Band energy diagrams of n-GaInP/n-AlInP(100) surfaces and heterointerfaces studied by X-ray photoelectron spectroscopy. - In: Surfaces and Interfaces, ISSN 2468-0230, Bd. 34 (2022), 102384, S. 1-7
Lattice matched n-type AlInP(100) charge selective contacts are commonly grown on n-p GaInP(100) top absorbers in high-efficiency III-V multijunction solar or photoelectrochemical cells. The cell performance can be greatly limited by the electron selectivity and valance band offset at this heterointerface. Understanding of the atomic and electronic properties of the GaInP/AlInP heterointerface is crucial for the reduction of photocurrent losses in III-V multijunction devices. In our paper, we investigated chemical composition and electronic properties of n-GaInP/n-AlInP heterostructures by X-ray photoelectron spectroscopy (XPS). To mimic an in-situ interface experiment with in-situ stepwise deposition of the contact material, 1 nm -50 nm thick n-AlInP(100) epitaxial layers were grown on n-GaInP(100) buffer layer on n-GaAs(100) substrates by metal organic vapor phase epitaxy. We observed (2 × 2)/c(4 × 2) low-energy electron diffraction patterns with characteristic diffuse streaks along the [011¯] direction due to PP dimers on both AlInP(100) and GaInP(100) as-prepared surfaces. Atomic composition analysis confirmed P-rich termination on both surfaces. Angle-resolved XPS measurements revealed a surface core level shift of 0.9 eV in P 2p peaks and the absence of interface core level shifts. We assigned the surface chemical shift in the P 2p spectrum to PP bonds on a surface. We found an upward surface band bending on the (2 × 2)/c(4 × 2) surfaces most probably caused by localized mid-gap electronic states. Pinning of the Fermi level by localized electronic states remained in n-GaInP/n-AlInP heterostructures. A valence band offset of 0.2 eV was derived by XPS and band alignment diagram models for the n-n junctions were suggested.
https://doi.org/10.1016/j.surfin.2022.102384
Human RF electromagnetic exposure to V2X-communication. - In: Advances in radio science, ISSN 1684-9973, Bd. 19 (2022), S. 233-239
In the era of automated and connected driving, more and more cars will be equipped with wireless transmission technologies such as mobile communications 4G (LTE) and 5G, WiFi, Bluetooth, and V2X. For the technical implementation of V2X-communications, different standards like cellular-V2X from the cooperation 3rd Generation Partnership Project and ITS-G5, based on the WiFi standard 802.11p from the Institute of Electrical and Electronics Engineers, are under consideration. The electromagnetic environment of cars and the corresponding exposure of the general public to wireless emission will be significantly influenced by new radio technologies. Under all circumstances, it must be ensured that the exposure of the electromagnetic fields inside a car does not cause any harmful effects on humans. In order to quantitatively assess the resulting exposure, the generated exposure must be correctly recorded and evaluated according to their specific time-frequency spectra. This paper describes a new measurement procedure suitable for the V2X-standard ITS-G5 together with various exposure measurements performed in different cars with WiFi, Bluetooth and ITS-G5. In comparison of all wireless standards studied here, the V2X-service generated the highest electric field strengths inside a car, when a transmitting di-patch antenna was mounted on the windscreen inside the driver's cabin. The maximum fraction of the corresponding ICNIRP reference level amounted to 15.1 %. We conclude that the total exposure of wireless on-board automotive devices will be dominated by ITS-G5, if the transmitting antenna is located inside the passenger cabin. As V2X-communications will increasingly penetrate road traffic, the resulting exposure should be carefully monitored, in order not to exceed the corresponding reference levels for general public.
https://doi.org/10.5194/ars-19-233-2022
On the benefits and limitations of Echo State Networks for turbulent flow prediction. - In: Measurement science and technology, ISSN 1361-6501, Bd. 34 (2022), 1, 014002, S. 1-18
The prediction of turbulent flow by the application of machine learning (ML) algorithms to big data is a concept currently in its infancy which requires further development. It is of special importance if the aim is a prediction that is good in a statistical sense or if the vector fields should be predicted as good as possible. For this purpose, the statistical and deterministic prediction of the unsteady but periodic flow of the von Kármán Vortex Street (KVS) was examined using an Echo State Network (ESN) which is well suited for learning from time series due to its recurrent connections. The experimental data of the velocity field of the KVS were collected by Particle Image Velocimetry (PIV). Then, the data were reduced by Proper Orthogonal Decomposition (POD) and the flow was reconstructed by the first hundred most energetic modes. An ESN with 3000 neurons was optimized with respect to its three main hyperparameters to predict the time coefficients of the POD modes. For the deterministic prediction, the aim was to maximize the correct direction of the vertical velocities. The results indicate that the ESN can mimic the periodicity and the unsteadiness of the flow. It is also able to predict the sequence of the upward and downward directed velocities for longer time spans. For the statistical prediction, the similarity of the probability density functions of the vertical velocity fields between the predicted and actual flow was achieved. The leaking rate of the ESN played a key role in the transition from deterministic to statistical predictions.
