arXiv subjects

M. Selim Hanay

Publications and source records attributed to M. Selim Hanay.

18 recordsLinked to original sources

arXiv2026

Statistical Properties of a Fluctuation-Driven Nanomechanical Duffing Resonator

We investigate the fluctuating nonlinear dynamics of multiple modes of a nanomechanical doubly clamped beam resonator. Each mode is driven by Gaussian force noise centered around the resonance; the mode response is monitored while the force magnitude is increased, inducing a transition from harmonic to the nonlinear Duffing regime. To characterize the dynamics, we introduce an effective temperature based on the mode fluctuation amplitude. As the nonlinearity becomes prominent at large amplitudes, we observe a reduction in the effective thermal energy and a crossover in response statistics from Gaussian to platykurtic, consistent with the dynamics expected in a Duffing potential.

cond-mat.mes-hall↗

arXiv2026

Programmable Synchronization Graphs for Adaptive and Fault-Tolerant Modular Miniature Robots

Modular miniature robots could provide scalable function in constrained environments, but coordinating many imperfect modules remains difficult when computation, communication and reliability are limited. A central robotics challenge is to coordinate many actuator-sensor modules without assigning a privileged leader, prescribing a fixed gait template, or relying on dense communication. Here we introduce a programmable synchronization-graph framework for modular miniature robots in which each actuator-sensor pair is represented as a network node and locomotor coordination is encoded through graph coupling. Fixed intra-subgraph links synchronize heterogeneous actuator groups, whereas a small number of signed inter-subgraph links program phase relationships between groups. In physical robot collectives with up to nine modules, graph coupling drives the emergence of synchronization, signed links tune the phase difference from in-phase to out-of-phase motion, and floor experiments produce gallop-like and trot-like contact patterns in a five-module robot assembly. Replacing dense all-to-all coupling with sparse d-regular topologies preserves synchronization while reducing the coupling burden. The same graph representation also captures fault tolerance: increasing graph degree increases the number of module deactivations tolerated before desynchronization. Finally, an upper-confidence-bound edge-selection algorithm learns inter-subgraph links that drive the system toward target phase states. In a separate deactivation benchmark, the graph-based controller avoids the leader-specific failure mode observed in centralized leader-follower control and reduces worst-case phase error by about threefold. These results establish programmable network topology as a compact control layer for gait phase programming, online adaptation and robustness to unit loss in modular miniature robots.

cs.RO↗

arXiv2025

Microwave Cytometry with Machine Learning for Shape-Resolved Microplastic Detection

Microplastics are increasingly recognized as a global environmental health threat, yet their detection and characterization remain constrained by the cost, form factor, and throughput of existing analytical tools. Portable micro/nanotechnology-based sensors are emerging to address this need, but most rely on the assumption of spherical particle geometry in their operating principle, limiting their relevance for environmental analysis. Here, we overcome this limitation by advancing microwave cytometry with machine learning-enabled shape recognition. Microwave cytometry is a flow-through electronic platform that integrates microwave resonator responses with low-frequency impedance signals to capture the dielectric signatures of individual particles. Using microscopy-derived shape measurements as ground truth, we trained a random forest model to decode these information-rich waveforms. Once trained, the system operates without optical input, enabling electronic-only determination of particle geometry. We demonstrate extraction of the major and minor axes of ellipsoidal microparticles with <8% relative error on average and use these predictions to derive the dielectric permittivity of ellipsoid particles. This approach removes long-standing shape assumptions in microplastic sensing and establishes a pathway toward portable, high-throughput, morphology-aware detection technologies.

physics.app-ph↗

arXiv2025

Multistability and Noise-Induced Transitions in Dispersively-Coupled Nonlinear Nanomechanical Modes

We study the noisy dynamics of two coupled bistable modes of a nanomechanical beam. When de-coupled, each driven mode obeys the Duffing equation of motion, with a well-defined bistable region in the frequency domain. When both modes are driven, intermodal dispersive coupling emerges due to the amplitude dependence of the modal frequencies and leads to coupled states of the two modes. We map out the dynamics of the system by sweeping the drive frequencies of both modes in the presence of added noise. The system then samples all accessible states at each combination of frequencies, with the probability of each stable state being proportional to its occupancy time at steady state. In the frequency domain, the system exhibits four stable regions -- one for each coupled state -- which are separated by five curves. These curves are reminiscent of coexistence curves in an equilibrium phase diagram: each curve is defined by robust inter-state transitions, with equal probabilities of finding the system in the two contiguous states. Remarkably, the curves intersect in two triple points, where the system now transitions between three distinct contiguous states. A physical analogy can be made between this nonequilibrium system and a multi-phase thermodynamic system, with possible applications in computing, precision sensing, and signal processing.

