Long distance manipulation of a levitated nanoparticle in high vacuum

Accurate delivery of small targets in high vacuum is a pivotal task in many branches of science and technology. Beyond the different strategies developed for atoms, proteins, macroscopic clusters and pellets, the manipulation of neutral particles over macroscopic distances still poses a formidable challenge. Here we report a novel approach based on a mobile optical trap operated under feedback control that enables long range 3D manipulation of a silica nanoparticle in high vacuum. We apply this technique to load a single nanoparticle into a high-finesse optical cavity through a load-lock vacuum system. We foresee our scheme to benefit the field of optomechanics with levitating nano-objects as well as ultrasensitive detection and monitoring.Comment: 12 pages 5 figure

Noise Spectrum as a Source of Information in Gas Sensors Based on Liquid-Phase Exfoliated Graphene

Surfaces of adsorption-based gas sensors are often heterogeneous, with adsorption sites that differ in their affinities for gas particle binding. Knowing adsorption/desorption energies, surface densities and the relative abundance of sites of different types is important, because these parameters impact sensor sensitivity and selectivity, and are relevant for revealing the response-generating mechanisms. We show that the analysis of the noise of adsorption-based sensors can be used to study gas adsorption on heterogeneous sensing surfaces, which is applicable to industrially important liquid-phase exfoliated (LPE) graphene. Our results for CO2 adsorption on an LPE graphene surface, with different types of adsorption sites on graphene flake edges and basal planes, show that the noise spectrum data can be used to characterize such surfaces in terms of parameters that determine the sensing properties of the adsorbing material. Notably, the spectrum characteristic frequencies are an unambiguous indicator of the relative abundance of different types of adsorption sites on the sensing surface and their surface densities. We also demonstrate that spectrum features indicate the fraction of the binding sites that are already occupied by another gas species. The presented study can be applied to the design and production of graphene and other sensing surfaces with an optimal sensing performance

Reliable fabrication of transparent conducting films by cascade centrifugation and Langmuir–Blodgett deposition of electrochemically exfoliated graphene

Electrochemical exfoliation is an efficient and scalable method to obtain liquid-phase graphene. Graphene in solution, obtained through electrochemical exfoliation or other methods, is typically polydisperse, containing particles of various sizes, which is not optimal for applications. We employed cascade centrifugation to select specific particle sizes in solution and prepared thin films from those graphene particles using the Langmuir–Blodgett assembly. Employing centrifugation speeds of 3, 4, and 5 krpm, further diluting the solutions in different volumes of solvent, we reliably and consistently obtained films of tunable thickness. We show that there is a limit to how thin these films can be, which is imposed by the percolation threshold. The percolation threshold is quantitatively compared to results found in literature that are obtained using other, more complex graphene film fabrication methods, and is found to occur with a percolation exponent and percolative figure of merit that are of the same order as results in literature. A maximum optical transparency of 82.4% at a wavelength of 660 nm is obtained for these films, which is in agreement with earlier works on Langmuir–Blodgett assembled ultrasonic-assisted liquid-phase exfoliated graphene. Our work demonstrates that films that are in all respects on par with films of graphene obtained through other solution-based processes can be produced from inexpensive and widely available centrifugal post-processing of existing commercially available solutions of electrochemically exfoliated graphene. The demonstrated methodology will lower the entry barriers for new research and industrial uses, since it allows researchers with no exfoliation experience to make use of widely available graphene materials

Ultrafast humidity sensor based on liquid phase exfoliated graphene

Humidity sensing is important to a variety of technologies and industries, ranging from environmental and industrial monitoring to medical applications. Although humidity sensors abound, few available solutions are thin, transparent, compatible with large-area sensor production and flexible, and almost none are fast enough to perform human respiration monitoring through breath detection or real-time finger proximity monitoring via skin humidity sensing. This work describes chemiresistive graphene-based humidity sensors produced in few steps with facile liquid phase exfoliation (LPE) followed by Langmuir-Blodgett assembly that enables active areas of practically any size. The graphene sensors provide a unique mix of performance parameters, exhibiting resistance changes up to 10% with varying humidity, linear performance over relative humidity (RH) levels between 8% and 95%, weak response to other constituents of air, flexibility, transparency of nearly 80%, and response times of 30 ms. The fast response to humidity is shown to be useful for respiration monitoring and real-time finger proximity detection, with potential applications in flexible touchless interactive panels.Comment: 18 pages, 13 figure

Monolayer Gas Adsorption on Graphene-Based Materials: Surface Density of Adsorption Sites and Adsorption Capacity

Surface density of adsorption sites on an adsorbent (including affinity-based sensors) is one of the basic input parameters in modeling of process kinetics in adsorption based devices. Yet, there is no simple expression suitable for fast calculations in current multiscale models. The published experimental data are often application-specific and related to the equilibrium surface density of adsorbate molecules. Based on the known density of adsorbed gas molecules and the surface coverage, both of these in equilibrium, we obtained an equation for the surface density of adsorption sites. We applied our analysis to the case of pristine graphene and thus estimated molecular dynamics of adsorption on it. The monolayer coverage was determined for various pressures and temperatures. The results are verified by comparison with literature data. The results may be applicable to modeling of the surface density of adsorption sites for gas adsorption on other homogeneous crystallographic surfaces. In addition to it, the obtained analytical expressions are suitable for training artificial neural networks determining the surface density of adsorption sites on a graphene surface based on the known binding energy, temperature, mass of adsorbate molecules and their affinity towards graphene. The latter is of interest for multiscale modelling

Influence of UV radiation on the time response of a resistive gas sensor based on liquid-phase exfoliated graphene

Herein we investigate the influence of UV irradiation on the time response of a resistive gas sensor with a liquid-phase exfoliated graphene as the active material. The effect of exposure to UV light on the baseline electrical resistance (in inert atmosphere) will be compared with the effect of the annealing process. The influence of various intensities of UV radiation on the response and recovery time, repeatability and detection limit of graphene will be discussed

Characterization of heterogeneous sensing layers in graphene-based gas sensors

Graphene-based sensors have a great potential for applications in public and personal health protection, including defense and security fields. However, sensitivity and selectivity of such sensors are inherently dependent on adsorption properties of the graphene sensing layer, which is typically of heterogeneous morphology and/or of heterogeneous chemical composition due to intentionally introduced functionalizing elements or spontaneously adsorbed molecules during sensor fabrication or operation. Therefore, characterization and optimization of sensing layers is extremely important for achieving high sensing performance. In this work, we present a method for characterization of the heterogeneous sensing layer by using the frequency domain analysis of the sensor output signal. The method is based on the mathematical model we devised. Here, the model is presented in detail for the case of a surface with three types of adsorption sites, and then the method is applied for extraction of parameters that characterize adsorption properties of a graphene sensing layer