  Fingerprint analysis is a ubiquitous tool for pattern recognition with
applications spanning from geolocation and DNA analysis to facial recognition
and forensic identification. Central to its utility is the ability to provide
accurate identification without an a priori mathematical model for the pattern.
We report a data-driven fingerprint approach for nanoelectromechanical systems
mass spectrometry (NEMS-MS) that enables mass measurements of particles and
molecules using complex, uncharacterized nanoelectromechanical devices of
arbitrary specification. NEMS-MS is based on the frequency shifts of the NEMS
vibrational modes induced by analyte adsorption. The sequence of frequency
shifts constitutes a fingerprint of this adsorption, which is directly amenable
to pattern matching. Two current requirements of NEMS-based mass spectrometry
are: (1) a priori knowledge or measurement of the device mode-shapes, and (2) a
mode-shape-based model that connects the induced modal frequency shifts to mass
adsorption. This may not be possible for advanced NEMS with three-dimensional
mode-shapes and nanometer-sized features. The advance reported here eliminates
this impediment, thereby allowing device designs of arbitrary specification and
size to be employed. This enables the use of advanced NEMS devices with complex
vibrational modes, which offer unprecedented prospects for attaining the
ultimate detection limits of nanoelectromechanical mass spectrometry.
