Fraunhofer Centre for Applied Photonics

Wang Y., Xie W., Chen H., Pei C., Li D.D.

Davidson Z.C., Hugues-Salas E., Bonner G.M., Jones B.E., Prentice J., Kariappa S., Fowler D.S., Oliveira R.D., Zhang P., Andersson Y., Kosmatos E.A., Stavdas A., Lord A.

Burnford J., Morrisset D., Ojo A.O., Hadden R.M., Law A., Peterson B.

Flame spread over a solid surface is a critical metric in assessing the fire hazard of a material. At the core of the flame spread problem is heat transfer to and within the solid fuel. Accurate measurement of surface temperature on the burning solid is necessary to describe the heat transfer mechanisms which drive flame spread. This work employs phosphor thermometry to measure the spatiotemporal surface temperature during downward flame spread over polymethyl methacrylate (PMMA) samples. The phosphor Gd3Ga5O12:Cr,Ce is used to measure the surface temperature in a 23 × 23 mm2 area with an image resolution of 410 µm/pixel. CH* chemiluminescence imaging is performed alongside phosphor thermometry to measure the flame spread rate and evaluate the surface temperature relative to the flame position. This work investigates the limitations and considerations required to adequately measure surface temperatures in a flame spread scenario using phosphor thermometry. The optimal phosphor coating thickness to prevent interference with the flame spread process is first investigated. Phosphor coating thicknesses of 6 µm and 4 µm impeded flame spread rate and altered the flame shape – thus proving too invasive for this application. A coating thickness of 2 µm, which provided a phosphor to PMMA surface ratio of 0.55/0.45, had no measurable effect on the flame spread behavior and provided reliable 2D surface temperature measurements. The phosphor measurements presented in this work exhibit a similar reliability to a thermocouple, but provide spatially resolved surface temperatures and provide measurement access to the surface underneath the flame sheet. The findings report 2D spatiotemporal surface temperature measurements ahead of the flame front, at the flame's leading edge, and in the pyrolyzing region immediately beneath the flame. Detailed surface temperature measurements underneath the flame sheet are novel to the use of phosphor thermometry and have not been previously recorded. This study showcases this diagnostic technique in the context of flame spread, and shows the potential of applying these methods to other solid-fuel related research.

McWilliam A., Al Khafaji M., Svensson S., padua S., Franke-Arnold S.

Mueller matrices provide a complete description of a medium’s response to excitation by polarized light, and their characterization is important across a broad range of applications from ellipsometry in material science to polarimetry in biochemistry, medicine and astronomy. Here we introduce single-shot Mueller matrix polarimetry based on generalized measurements performed with a Poincaré beam. We determine the Mueller matrix of a homogeneous medium with unknown optical activity by detecting its optical response to a Poincaré beam, which across its profile contains all polarization states, and analyze the resulting polarization pattern in terms of four generalized measurements, which are implemented as a path-displaced Sagnac interferometer. We illustrate the working of our Mueller matrix polarimetry on the example of tilted and rotated wave plates and find excellent agreement with predictions as well as alternative Stokes measurements. After initial calibration, the alignment of the device stays stable for up to 8 hours, promising suitability for the dynamic characterization of Mueller matrices that change in time. Unlike traditional rotating waveplate polarimetry, our method allows the acquisition of a sample’s dynamic Mueller matrix. We expect that our feasibility study could be developed into a practical and versatile tool for the real-time analysis of optical activity changes, with applications in biomedical and biochemical research and industrial monitoring.

Wang J., Svensson S.J., Clark T.W., Chen Y., Al Khafaji M.A., Gao H., Westerberg N., Franke-Arnold S.

We investigate the transmission of vector beams, correlated in their polarization and spatial degrees of freedom, through cold atoms in the presence of a transverse magnetic coupling field. The resulting phase-dependent dynamics allow us to imprint the spatially varying polarization of a vector beam onto atomic spin polarizations, thereby establishing a direct link between optical space-polarization correlations and atomic-state interference. We find that the resulting absorption profiles show interference fringes whose modulation strength is given by the squared concurrence of the vector beam, letting us identify optical concurrence from a single absorption image. We expect impact across a diverse range of applications, including spintronics, quantum memories, metrology, and clocks. Published by the American Physical Society 2024

Eling C.J., Bruce N., Gunasekar N., Alves P.U., Edwards P.R., Martin R.W., Laurand N.

Mishra S., Anwar A., Singh R.P.

We demonstrate an experimental method to generate arbitrary non-separable states of light in two degrees of freedom i.e., polarization and orbital angular momentum (OAM). We observe the intensity distribution corresponding to OAM modes of the light beam by projecting the non-separable state into different polarization states. We further verify the presence of non-separability by measuring the degree of polarization and linear entropy. This classical non-separability can be easily transferred to the quantum domain using spontaneous parametric down-conversion for applications in quantum communication and quantum sensing.

Vasile M., Walker L., Campbell A., Marto S., Murray P., Marshall S., Savitski V.

AbstractThis paper presents a data processing pipeline designed to extract information from the hyperspectral signature of unknown space objects. The methodology proposed in this paper determines the material composition of space objects from single pixel images. Two techniques are used for material identification and classification: one based on machine learning and the other based on a least square match with a library of known spectra. From this information, a supervised machine learning algorithm is used to classify the object into one of several categories based on the detection of materials on the object. The behaviour of the material classification methods is investigated under non-ideal circumstances, to determine the effect of weathered materials, and the behaviour when the training library is missing a material that is present in the object being observed. Finally the paper will present some preliminary results on the identification and classification of space objects.

