De missie van het lectoraat Fotonica is om een bijdrage te leveren aan een gezonde wereld en een duurzame economie door het toepasbaar maken van fotonicatechnologie in de praktijk. Ook draagt het lectoraat bij aan het opleiden van professionals op het gebied van fotonica, wat een voorwaarde is om de ambities van deze groeisector waar te kunnen maken. Het fotonica-onderzoek richt zich op de toepassingsgebieden Hightech Industrie, Agri & Food, Energie & Klimaat, Gezondheid en Mobiliteit. Digitale technologie speelt in de ontwikkeling van deze gebieden een grote rol, waarbij fotonica op grote schaal wordt ingezet voor het verkrijgen van digitale data. Sleutelwoorden voor het onderzoek zijn spectroscopie, metrologie en afbeelding. Het toepassen van optische sensoren, zoals spectrometers of glasvezel-gebaseerde sensoren, speelt hierbij een centrale rol. De lijfspreuk van de natuurkundige Heike Kamerlingh Onnes ‘door meten tot weten’, aangevuld met ‘door weten tot handelen’, is dan ook een leidraad voor het lectoraat.
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Poster presentatiion, project Printing Makes Sense at Saxion Research Conference 2018, Deventer. Photonics is declared one of the key enabling technologies by the European Commission. Photonics finds its application in many fields ranging from health & well-being to smart industries. Automation in photonics manufacturing and packaging is key to reduce assembly costs. At the NanoPhysics Interface group, we investigate how to quickly couple light from one fiber to another fiber (or photonic devices). After developing a theoretical model and performing measurements, we find that the alignment is most critical in the lateral translations (x and y-direction) and that pre-alignment of the photonic components can be realized by a smart design of the chip holder
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Micro Ring Resonators (MRRs) have become the workhorse in photonics, both for data/telecomas well as bio-chemical sensing applications. In this contribution the use of MRRs as sensors for food-safety applications will be discussed.
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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.
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From the article: "The term Internet of Things (IoT) is used for situations where one or more devices are connected to a network or possibly the Internet. Most studies focus on the possibilities that arise when a device is capable to share its data with other devices or humans. In this study, the focus is on the device itself and what kind of possibilities an Internet connection gives to the device and its owner or user. Also the data the device needs to participate in a smart way in the IoT are part of this study. Agent technology is the enabling technology for the ideas introduced here. A proof of concept is given, where some concepts proposed in the paper are put into practice."
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Purpose/Objective: Most dose-escalation trials in glioblastoma patients integrate the escalated dose throughout the standard course by targeting a specific subvolume. We hypothesize that anatomical changes during irradiation may affect the dose coverage of this subvolume for both proton- and photon-based radiotherapy. Material and Methods: For 24 glioblastoma patients a photon- and proton-based dose escalation treatment plan (of 75 Gy/30 fr) was simulated on the dedicated radiotherapy planning MRI obtained before treatment. The escalated dose was planned to cover the resection cavity and/or contrast enhancing lesion on the T1w post-gadolinium MRI sequence. To analyze the effect of anatomical changes during treatment, we evaluated on an additional MRI that was obtained during treatment the changes of the dose distribution on this specific high dose region. Results: The median time between the planning MRI and additional MRI was 26 days (range 16–37 days). The median time between the planning MRI and start of radiotherapy was relatively short (7 days, range 3–11 days). In 3 patients (12.5%) changes were observed which resulted in a substantial deterioration of both the photon and proton treatment plans. All these patients underwent a subtotal resection, and a decrease in dose coverage of more than 5% and 10% was observed for the photon- and proton-based treatment plans, respectively. Conclusion: Our study showed that only for a limited number of patients anatomical changes during photon or proton based radiotherapy resulted in a potentially clinically relevant underdosage in the subvolume. Therefore, volume changes during treatment are unlikely to be responsible for the negative outcome of dose-escalation studies.
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How to find the right balance
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Spectral imaging has many applications, from methane detection using satellites to disease detection on crops. However, spectral cameras remain a costly solution ranging from 10 thousand to 100 thousand euros for the hardware alone. Here, we present a low-cost multispectral camera (LC-MSC) with 64 LEDs in eight different colors and a monochrome camera with a hardware cost of 340 euros. Our prototype reproduces spectra accurately when compared to a reference spectrometer to within the spectral width of the LEDs used and the ±1σ variation over the surface of ceramic reference tiles. The mean absolute difference in reflectance is an overestimate of 0.03 for the LC-MSC as compared to a spectrometer, due to the spectral shape of the tiles. In environmental light levels of 0.5 W m−2 (bright artificial indoor lighting) our approach shows an increase in noise, but still faithfully reproduces discrete reflectance spectra over 400 nm–1000 nm. Our approach is limited in its application by LED bandwidth and availability of specific LED wavelengths. However, unlike with conventional spectral cameras, the pixel pitch of the camera itself is not limited, providing higher image resolution than typical high-end multi- and hyperspectral cameras. For sample conditions where LED illumination bands provide suitable spectral information, our LC-MSC is an interesting low-cost alternative approach to spectral imaging.
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Photonic biosensors for medical diagnostics have been in development for some time. They have proven to show equal or better performance as compared to other techniques in terms of sensitivity, accuracy, and reliability. In order for companies to successfully introduce these sensor products on the market, they must also perform equal or better in price per test and usability. The price per test is to a large extent determined by the costs of the (disposable) cartridge containing the sensor chip and bioactive layer. If the active components can be left out of the cartridge a significant cost reduction can be obtained. However, this adds the challenge of coupling light from the source to the sensor chip inside the cartridge and back onto detectors. This coupling requires a positioning accuracy in the (sub-) micrometer regime. Here, we present a demonstrator system, which implements an passive alignment step followed by an active alignment procedure. The initial alignment is realized with high accuracy when placing a cartridge in an acceptor slot. This results in finding a “first light” state, which allows the active alignment to take over. Active alignment is then realized by moving the fiber by means of a set of actuators to the position with optimal coupling efficiency. A demonstrator was designed and manufactured to test the influence of several key parameters, such as the influence of production accuracy of the cartridges on the initial alignment. The resulting system has shown to comply with the requirements of ease of alignment along with full automation.
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We report on the calibration and testing of a fiber Bragg grating (FBG)-based 2D-shape sensing strip for real-time monitoring of the position and orientation of the human spine during gait. The strip is evaluated for its use as an input for control of an exoskeleton for patients with spinal cord injury. By measuring the torsion and bending of the back, walking movements can be reconstructed. The 3D-printed strip has nine embedded fiber Bragg gratings that are located at specific places with respect to the vertebral column. Three FBGs are placed opposite to the thoracic vertebrae T6–T9, these FBGs are sensitive for measuring the bending of the spine during the gait cycle. Torsion is measured at two locations: at thoracic vertebra, T3 and at lumbar vertebra, L3. At these locations, the width of the strip is reduced to have a larger sensitivity for torsion. The strain at each FBG is measured using an interrogator. This leads to the radius of curvature and torsion as a function of time. The Frenet-Serret formulae are used to calculate the shape of the strip during the gait cycle. We have calibrated this FBG strip for curvature by bending it at known radius of different curvatures. We found a linear dependence between the strain and curvature. For torsion calibration we have rotated the strip with a stepper motor at different angles and monitored the strain. We, again, found a linear dependence with a small hysteresis. We mounted the strip on a healthy test subject and monitored their gait cycle. The FBG strip shows similar results when compared to a motion capture system based on multiple cameras. Although the fixation of the strip to a garment or on the back directly strongly influences the measured response, it does show a periodic and reproducible signal during the gait cycle.
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