cond-mat.mes-hall↗

arXiv2024

Rapid Differentiation between Microplastic Particles Using Integrated Microwave Cytometry with 3D Electrodes

Rapid identification of microparticles in liquid is an important problem in environmental and biomedical applications such as for microplastic detection in water sources and physiological fluids. Existing spectro-scopic techniques are usually slow and not compatible with flow-through systems. Here we analyze single microparticles in the 14 - 20 micrometer range using a combination of two electronic sensors in the same microfluidic system: a microwave capacitive sensor and a resistive pulse sensor. Together, this integrated sen-sor system yields the effective electrical permittivity of the analyte particles. To simplify data analysis, 3D electrode arrangements were used instead of planar electrodes, so that the generated signal is unaffected by the height of the particle in the microfluidic channel. With this platform, we were able to distinguish between polystyrene (PS) and polyethylene (PE) microparticles. We showcase the sensitivity and speed of this tech-nique and discuss the implications for the future application of microwave cytometry technology in the en-vironmental and biomedical fields.

physics.app-ph↗

arXiv2024

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↗

arXiv2024

Three-Dimensional Electrode Integration with Microwave Sensors for Precise Microparticle Detection in Microfluidics

Microwave sensors integrated with microfluidic platforms can provide the size and permittivity of single cells and microparticles. Amongst the microwave sensor topologies, the planar arrangement of electrodes is a popular choice owing to the ease of fabrication. Unfortunately, planar electrodes generate a non-uniform electric field which causes the responsivity of the sensor to depend on the vertical position of a microparticle in the microfluidic channel. To overcome this problem, we fabricated three-dimensional (3D) electrodes at the coplanar sensing region of an underlying microwave resonator. The 3D electrodes are based on SU8 polymer which is then metallized by sputter coating. With this system, we readily characterized a mixture composed of 12 um and 20 um polystyrene particles and demonstrated separation without any position-related calibration. The ratio of the electronic response of the two particle types is approximately equal to the ratio of the particle volumes, which indicates the generation of a uniform electric field at the sensing region. The current work obviates the need for using multiple coplanar electrodes and extensive processing of the data for the calibration of particle height in a microfluidic channel: as such, it enables the fabrication of more sophisticated microwave resonators for environmental and biological applications.

physics.app-ph↗

arXiv2023

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 environmental, material, and biological sciences. To detect nanoparticles, electronic approaches are especially desirable owing to their compactness and lower costs. Indeed, for single-molecule and single-nanoparticle detection, resistive pulse sensing has advanced significantly during the last two decades. While resistive pulse sensing was widely used to obtain the geometric size information, 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. The approach of single nanoparticles near the sensing region and their translocation through the nanopore 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 nm and 50 nm polystyrene nanoparticles to observe single-particle events. Our current implementation was limited by the non-uniform electric field at the sensing region. The work provides a complementary sensing modality for nanoparticle characterization where the dielectric response, rather than the ionic current, determines the signal.

physics.app-ph↗

arXiv2023

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.

eess.IV↗

arXiv2023

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↗

arXiv2023

High Resolution Dielectric Characterization of Single Cells and Microparticles Using Integrated Microfluidic Microwave Sensors

Microwave sensors can probe intrinsic material properties of analytes in a microfluidic channel at physiologically relevant ion concentrations. While microwave sensors have been used to detect single cells and microparticles in earlier studies, the synergistic use and comparative analysis of microwave sensors with optical microscopy for material classification and size tracking applications have been scarcely investigated so far. Here we combined microwave and optical sensing to differentiate microscale objects based on their dielectric properties. We designed and fabricated two types of planar sensor: a Coplanar Waveguide Resonator (CPW) and a Split-Ring Resonator (SRR). Both sensors possessed sensing electrodes with a narrow gap to detect single cells passing through a microfluidic channel integrated on the same chip. We also show that standalone microwave sensors can track the relative changes in cellular size in real-time. In sensing single 20-micron diameter polystyrene particles, Signal-to-Noise ratio values of approximately 100 for CPW and 70 for SRR sensors were obtained. These findings demonstrate that microwave sensing technology can serve as a complementary technique for single-cell biophysical experiments and microscale pollutant screening.

