipids Databank repository. The resulting form factor qualities are stored in files named FormFactorQuality.json at folders in /Data/Simulations in the NMRlipids Databank repository.