Data-driven fingerprint nanoelectromechanical mass spectrometry
Nature Communications volume 15, Article number: 8800 (2024 ) Cite this article
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 that enables mass measurements of particles and molecules using complex, uncharacterized nanoelectromechanical devices of arbitrary specification. Nanoelectromechanical systems mass spectrometry is based on the frequency shifts of the nanoelectromechanical device vibrational modes that are 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 nanoelectromechanical-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 nanoelectromechanical devices 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 nanoelectromechanical devices with complex vibrational modes, which offer unprecedented prospects for attaining the ultimate detection limits of nanoelectromechanical mass spectrometry.
Mass spectrometry is used across a broad spectrum of applications, ranging from the chemical identification of compounds to the sequencing of proteins and its use in drug discovery1,2,3,4,5,6,7. These applications discriminate between analytes based on their mass-to-charge (\(m/z\) ) ratio, often in combination with an initial chromatographic separation. In proteomic analysis, \(m/z\) analysis is often complemented with information about the fragmentation patterns of proteins and protein complexes from which bioinformatics can enable the identification of the original, intact analyte6,8,9,10,11.