cond-mat.soft↗

arXiv2021

Atmospheric Pressure Mass Spectrometry of Single Viruses and Nanoparticles by Nanoelectromechanical Systems

Mass spectrometry of intact nanoparticles and viruses can serve as a potent characterization tool for material science and biophysics. Inaccessible by widespread commercial techniques, the mass of single nanoparticles and viruses (>10MDa) can be readily measured by NEMS (Nanoelectromechanical Systems) based Mass Spectrometry, where charged and isolated analyte particles are generated by Electrospray Ionization (ESI) in air and transported onto the NEMS resonator for capture and detection. However, the applicability of NEMS as a practical solution is hindered by their miniscule surface area, which results in poor limit-of-detection and low capture efficiency values. Another hindrance is the necessity to house the NEMS inside complex vacuum systems, which is required in part to focus analytes towards the miniscule detection surface of the NEMS. Here, we overcome both limitations by integrating an ion lens onto the NEMS chip. The ion lens is composed of a polymer layer, which charges up by receiving part of the ions incoming from the ESI tip and consequently starts to focus the analytes towards an open window aligned with the active area of the NEMS electrostatically. With this integrated system, we have detected the mass of gold and polystyrene nanoparticles under ambient conditions and with two orders-of-magnitude improvement in capture efficiency compared to the state-of-the-art. We then applied this technology to obtain the mass spectrum of SARS-CoV-2 and BoHV-1 virions. With the increase in analytical throughput, the simplicity of the overall setup and the operation capability under ambient conditions, the technique demonstrates that NEMS Mass Spectrometry can be deployed for mass detection of engineered nanoparticles and biological samples efficiently.

physics.ins-det↗

arXiv2020

Nanomechanical Measurement of the Brownian Force Noise in a Viscous Liquid

We study the spectral properties of the thermal force giving rise to the Brownian motion of a continuous mechanical system -- namely, a nanomechanical beam resonator -- in a viscous liquid. To this end, we perform two separate sets of experiments. First, we measure the power spectral density (PSD) of the position fluctuations of the resonator around its fundamental mode at its center. Then, we measure the frequency-dependent linear response of the resonator, again at its center, by driving it with a harmonic force that couples well to the fundamental mode. These two measurements allow us to determine the PSD of the Brownian force noise acting on the structure in its fundamental mode. The PSD of the force noise extracted from multiple resonators spanning a broad frequency range displays a "colored spectrum". Using a single-mode theory, we show that, around the fundamental resonances of the resonators, the PSD of the force noise follows the dissipation of a blade oscillating in a viscous liquid -- by virtue of the fluctuation-dissipation theorem.

cond-mat.other↗

arXiv2019

Phase-Locked Loop based Resonant Sensors: A Rigorous Theory and General Analysis Framework for Deciphering Fundamental Sensitivity Limitations due to Noise

Nanomechanical resonators are used in building ultra-sensitive mass and force sensors. In a widely used resonator based sensing paradigm, each modal resonance frequency is tracked with a phase-locked loop (PLL) based system. There is great interest in deciphering the fundamental sensitivity limitations due to inherent noise and fluctuations in PLL based resonant sensors to improve their performance. In this paper, we present a precise, first-principles based theory for the analysis of PLL based resonator tracking systems. Based on this theory, we develop a general, rigorously-derived noise analysis framework for PLL based sensors. We apply this framework to a setting where the sensor performance is mainly limited by the thermomechanical noise of the nanomechanical resonator. The results that are deduced through our analysis framework are in complete agreement with the ones we obtain from extensive, carefully run stochastic simulations of a PLL based sensor system. We compare the conclusions we derive with the recent results in the literature. Our theory and analysis framework can be used in assessing PLL based sensor performance with other sources of noise, e.g., from the electronic components, actuation and sensing mechanisms, and due to the signal generator, as well as for a variety of PLL based sensor configurations such as multi-mode and nonlinear sensing.