Mekhail S.P., Stellinga D., Phillips D., Selyem A., Turtaev S., Čižmár T., Padgett M.

We measure the modal dispersion occurring in a single multimode fibre and account for this using a digital micromirror device to form a raster scanning spot in the far field of the distal facet of the fibre. We perform this with a q-switched 700 ps pulsed laser at a 532 nm wavelength. The raster scanning allows us to spatially interrogate the reflectivity of a scene while the time of flight of the pulse gives distance information allowing for the generation of a three-dimensional image.

Wang B., Deng Z., Fu Y., Kerman S., Xu W., Li H., Liu H., He Q., Chen C., Cheng J.

AbstractOrganic thin‐film fluorescent sensor is an efficient tool for detecting trace chemical vapor, such as illegal drugs, explosives, nerve agents, and other dangerous substances due to its high sensitivity and quick response. However, most of the current device structures rely on space optics, which makes it challenging to integrate with complementary metal oxide semiconductor (CMOS) technology, and hence difficult for achieving chip‐level implementation. On the other hand, silicon nitride waveguide‐based photonics have recently shown strong potential for developing commercial‐scale fully integrated on‐chip gas sensors. In this work, to the best of the knowledge, the first chemical vapor detector based on fluorescence sensing is reported by the evanescent field of the waveguide on integrated photonic platform. By the simultaneous excitation and collection with the same waveguide, a detection limit of 0.19 and 93.7 ppb for methamphetamine and aniline, respectively, is achieved. Thanks to the good compatibility with CMOS fabrication processes, this on‐chip optical sensor can achieve production scalability as well as ease of integration with wearable electronic devices to meet the demands of portable, rapid detection. The technical route presented in this work provides a promising solution for compact, low‐cost fluorescence‐based gas sensors.

Xiao D., Sapermsap N., Li D., Chen Y.

We present a deep learning (DL) framework, termed few-photon fluorescence lifetime imaging (FPFLI), for fast analysis of fluorescence lifetime imaging (FLIM) data under highly low-light conditions with only a few photons per pixel. FPFLI breaks the conventional pixel-wise lifetime analysis paradigm and fully exploits the spatial correlation and intensity information of fluorescence lifetime images to estimate lifetime images, pushing the photon budget to an unprecedented low level. The DL framework can be trained by synthetic FLIM data and easily adapted to various FLIM systems. FPFLI can effectively and robustly estimate FLIM images within seconds using synthetic and experimental data. The fast analysis of low-light FLIM images made possible by FPFLI promises a broad range of potential applications.

Flores Y.V., Polak A., Jambet J., Stothard D., Haertelt M.

Vovrosh J., Wilkinson K., Hedges S., McGovern K., Hayati F., Carson C., Selyem A., Winch J., Stray B., Earl L., Hamerow M., Wilson G., Seedat A., Roshanmanesh S., Bongs K., et. al.

Borehole gravity sensing can be used in a number of applications to measure features around a well, including rock-type change mapping and determination of reservoir porosity. Quantum technology gravity sensors, based on atom interferometry, have the ability to offer increased survey speeds and reduced need for calibration. While surface sensors have been demonstrated in real world environments, significant improvements in robustness and reductions to radial size, weight, and power consumption are required for such devices to be deployed in boreholes. To realise the first step towards the deployment of cold atom-based sensors down boreholes, we demonstrate a borehole-deployable magneto-optical trap, the core package of many cold atom-based systems. The enclosure containing the magneto-optical trap itself had an outer radius of (60 ± 0.1) mm at its widest point and a length of (890 ± 5) mm. This system was used to generate atom clouds at 1 m intervals in a 14 cm wide, 50 m deep borehole, to simulate how in-borehole gravity surveys are performed. During the survey, the system generated, on average, clouds of (3.0 ± 0.1) × 105 87Rb atoms with the standard deviation in atom number across the survey observed to be as low as 8.9 × 104.

Bruce N., Farrell F., Xie E., Scullion M., haughey A., Gu E., Dawson M.D., Laurand N.

A fluorescence sensor with the capability for spatially multiplexed measurements utilizing smartphone detection is presented. Bioconjugated quantum dots are used as the fluorescent tag and are excited using a blue-emitting microLED (µLED). The 1-dimensional GaN µLED array is butt-coupled to one edge of the glass slide to take advantage of total internal reflection fluorescence (TIRF) principles. The bioassays on the top surface of the glass waveguide are excited and the resultant fluorescence is detected with the smartphone. The red, green, and blue channels of the digital image are utilized to spectrally separate the excitation light from the fluorescence for analysis. Using a biotin-functionalized glass slide as proof of principle, we have shown that streptavidin conjugated quantum dots can be detected down to a concentration of 8 nM.

Vasile M., Walker L., Dunphy R.D., Zabalza J., Murray P., Marshall S., Savitski V.

This paper presents some initial results on the use of hyperspectral imaging technology and machine learning to characterise the surface composition of space objects and reconstruct their attitude motion. The paper provides a preliminary demonstration that hyperspectral and multispectral analysis of the light absorbed, emitted and reflected by space objects can be used to identify, with some degree of accuracy, the materials composing their surface. The paper introduces a high-fidelity simulation model, developed to test this concept, and a validation of the model against experimental tests in a laboratory environment. The paper shows how to unmix the spectra to provide an estimation of the materials composing the surface facing the sensor. A machine learning approach is then proposed to reconstruct the attitude motion from the time series of spectra.