Particle detection and size recognition based on defocused particle images: a comparison of a deterministic algorithm and a deep neural network. - In: Experiments in fluids, ISSN 1432-1114, Bd. 64 (2023), 2, 21, S. 1-16
The systematic manipulation of components of multimodal particle solutions is a key for the design of modern industrial products and pharmaceuticals with highly customized properties. In order to optimize innovative particle separation devices on microfluidic scales, a particle size recognition with simultaneous volumetric position determination is essential. In the present study, the astigmatism particle tracking velocimetry is extended by a deterministic algorithm and a deep neural network (DNN) to include size classification of particles of multimodal size distribution. Without any adaptation of the existing measurement setup, a reliable classification of bimodal particle solutions in the size range of 1.14 μm–5.03 μm is demonstrated with a precision of up to 99.9 %. Concurrently, the high detection rate of the particles, suspended in a laminar fluid flow, is quantified by a recall of 99.0 %. By extracting particle images from the experimentally acquired images and placing them on a synthetic background, semi-synthetic images with consistent ground truth are generated. These contain labeled overlapping particle images that are correctly detected and classified by the DNN. The study is complemented by employing the presented algorithms for simultaneous size recognition of up to four particle species with a particle diameter in between 1.14 μm and 5.03 μm. With the very high precision of up to 99.3 % at a recall of 94.8 %, the applicability to classify multimodal particle mixtures even in dense solutions is confirmed. The present contribution thus paves the way for quantitative evaluation of microfluidic separation and mixing processes.
https://doi.org/10.1007/s00348-023-03574-2
Effect of poly-crystallinity on the magnetoelectric behavior of TiN/AlN/Ni MEMS cantilevers investigated by finite element methods. - In: Physica status solidi, ISSN 1862-6319, Bd. 220 (2023), 16, 2200839, S. 1-6
Herein, magnetoelectric microelectromechanical system (MEMS) cantilevers are investigated on basis of a TiN/AlN/Ni laminate derived from experimental sensors using finite-element simulations. With the anisotropic ΔE effect as an implication of the magnetocrystalline anisotropy, the lateral sensitivity of the sensor is studied for different nickel layer thicknesses and boundary conditions. It is found that above 60% of the cantilever length, the nickel is effectively not contributing to the sensor sensitivity anymore which is supported by the investigation of sensors with partial nickel coverage. The boundary condition of the magnetostrictive layer is found to affect the sensitivity of thick layers while it is negligible for thinning layers. Further investigations on basis of polycrystalline untextured nickel with slightly preferred orientations reveal a stronger effect on thin layers than on thicker ones. It is found to arise from relatively large crystals in the high-sensitivity region near the clamping of the sensor. For thicker polycrystalline layers, the ΔE effect reproduces a characteristic based mainly on the (110) and (111) orientations while the (100) orientation appears to be underrepresented.
https://doi.org/10.1002/pssa.202200839
High sensitivity and selectivity microwave biosensor using biofunctionalized differential resonant array implemented in LTCC for Escherichia coli detection. - In: Measurement, Bd. 208 (2023), 112473, insges. 8 S.
A novel method for label-free detection of Escherichia coli relying on microwave sensing is proposed. A transmission-type differential resonator array biosensor covered with polyclonal anti-Escherichia coli antibodies is introduced providing a robust response with high sensitivity for detecting bacteria presence due to resonant operation combined. The high selectivity is given by the presence of specific bacteria-binding antibodies. Low-Temperature Co-Fired Ceramics technology is proposed to be used for implementation to take advantage of its quasi-three-dimensional fabrication capability. The proposed sensing structure operates in a frequency range of 4 - 6 GHz with five distinct resonances increasing the probability of bacteria detection presence. The developed sensor was experimentally validated by measurements of various concentrations of Escherichia coli along with measurement of a non-specific high concentration of Lactobacillus rhamnosus LOCK 0919. The obtained results prove the performance and suitability of the proposed biosensor for biomedical applications.
