41 research outputs found

    Characterization of Nanoparticle Release from Surface Coatings by the Simulation of a Sanding Process

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    Nanoparticles are used in industrial and domestic applications to control customized product properties. But there are several uncertainties concerning possible hazard to health safety and environment. Hence, it is necessary to search for methods to analyze the particle release from typical application processes. Based on a survey of commercial sanding machines, the relevant sanding process parameters were employed for the design of a miniature sanding test setup in a particle-free environment for the quantification of the nanoparticle release into air from surface coatings. The released particles were moved by a defined airflow to a fast mobility particle sizer and other aerosol measurement equipment to enable the determination of released particle numbers additionally to the particle size distribution. First, results revealed a strong impact of the coating material on the swarf mass and the number of released particles

    Demonstration of Bias-Controlled Algorithmic Tuning of Quantum Dots in a Well (DWELL) MidIR Detectors

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    The quantum-confined Stark effect in intersublevel transitions present in quantum-dots-in-a-well (DWELL) detectors gives rise to a midIR spectral response that is dependent upon the detector\u27s operational bias. The spectral responses resulting from different biases exhibit spectral shifts, albeit with significant spectral overlap. A postprocessing algorithm was developed by Sakoglu that exploited this bias-dependent spectral diversity to predict the continuous and arbitrary tunability of the DWELL detector within certain limits. This paper focuses on the experimental demonstration of the DWELL-based spectral tuning algorithm. It is shown experimentally that it is possible to reconstruct the spectral content of a target electronically without using any dispersive optical elements for tuning, thereby demonstrating a DWELL-based algorithmic spectrometer. The effects of dark current, detector temperature, and bias selection on the tuning capability are also investigated experimentally

    An ultra-compact particle size analyser using a CMOS image sensor and machine learning

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    Light scattering is a fundamental property that can be exploited to create essential devices such as particle analysers. The most common particle size analyser relies on measuring the angle-dependent diffracted light from a sample illuminated by a laser beam. Compared to other non-light-based counterparts, such a laser diffraction scheme offers precision, but it does so at the expense of size, complexity and cost. In this paper, we introduce the concept of a new particle size analyser in a collimated beam configuration using a consumer electronic camera and machine learning. The key novelty is a small form factor angular spatial filter that allows for the collection of light scattered by the particles up to predefined discrete angles. The filter is combined with a light-emitting diode and a complementary metal-oxide-semiconductor image sensor array to acquire angularly resolved scattering images. From these images, a machine learning model predicts the volume median diameter of the particles. To validate the proposed device, glass beads with diameters ranging from 13 to 125 µm were measured in suspension at several concentrations. We were able to correct for multiple scattering effects and predict the particle size with mean absolute percentage errors of 5.09% and 2.5% for the cases without and with concentration as an input parameter, respectively. When only spherical particles were analysed, the former error was significantly reduced (0.72%). Given that it is compact (on the order of ten cm) and built with low-cost consumer electronics, the newly designed particle size analyser has significant potential for use outside a standard laboratory, for example, in online and in-line industrial process monitoring

    Quantum Transduction of Telecommunications-band Single Photons from a Quantum Dot by Frequency Upconversion

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    The ability to transduce non-classical states of light from one wavelength to another is a requirement for integrating disparate quantum systems that take advantage of telecommunications-band photons for optical fiber transmission of quantum information and near-visible, stationary systems for manipulation and storage. In addition, transducing a single-photon source at 1.3 {\mu}m to visible wavelengths for detection would be integral to linear optical quantum computation due to the challenges of detection in the near-infrared. Recently, transduction at single-photon power levels has been accomplished through frequency upconversion, but it has yet to be demonstrated for a true single-photon source. Here, we transduce the triggered single-photon emission of a semiconductor quantum dot at 1.3 {\mu}m to 710 nm with a total detection (internal conversion) efficiency of 21% (75%). We demonstrate that the 710 nm signal maintains the quantum character of the 1.3 {\mu}m signal, yielding a photon anti-bunched second-order intensity correlation, g^(2)(t), that shows the optical field is composed of single photons with g^(2)(0) = 0.165 < 0.5.Comment: 7 pages, 4 figure

    Construcción y calibración de una celda de sedimentación gravimétrica para la medición fotométrica de la distribución de tamaño de micro partículas

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    El presente trabajo muestra la base teórica, el desarrollo, la implementación y los resultados alcanzados al emplearse una celda de sedimentación gravimétrica para la detección de la distribución de tamaño o diámetro medio de un conjunto de micropartículas, a partir de su detección a través de un sistema de tipo óptico, basado en la medición de la extinción o decaimiento de la intensidad de flujo de fotones de un haz de luz que atraviesa una suspensión compuesta por un material particulado y agua. La celda fue construida de manera modular, mientras que su calibración y los ensayos se realizaron utilizando suspensiones compuestas por partículas de tamaño estandarizado de dióxido de silicio amorfo (Geltech S 1500) de un diámetro medio nominal de 1,5 µm en agua. Los resultados alcanzados mostraron que el uso de esta celda de sedimentación es en extremo conveniente, ya que fue posible detectar la distribución de tamaño de micropartículas con precisión y a un relativo bajo costo, lo que permitiría aplicarlo ventajosamente en la industria de procesos en genera

    Impact of thermal stress on abrasive dust from a carbon fiber-reinforced concrete composite.

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    Recently, a novel corrosion-resistant construction material, Carbon Concrete Composite (C3 ), consisting of coated carbon fibers embedded in a concrete matrix, was introduced. However, thermal exposure during domestic fires may impact the release of organic pollutants and fibers during abrasive processing and/or demolition. Consequently, the objective of this study was to explore the emission characteristics of toxic compounds and harmful fibers during the dry-cutting after exposure to 25–600◦C (3 h, air). These parameters mimic the abrasive machining and dismantling after a domestic fire event. Mass spectrometry and chromatography served as analytical methodologies, and no organic pollutants for exposure temperatures ≥ 400◦C were found. In contrast, significant amounts of pyrolysis products from the organic fiber coating were released at lower temperatures. Studying the morphology of the released fibers by electron microscopy revealed a decrease in fiber diameter for temperatures exceeding 450◦C. At ≥550◦C, harmful fibers, according to the World Health Organization (WHO) definition, occurred (28–41 × 104 WHO fibers/m3 at 550–600◦C). This leads to the conclusion that there is a demand for restraining and protection measures, such as the use of wet cutting processes, suction devices, particle filtering masks and protective clothing, to handle thermally stressed C3
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