Dataset for publication: "Harnessing nonlinearity for mode-shape independent nanomechanical mass spectrometry across extreme mass scales (from Da to GDa)"

Nanomechanical mass spectrometry enables the detection of both ionized and neutral particles by tracking shifts in resonance frequencies, offering a powerful platform for single-particle analysis. However, existing approaches typically rely on prior knowledge of vibrational mode shapes, which becomes increasingly difficult to obtain for nanoscale devices. Although such systems offer exceptional sensitivity down to single proteins, their limited linear dynamic range makes them highly susceptible to nonlinear effects, particularly complicating resonance tracking and rendering mode-shape estimation impractical. These limitations restrict accurate mass determination for large analytes and under realistic operating conditions, thereby limiting the broader applicability of nanomechanical spectrometry. Here we introduce a nonlinear nanomechanical mass spectrometry approach that harnesses these effects rather than suppressing them. The method enables the determination of analyte mass over a broad range, from daltons to gigadaltons, on devices of arbitrary geometry without requiring prior knowledge of vibrational mode shapes. In this framework, analyte identification relies solely on bifurcation frequency shifts measured in two consecutive vibrational modes of a nonlinear resonator. We develop a theoretical model that captures the mechanisms underlying this nonlinear response and validate the approach experimentally using frequency-shift measurements from a nanomechanical resonator. Monte Carlo probabilistic analysis is further employed to quantify the achievable accuracy in mass estimation. This study establishes a new route for nanomechanical mass spectrometry and provides a platform to explore the interplay between nonlinear dynamics, analyte properties and modal behavior across extreme mass scales.