https://doi.org/10.1016/j.measurement.2023.112473
Strahlungsfehler bei Lufttemperaturmessungen: Minimierung des Fehlers durch ein neues Referenzsystem und Vergleich mit konventionellen Messsystemen, Tages- und Jahresgang ihres Fehlers in Abhängigkeit von Strahlung und Windgeschwindigkeit :
Radiation error of air temperature measurements: minimization of the error by a new reference system and comparison with conventional measurement systems, diurnal and annual variation of their errors as a function of radiation and wind speed. - In: Technisches Messen, ISSN 2196-7113, Bd. 90 (2023), 1, S. 65-78
The measurement of air temperature is associated with inaccuracies resulting from radiation errors. Liquid thermometers and automatic sensors are therefore housed in screens. Mechanical ventilation also helps to increase the accuracy of readings. Nonetheless, temperature measurements are not completely accurate. This spurred the development of a measuring system that features improved radiation protection and a modified mechanical ventilation system through a new type of screen. Parallel measurements with this new measurement system and two conventional screens of multiple plastic cones were taken at a location in north-east Germany with a temperate climate. Of the two traditional screens, one was ventilated and the other not. Based on previous findings concerning the seasonality of radiation errors, our analysis of their dependency on global radiation and wind speed was focused on the months of May to August, when global radiation is at its strongest. It was found that the not insignificant differences in Δ T\Delta T display a characteristic diurnal variation. With the new measurement system, in comparison with the two conventional measurung systems, the average air temperature of the four surveyed months during daylight hours was 0.43 K and 0.58 K lower. The differences in Δ T\Delta T are greatest not in the middle of the day but when the sun is low in the sky, as radiation is then reflected into the screen. The findings contribute to the understanding of the temporal variability of radiation errors in modern weather stations in dependence on global radiation and wind speed. The technical innovations presented here allow radiation errors to be largely avoided.
https://doi.org/10.1515/teme-2022-0051
Atomic scale network structure of a barium aluminosilicate glass doped with different concentrations of rare-earth ions explored by molecular dynamics simulations. - In: Computational materials science, Bd. 218 (2023), 111965
Molecular dynamics (MD) simulation is employed for exploring the coordination of atoms in peralkaline BaO-Al2O3-SiO2 glasses of variable Gd3+ doping concentrations between 1 and 3.8 mol% Gd2O3. For this the MD simulation procedure of inherent structure sampling was used which provides statistically robust information on the local atomic surrounding of the doped rare earth ions. Distributions of Si/Al/Ba/Gd cations in the first, second and third coordination spheres are investigated. Special focus is laid on the effect of Gd3+ doping concentration on the local surrounding of the Gd3+ ions, i. e. rare earth clustering, and general glass structure. The simulations show that SiOAl bonds are preferred in comparison to SiOSi and AlOAl connections with respect to the random model predictions. Deviations from a statistical Si/Al distribution around the BaOp and GdOq polyhedra are observed. The network modifier ions are preferably surrounded by other network modifier ions, rather than by network formers. It is shown that the incorporation of Gd does not affect radial distribution functions, cumulative radial distribution function curves and the coordination sphere of Gd for Gd2O3 doping concentrations of up to 3.8 mol%, i.e. no rare earth clustering is observed. However, increasing Gd2O3 concentrations decrease the number of bridging oxygen and increase the number of non-bridging oxygen (NBO) species in the glass structure. Charge compensation of the additional non-bridging oxygen species is achieved by increasing NBO coordination numbers with Ba2+.
https://doi.org/10.1016/j.commatsci.2022.111965
Data-driven nonlinear system identification of blood glucose behaviour in Type I diabetics. - In: Control engineering practice, ISSN 1873-6939, Bd. 132 (2023), 105405, S. 1-12
Data-driven nonlinear system identification with sparse regression is a promising method to represent nonlinear dynamics in the form of a rigorous model description. Therefore, nonlinear functional structure identification and parameter estimation are performed simultaneously. Classical identification methods require functional structures that are manually derived using process knowledge either from first principles or practical experience. However, the effort required to provide these structures is time-consuming, labour-intensive, and in connection with operational trials in production plants, also associated with high costs. In addition, the latest sparse regression solution for nonlinear system identification does not offer an analytical solution due to the properties of the L1 norm. For this reason, sparse regression with smoothed L1 regularisation is proposed for nonlinear system identification. For this purpose, a nonlinear library function is first constructed based on the extended dynamic mode decomposition theory (eDMD), which contains all possible nonlinear bijective function candidates. For the process description, the most suitable functions with the related weighting parameters are selected using the regularisation properties. The performance of the method is demonstrated using the blood glucose behaviour from Type I Diabetes. The validation of the method is performed for a simulation study with and without noise influence and applied to experimental data of two patients in a Python simulation. It can be shown that the identification is successful for both studies with a performance limit for a signal-to-noise ratio (SNR) of 0.45 (3.46 dB).
