Optimized ¹³C qNMR for Complex Mixtures through Relaxation Engineering and Signal-to-Noise Efficiency Metrics

Quantitative analysis of structurally analogous constituents in complex mixtures remains a central challenge in analytical chemistry. Here, we present an optimized ¹³C quantitative NMR (¹³C qNMR) methodology that systematically addresses its two major limitations: prolonged acquisition times and inherently low sensitivity. Incorporation of a paramagnetic relaxation agent reduced ¹³C longitudinal relaxation times (T1) by up to 95%, enabling a 65% reduction in total acquisition time while preserving spectral resolution. To rationalize parameter selection, we introduce for the first time a signal-to-noise efficiency factor (η = SNR²/T), which provides a quantitative metric for balancing sensitivity against experiment duration. Factorial evaluation of sample concentration and number of scan (NS) using η established acquisition conditions that minimized sample consumption while maximizing efficiency. The optimized workflow demonstrated excellent quantitative reliability, with <1% deviation compared to HPLC-UV, and was successfully applied to quantify multiple saponins in a Panax notoginseng extract. Overall, this study establishes a robust, reference-material-independent ¹³C qNMR platform, where relaxation acceleration and η-based optimization together advance the technique into a versatile tool for the quantitative analysis of natural, biological, and environmental mixtures.