https://doi.org/10.1088/1361-6501/ac93a4
Multi-center evaluation of gel-based and dry multipin EEG caps. - In: Sensors, ISSN 1424-8220, Bd. 22 (2022), 20, 8079, S. 1-16
Dry electrodes for electroencephalography (EEG) allow new fields of application, including telemedicine, mobile EEG, emergency EEG, and long-term repetitive measurements for research, neurofeedback, or brain–computer interfaces. Different dry electrode technologies have been proposed and validated in comparison to conventional gel-based electrodes. Most previous studies have been performed at a single center and by single operators. We conducted a multi-center and multi-operator study validating multipin dry electrodes to study the reproducibility and generalizability of their performance in different environments and for different operators. Moreover, we aimed to study the interrelation of operator experience, preparation time, and wearing comfort on the EEG signal quality. EEG acquisitions using dry and gel-based EEG caps were carried out in 6 different countries with 115 volunteers, recording electrode-skin impedances, resting state EEG and evoked activity. The dry cap showed average channel reliability of 81% but higher average impedances than the gel-based cap. However, the dry EEG caps required 62% less preparation time. No statistical differences were observed between the gel-based and dry EEG signal characteristics in all signal metrics. We conclude that the performance of the dry multipin electrodes is highly reproducible, whereas the primary influences on channel reliability and signal quality are operator skill and experience.
https://doi.org/10.3390/s22208079
P3HT:PCBM polymer solar cells from a didactic perspective. - In: Journal of photonics for energy, ISSN 1947-7988, Bd. 12 (2022), 3, S. 035501-1-035501-19
Here, we studied the influence of pre- and post-thermal annealing on the performance of polymer:fullerene bulk heterojunction solar cells using the conventional architecture, comprising a conjugated polymer, namely, poly(3-hexylthiophene-2,5-diyl) (P3HT) and a fullerene derivative [6,6]-phenyl-C60-butyric acid methyl ester (PC60BM) as a photoactive layer. The non-annealed active layer device exhibited a power conversion efficiency of <1 % , which was significantly lower than the pre- and post-annealed devices. To investigate the impact of pre- and post thermal annealing on the natural morphological state of the polymer, regiorandom (P3HT-I) and regioregular (P3HT-II) type P3HT were compared in photoactive layers. In general, P3HT-I is amorphous, whereas P3HT-II is semi-crystalline. Changes in solar cell performance were associated with changes in carrier extraction efficiencies influenced by the annealing conditions. The charge photogeneration processes were investigated using spectroscopic techniques, including electroluminescence, steady-state, and time-resolved photoluminescence spectroscopy. Finally, to explore the morphological changes upon annealing, atomic force microscopy and electroluminescence imaging measurements were performed on films and solar cells, respectively.
https://doi.org/10.1117/1.JPE.12.035501
Material removal predictions in the robot glass polishing process using machine learning. - In: SN applied sciences, ISSN 2523-3971, Bd. 4 (2022), 1, 33, insges. 14 S.
Robot polishing is increasingly being used in the production of high-end glass workpieces such as astronomy mirrors, lithography lenses, laser gyroscopes or high-precision coordinate measuring machines. The quality of optical components such as lenses or mirrors can be described by shape errors and surface roughness. Whilst the trend towards sub nanometre level surfaces finishes and features progresses, matching both form and finish coherently in complex parts remains a major challenge. With increasing optic sizes, the stability of the polishing process becomes more and more important. If not empirically known, the optical surface must be measured after each polishing step. One approach is to mount sensors on the polishing head in order to measure process-relevant quantities. On the basis of these data, machine learning algorithms can be applied for surface value prediction. Due to the modification of the polishing head by the installation of sensors and the resulting process influences, the first machine learning model could only make removal predictions with insufficient accuracy. The aim of this work is to show a polishing head optimised for the sensors, which is coupled with a machine learning model in order to predict the material removal and failure of the polishing head during robot polishing. The artificial neural network is developed in the Python programming language using the Keras deep learning library. It starts with a simple network architecture and common training parameters. The model will then be optimised step-by-step using different methods and optimised in different steps. The data collected by a design of experiments with the sensor-integrated glass polishing head are used to train the machine learning model and to validate the results. The neural network achieves a prediction accuracy of the material removal of 99.22%.