https://doi.org/10.1016/j.conengprac.2022.105405
Broadened photocatalytic capability to near-infrared for CdS hybrids and positioning hydrogen evolution sites. - In: Applied catalysis, ISSN 1873-3883, Bd. 325 (2023), 122327
Wide-spectrum light harvesting is critical in determining practical photocatalysis water splitting. Hybridization presents a viable strategy to broaden photocatalytic capability, yet the direct conversion of near-infrared (NIR) light remains a matter of great concern. Herein, a state-of-art ternary Au nanorodsMoS2-CdS (AMC) hybrid is designed to address this challenge. AMC achieves a leap-forward apparent quantum yield (AQY) of 1.06% at 700 nm and an AQY of 35.7% at 450 nm, extending the hydrogen evolution reaction (HER) capability of CdS hybrids to the NIR region firstly. It is revealed that the energetic hot electrons supplied by Au nanorods (NRs) are responsible for this extension. Indispensable, MoS2 performs a platform to collect the hot electrons from Au NRs and the photoinduced electrons from CdS. The HER active sites are positioned as MoS2-CdS interfaces both from experimental and theoretical viewpoints. This work opens up a new horizon for the forward of the wide-spectrum photocatalysis design.
https://doi.org/10.1016/j.apcatb.2022.122327
Hybrid thermoplastic-metal joining based on Al/Ni multilayer foils - analysis of the joining zone. - In: Materials and design, ISSN 1873-4197, Bd. 226 (2023), 111561, insges. 16 S.
Multi material pairings like metal-plastic hybrid compounds are becoming increasingly important across all industrial sectors. However, the substitution of metals by plastics leads to a multitude of challenges based on the combination of dissimilar materials. The variations in the chemical and physical properties of the used materials require innovative joining processes. The application of reactive multilayers represents an advanced joining method for flexible and low-distortion joining of dissimilar joining partners by means of a short-term and localized application of thermal energy. In the context of this publication, the joining process between semi-crystalline polyamide 6 and austenitic stainless steel X5CrNi18-10(EN 1.4301 / AlSI304) based on reactive Al/Ni multilayers is investigated. In addition to evaluation of resulting joint strength, the focus of the work is in particular the characterization of the resulting failure behavior at the fracture interface under tensile load and the deriving binding mechanisms in the joint. From the results obtained, it is estimated that a direct bond can be generated between plastic and metal despite the presence of a residual reacted foil in the joining area. The structures present in the metal surface have a particularly positive influence on crack initiation and the resulting increased bond strength.
https://doi.org/10.1016/j.matdes.2022.111561
Reactive magnetron sputtering of large-scale 3D aluminum-based plasmonic nanostructure for both light-induced thermal imaging and photo-thermoelectric conversion. - In: Advanced optical materials, ISSN 2195-1071, Bd. 11 (2023), 6, 2202664, S. 1-7
Plasmonic nanostructures have attracted tremendous interest due to their special capability to trap light, which is of great significance for many applications such as solar steam generation and desalination, electric power generation, photodetection, sensing, catalysis, cancer therapy, and photoacoustic imaging. However, the noble metal-based (Au, Ag, Pd) plasmonic nanostructures with expensive costs and limitations to large-scale fabrication restrict their practical applications. Here, a novel and noble-metal-free Al/AlN plasmonic nanostructure fabricated by a reactive magnetron sputtering at the elevated temperature of 200 ˚C is presented. The unique 3D Al/AlN plasmonic nanostructures show a highly efficient (96.8%) and broadband (full solar spectrum) absorption and a strong photothermal conversion effect on its surface, demonstrating the potential in applications in light-induced thermal imaging and photo-thermoelectric power generation. This simple fabrication method and the developed Al/AlN plasmonic nanostructure combine excellent light trapping performance, abundant and low-cost Al and N elements, good heat localization effect, and scalable fabrication method, suggesting a promising alternative to noble-metal plasmonic nanostructures for photonic applications.
https://doi.org/10.1002/adom.202202664
A user-guide for polymer purification using dialysis. - In: Polymer chemistry, ISSN 1759-9962, Bd. 14 (2023), 1, S. 92-101
Dialysis diffusion kinetics are investigated via in situ NMR spectroscopy for numerous different raw polymeric solutions to result in a general guideline for polymer purification using dialysis. In several approaches, a polymer was on purpose contaminated with its respective monomer, regenerated conducting conventional dialysis and monitored online utilizing in situ NMR spectroscopy. Consequently, polymer type and molar mass, monomer type, molar mass cut-off of the dialysis tubing and type of solvent were varied resulting in 29 different purification approaches and over 40 000 NMR-spectra. As a result, several major parameters were identified affecting the purification process significantly such as the chosen solvent, viscosity and alpha value. On the contrary, parameters such as dialysis tubing molar mass cut-off and molar mass of the polymer did not affect the purification in a significant manner. Furthermore, physical properties such as density, viscosity, alpha value, and dipole moment of the ingredients were combined in a principal component analysis in order to identify the most important parameters.
https://doi.org/10.1039/D2PY00972B