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Enise Kartal

Publications and source records attributed to Enise Kartal.

3 recordsLinked to original sources

Frequency Stability of Graphene Nonlinear Parametric Oscillator

High-frequency stability is crucial for the performance of graphene resonators in sensing and timekeeping applications. However, the extreme miniaturization and high mechanical compliance that make graphene attractive also render it highly susceptible to nonlinearities, degrading frequency stability. Here, we demonstrate that graphene parametric oscillators provide an alternative nonlinear operating regime, where short-term frequency stability can be enhanced despite strong nonlinearity. By operating graphene resonators in a phase-locked loop (PLL), we experimentally demonstrate that parametric oscillations in the post-bifurcation regime achieve lower Allan deviation at fast integration times than Duffing oscillations at identical amplitudes. This improvement originates from strong nonlinear damping inherent to parametric oscillators, which suppresses amplitude-to-frequency noise conversion at large amplitudes. A minimal theoretical model captures observed phase diffusion and identifies nonlinear damping as the dominant mechanism governing phase noise reduction. These results highlight the role of nonlinear dissipation in enabling precision sensing beyond conventional limits of graphene oscillators.

cond-mat.mes-hall

Ultrafast Reservoir Computing based on Nonlinear Nanomechanical Resonators at Ambient Conditions

Reservoir computing offers an energy-efficient alternative to deep neural networks (DNNs) by replacing complex hidden layers with a fixed nonlinear system and training only the final layer. This work investigates nanoelectromechanical system (NEMS) resonators for reservoir computing, utilizing inherent nonlinearities and the fading memory effect from NEMS's transient response. This approach transforms input data into a higher-dimensional space for effective classification. The smaller size and higher operating frequencies of the NEMS resonators enable faster processing rates than recent demonstrations with micromechanical systems, while their compact footprint and ability to operate under ambient conditions simplify integration into practical applications. Through an MNIST handwritten digit recognition test, this system achieved 90% accuracy with a 3.3-microsecond processing time per pixel, highlighting the potential for various applications that require efficient and fast information processing in resource-constrained environments.

physics.app-ph

Atmospheric Pressure Mass Spectrometry by Single-Mode Nanoelectromechanical Systems

Weighing particles above MegaDalton mass range has been a persistent challenge in commercial mass spectrometry. Recently, nanoelectromechanical systems-based mass spectrometry (NEMS-MS) has shown remarkable performance in this mass range, especially with the advance of performing mass spectrometry under entirely atmospheric conditions. This advance reduces the overall complexity and cost, while improving the limit of detection. However, this technique required the tracking of two mechanical modes, and the accurate knowledge of mode shapes which may deviate from their ideal values especially due to air damping. Here, we used a NEMS architecture with a central platform, which enables the calculation of mass by single mode measurements. Experiments were conducted using polystyrene and gold nanoparticles to demonstrate the successful acquisition of mass spectra using a single mode, with improved areal capture efficiency. This advance represents a step forward in NEMS-MS, bringing it closer to becoming a practical application for mass sensing of nanoparticles.

physics.app-ph