https://doi.org/10.1007/s42452-021-04916-7
Multilayer redox-based HfOx/Al2O3/TiO2 memristive structures for neuromorphic computing. - In: Scientific reports, ISSN 2045-2322, Bd. 12 (2022), 18266, S. 1-15
Redox-based memristive devices have shown great potential for application in neuromorphic computing systems. However, the demands on the device characteristics depend on the implemented computational scheme and unifying the desired properties in one stable device is still challenging. Understanding how and to what extend the device characteristics can be tuned and stabilized is crucial for developing application specific designs. Here, we present memristive devices with a functional trilayer of HfOx/Al2O3/TiO2 tailored by the stoichiometry of HfOx (x = 1.8, 2) and the operating conditions. The device properties are experimentally analyzed, and a physics-based device model is developed to provide a microscopic interpretation and explain the role of the Al2O3 layer for a stable performance. Our results demonstrate that the resistive switching mechanism can be tuned from area type to filament type in the same device, which is well explained by the model: the Al2O3 layer stabilizes the area-type switching mechanism by controlling the formation of oxygen vacancies at the Al2O3/HfOx interface with an estimated formation energy of ≈ 1.65 ± 0.05 eV. Such stabilized area-type devices combine multi-level analog switching, linear resistance change, and long retention times (≈ 107-108 s) without external current compliance and initial electroforming cycles. This combination is a significant improvement compared to previous bilayer devices and makes the devices potentially interesting for future integration into memristive circuits for neuromorphic applications.
https://doi.org/10.1038/s41598-022-22907-5
Einsatz von gepulsten Lasern mit hoher Leistung in der Präzisionskraftmesstechnik - ein Schritt in die Richtung einer künftigen, SI-rückführbaren und praktischen Kraftquantisierung durch Photonenimpulse :
Deploying the high-power pulsed lasers in precision force metrology - towards SI traceable and practical force quantization by photon momentum. - In: Technisches Messen, ISSN 2196-7113, Bd. 89 (2022), 11, S. 757-777
Design and operational performance of table-top measurement apparatus is presented towards direct Planck constant traceable high accuracy and high precision small forces and optical power measurements within the SI unit system. Electromagnetic force compensation weighing balances, highly reflective mirrors and high-energy pulsed laser unit (static average power 20 W) are tailored together with a specially developed opto-electro-mechanical measurement infrastructure for cross-mapping the scale-systems of two different precision small force measurement methods. One of these methods obtains the force measurements by a state-of-the-art classical kinematic system employing the partial use of Kibble balance principle in the range of 10 nN to 4000 nN to be compared with forces generated due to quantum-mechanical effect namely the transfer of the momentum of photons from a macroscopic object. Detailed overview of the adapted measurement methodology, the static and the limits of dynamic measurement, the metrological traceability routes of the measurement parameters, quantities and their measurement uncertainties, parametric estimation of up (down)-scaling perspectives of the measurements are presented with respect to the state-of-the-art measurement principles and standard procedures within the newly redefined International System of Units (SI).
https://doi.org/10.1515/teme-2022-0080
Model signatures for the integration of simulation models into system models. - In: Systems, ISSN 2079-8954, Bd. 10 (2022), 6, 199, S. 1-15
Model-based systems engineering (MBSE) is an auspicious approach to the virtual development of cyber-physical systems. The behavior of the system’s elements is thus represented by specialized simulation models that are integrated into the descriptive SysML-based system model. Although many simulation models have been developed in research for the common system elements for various purposes and fidelities, their integration remains a major challenge: the parameter interfaces of the simulation models must be coupled with each other and with the parameters of the system elements in such a way that they are correctly parameterized. So far, this coupling can only be carried out by model experts in a time-consuming and error-prone manner. Therefore, in this paper, we first propose a concept that structures the system element parameters for targeted use in validation and design cases. Second, we propose a model signature for simulation models that differentiates its parameters by input, internal, output, and model parameters and specifies them with spatial and temporal dimensions as well as admissible ranges, among others. Based on the two contributions, domain models can be validly and automatable coupled and used for the virtual development of system elements in model-based systems engineering.
https://doi.org/10.3390/systems10060199
Electrical properties of the base-substrate junction in freestanding core-shell nanowires. - In: Advanced materials interfaces, ISSN 2196-7350, Bd. 9 (2022), 30, 2200948, S. 1-8
Well-defined hetero-interfaces with controlled properties are crucial for any high-performance, semiconductor-based, (opto-)electronic device. They are particularly important for device structures on the nanoscale with increased interfacial areas. Utilizing a ultrahigh-vacuum based multi-tip scanning tunneling microscope, this work reveals inadvertent conductivity channels between the nanowire (NW) base and the substrate, when measuring individual vertical core-shell III-V-semiconductor NWs. For that, four-terminal probing is applied on freestanding, epitaxially grown coaxial p-GaAs/i-GaInP/n-GaInP NWs without the need of nanoscale lithography or deposition of electrical contacts. This advanced analysis, carried out after composition-selective wet chemical etching, reveals a substantially degraded electrical performance of the freestanding NWs compared to detached ones. In an electron beam induced current mode of the nanosensor, charge separation at the substrate-to-NW base junction is demonstrated. An energy dispersive X-ray spectroscopic linescan shows an unintended compositional change of the epitaxially grown NW toward the planar layers caused by different incorporation mechanisms of Ga and In at the NW base. This approach provides direct insight into the NW-substrate transition area and leads to a model of the conductivity channels at the NW base, which should, in principle, be considered in the fabrication of all NW heterostructures grown bottom-up on heterogeneous substrate materials.
https://doi.org/10.1002/admi.202200948