&A however, C detection is inherently less sensitive than H detection. Second, slower relaxation and the need for high-power H decoupling in solids necessitate longer recycle delays. For these reasons, employing three or more dimensions in MAS NMR experiments has not yet become common practice. In solution NMR, more efficient acquisition has relied on non-uniform sampling (NUS), which has been successfully applied to multidimensional experiments on larger systems. Although extending NUS to MAS NMR would be of enormous practical importance, the application of conventional NUS methods to MAS NMR has been limited by the specific problem of accurately modeling weak signals in noisy spectra, in addition to the general problems of quantitative spectral reconstruction and slow computation. The lower sensitivity in MAS NMR experiments requires an unprecedented robustness of any NUS method to minimize artifacts. Herein, we address these challenges with SIFT (spectroscopy by integration of frequency and time domain information), a rapid and model-free method for computing a NMR spectrum from a NUS time-domain dataset. SIFTworks by replacing missing information in the time domain with a priori knowledge of “dark” regions in the frequency domain; that is, those regions known to contain no NMR signals. The frequency domain information, assimilated by a very rapid computational process, obviates some time-domain sampling with no sacrifice in resolution and no modeling bias. We previously used SIFT to process 2D NUS N-HSQC solution data, where dark regions created by over-sampling were utilized to replace up to 75% of the uniform timedomain data points. We demonstrate the effectiveness of the SIFT method in solids, using dark regions resulting from the need for rotor-synchronized sampling in the indirect dimensions. Unlike other NUS data processing methods that actively model signals to reconstruct a spectrum, SIFT suppresses the sampling noise by using only definitive information from the dark spectral areas. Thus, SIFT avoids bias from subjective discrimination between weak signals and noise, and reconstructs missing time data points with high fidelity, as if they had been actually recorded. These favorable properties make SIFT uniquely suited for processing NUS data in the sensitivity-limited regime. To demonstrate the application of SIFT to NUS MAS NMR, we recorded a 3D NCOCX spectrum (Figure 1a ) of a microcrystalline, uniformly [N,C]-labeled sample of the b1 domain of protein G (GB1) at high digital resolution (1.1 ppm for F1, 0.7 ppm for F2, before zero-filling). For both t1 and t2, the dwell time was synchronized to three times the rotor period, 3/nR (bandwidth equal to nR/3 Hz), in order to fold the