physics.app-ph↗

arXiv2019

Full Electrostatic Control of Nanomechanical Buckling

Buckling at the micro and nanoscale generates distant bistable states which can be beneficial for sensing, shape-reconfiguration and mechanical computation applications. Although different approaches have been developed to access buckling at small scales, such as the use heating or pre-stressing beams, very little attention has been paid so far to dynamically and precisely control all the critical bifurcation parameters, the compressive stress and the lateral force on the beam. Precise and on-demand generation of compressive stress on individually addressable microstructures is especially critical for morphologically reconfigurable devices. Here, we develop an all-electrostatic architecture to control the compressive force, as well as the direction and amount of buckling, without significant heat generation on micro/nano structures. With this architecture, we demonstrated fundamental aspects of device function and dynamics. By applying voltages at any of the digital electronics standards, we have controlled the direction of buckling. Lateral deflections as large as 12% of the beam length were achieved. By modulating the compressive stress and lateral electrostatic force acting on the beam, we tuned the potential energy barrier between the post-bifurcation stable states and characterized snap-through transitions between these states. The proposed architecture opens avenues for further studies that can enable efficient actuators and multiplexed shape-shifting devices.

physics.app-ph↗

arXiv2019

Nonlinear Nanomechanical Mass Spectrometry at the Single-Nanoparticle Level

Nanoelectromechanical Systems (NEMS) have emerged as a promising technology for performing the mass spectrometry of large biomolecules and nanoparticles. As nanoscale objects land on NEMS sensor one by one, they induce resolvable shifts in the resonance frequency of the sensor proportional to their weight. The operational regime of NEMS sensors is often limited by the onset-of-nonlinearity, beyond which the highly sensitive schemes based on frequency tracking by phase-locked loops cannot be readily used. Here, we develop a measurement architecture to operate at the nonlinear regime and measure frequency shifts induced by analytes in a rapid and sensitive manner. We used this architecture to individually characterize the mass of gold nanoparticles and verified the results by performing independent measurements of the same nanoparticles based on linear mass sensing. Once the feasibility of the technique is established, we have obtained the mass spectrum of a 20 nm gold nanoparticle sample by individually recording about five hundred single particle events using two modes working sequentially in the nonlinear regime. The technique obtained here can be used for thin nanomechanical structures which possess a limited dynamic range.

cond-mat.mes-hall↗

arXiv2017

Mode-shape perturbation induced by analyte adsorption in nanomechanical sensors

Nanomechanical resonators offer important benefits for the sensing of physical stimuli such as the mass of an added molecule. To map out the local shape properties of the physical stimuli, such as the distribution of the mass density of a molecule, sensory information should be collected through multiple modes of a mechanical sensor. By utilizing the specific mode shapes, the spatial distribution of a physical stimulus can be reverse calculated. However, the mode shapes of a sensor may deviate from their ideal forms once analytes start to accumulate on the sensor. As a result, algorithms based on the ideal form of the mode shapes no longer work accurately. Here, we developed a theoretical framework to calculate the change in the mode shapes of a nanomechanical beam after analyte adsorption. We verified the theoretical model by performing finite element simulations and comparing the change in the mode shapes obtained from each approach. Monte Carlo simulations were performed to relate the maximum deviation in the mode shapes to the surface roughness of the sensor after analyte accumulation. By predicting the change in the mode shapes and using the corrected forms, the accuracy of the nanomechanical sensing can be improved significantly.

physics.app-ph↗

arXiv2017

Spatially Resolved Sensing in Microfluidics with Multimode Microwave Resonators

The analogy between mechanical and electromagnetic resonators has been a celebrated paradigm of science and engineering. Exploration of this analogy in recent years has resulted in several exciting research directions, including cavity optomechanics[1], phononic bandgap materials[2] and phononic metamaterials[3-5]. In these examples, progress in electromagnetic research has usually led the way for their mechanical counterparts. Here, we contribute to this analogy from a different perspective by adapting a sensing technique originally developed for mechanical devices to increase the capabilities of sensors based on electromagnetic fields. More specifically, multimode resonance techniques, which enable spatial resolution in inertial mass sensing experiments with nanoelectromechanical systems (NEMS), are tailored for use in microwave resonant sensing, which is commonly employed in microfluidics. We show that the use of higher-order modes of such sensors can provide electrical volume, position and geometric size data. The combination of such spatial features implies the potential for image reconstruction when a large number of modes are used. With the analytical and experimental framework presented here, we can move beyond simple counting and achieve the sizing and imaging of analytes with impedance spectroscopy.

cond-mat.mes-hall↗