Microtubules are hollow cylindrical polymers composed of the highly negatively-charged (~23e), high dipole moment (1750 D) protein α, β- tubulin. While the roles of microtubules in chromosomal segregation, macromolecular transport, and cell migration are relatively well-understood, studies on the electrical properties of microtubules have only recently gained strong interest. Here, we show that while microtubules at physiological concentrations increase solution capacitance, free tubulin has no appreciable effect. Further, we observed a decrease in electrical resistance of solution, with charge transport peaking between 20–60 Hz in the presence of microtubules, consistent with recent findings that microtubules exhibit electric oscillations at such low frequencies. We were able to quantify the capacitance and resistance of the microtubules (MT) network at physiological tubulin concentrations to be 1.27 × 10−5 F and 9.74 × 104 Ω. Our results show that in addition to macromolecular transport, microtubules also act as charge storage devices through counterionic condensation across a broad frequency spectrum. We conclude with a hypothesis of an electrically tunable cytoskeleton where the dielectric properties of tubulin are polymerisation-state dependent.
We describe the use of monolithic, buckled-dome cavities as ultrasound sensors. Patterned delamination within a compressively stressed thin film stack produces high-finesse plano-concave optical resonators with sealed and empty cavity regions. The buckled mirror also functions as a flexible membrane, highly responsive to changes in external pressure. Owing to their efficient opto-acousto-mechanical coupling, thermal-displacement-noise limited sensitivity is achieved at low optical interrogation powers and for modest optical (Q ∼ 103) and mechanical (Q ∼ 102) quality factors. We predict and verify broadband (up to ∼ 5 MHz), air-coupled ultrasound detection with noise-equivalent pressure (NEP) as low as ∼ 30-100 µPa/Hz1/2. This corresponds to an ultrasonic force sensitivity ∼ 2 × 10−13 N/Hz1/2 and enables the detection of MHz-range signals propagated over distances as large as ∼ 20 cm in air. In water, thermal-noise-limited sensitivity is demonstrated over a wide frequency range (up to ∼ 30 MHz), with NEP as low as ∼ 100-800 µPa/Hz1/2. These cavities exhibit a nearly omnidirectional response, while being ∼ 3-4 orders of magnitude more sensitive than piezoelectric devices of similar size. Easily realized as large arrays and naturally suited to direct coupling by free-space beams or optical fibers, they offer significant practical advantages over competing optical devices, and thus could be of interest for several emerging applications in medical and industrial ultrasound imaging.
The bulk acoustic modes of liquid droplets, well understood from a theoretical perspective, have rarely been observed experimentally. Here, we report the indirect observation of acoustic vibrational modes in a picoliter-scale droplet, extending up to ∼40 MHz. This was achieved by coupling the droplet to an ultra-sensitive optomechanical sensor, which operates in a thermal-noise limited regime and with a substantial contribution from acoustic noise in the ambient medium. The droplet vibrational modes manifest as Fano resonances in the thermal noise spectrum of the sensor. This is among the few reported observations of droplet acoustic modes and of Fano interactions in a coupled mechanical oscillator system driven only by thermal Brownian motion.
We present a hexagonal boron nitride (hBN) polymer-assisted transfer technique and discuss subtleties about the process. We then demonstrate localized emission from strained regions of the film draped over features on a prepatterned substrate. Notably, we provide insight into the brightness distribution of these emitters and show that the brightest emission is clearly localized to the underlying substrate features rather than unintentional wrinkles present in the hBN film. Our results aide in the current discussion surrounding scalability of single photon emitter arrays.
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