Image Processing Methods Applied to Motion Tracking of Nanomechanical Buckling on SEM Recordings

The scanning electron microscope (SEM) recordings of dynamic nano-electromechanical systems (NEMS) are difficult to analyze due to the noise caused by low frame rate, insufficient resolution and blurriness induced by applied electric potentials. Here, we develop an image processing algorithm enhanced by the physics of the underlying system to track the motion of buckling NEMS structures in the presence of high noise levels. The algorithm is composed of an image filter, two data filters, and a nonlinear regression model, which utilizes the expected form of the physical solution. The method was applied to the recordings of a NEMS beam about 150 nm wide, undergoing intra-and inter-well post-buckling states with a transition rate of approximately 0.5 Hz. The algorithm can track the dynamical motion of the NEMS and capture the dependency of deflection amplitude on the compressive force on the beam. With the help of the proposed algorithm, the transition from inter-well to intra-well motion is clearly resolved for buckling NEMS imaged under SEM.Comment: 7 pages, 7 figures. 1 Supplementary Vide

Efficient sensing of single viruses and nanoparticles by nanomechanical sensors integrated with ion lenses

Nanoelectromechanical Systems (NEMS) resonators can be used to detect, weigh and identify single nanoparticles and viruses. Given their small footprint, however, NEMS are plagued by low analyte detection rate since the active sensing cross-sections to capture analyte particles is very small. Here we report on the development of an on-chip focusing lens operating in air and integrated with the NEMS sensor. The integrated system increases the capture efficiency by orders of magnitude, and allows for operation under ambient conditions to measure the mass of nanoparticles and virions. With this system, mass spectrum of nanoparticle samples and mammalian viruses at biologically relevant concentrations can be characterized within less than 30 minutes

Dielectric Detection of Single Nanoparticles Using a Microwave Resonator Integrated with a Nanopore

The characterization of individual nanoparticles in a liquid constitutes a critical challenge for the environmental, material, and biological sciences. To detect nanoparticles, electronic approaches are especially desirable owing to their compactness and lower costs. While electronic detection in the form of resistive-pulse sensing has enabled the acquisition of geometric properties of various analytes, impedimetric measurements to obtain dielectric signatures of nanoparticles have scarcely been reported. To explore this orthogonal sensing modality, we developed an impedimetric sensor based on a microwave resonator with a nanoscale sensing gap surrounding a nanopore built on a 220 nm silicon nitride membrane. The microwave resonator has a coplanar waveguide configuration with a resonance frequency of approximately 6.6 GHz. The approach of single nanoparticles near the sensing region and their translocation through the nanopores induced sudden changes in the impedance of the structure. The impedance changes, in turn, were picked up by the phase response of the microwave resonator. We worked with 100 and 50 nm polystyrene nanoparticles to observe single-particle events. Our current implementation was limited by the nonuniform electric field at the sensing region. This work provides a complementary sensing modality for nanoparticle characterization, where the dielectric response, rather than ionic current, determines the signal