621 Angewandte Physik
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Both the ability to suppress disturbances and the simplicity of plant modeling within the active disturbance rejection control (ADRC) approach are enabled by its observer and largely dependent on its sufficiently fast tuning. This, however, may require high observer gain values, which increase the controller’s susceptibility to measurement noise. To reduce the noise sensitivity without requiring any change to the controller structure, this article transfers the results of a continuous-time method called half-gain tuning to the discrete-time domain. Applied only to ADRC’s observer, the closed-loop dynamics will remain almost unaffected. Explicit tuning equations for the discrete-time observer gains are derived. A detailed examination performed analytically, in simulation, and in experiment reveals how much of the theoretical noise reduction promised by the continuous-time method can still be achieved in the discrete-time domain. In summary, an observer tuning method is presented that delivers a substantial reduction in noise sensitivity in practically relevant scenarios and can be applied minimally invasively to existing ADRC control loops.
The machine parts subjected to high wear are conventionally thermally hardened and/or hard coated to minimize surface erosion. The hard coating requires special arrangements and complex machining and finishing processes, which are time and labor-intensive. An alternative solution is work hardening of the surfaces, where hardening and surface finishing can be achieved within a single process step. The manganese steel X120Mn12 is known for its excellent work hardening and wear resistance, making it suitable for applications that require superior surface properties. The addition of 15 wt.% vanadium carbide (VC) enhances its abrasion resistance. Deep rolling (DR) processes have been found to affect microtopography, including surface roughness, increase hardness, and induce compressive residual stresses. Within the scope of this paper, a layer X120Mn12+VC is PTA (Plasma-transferred arc) welded onto a S235 steel substrate. The samples are then deep rolled under various combinations of influencing parameters such as rolling pressure, tool diameter, and feed. The main focus was to achieve maximum surface hardness, an optimal hardness depth profile, and reduced surface roughness. The combination of optimal deep rolling parameters achieved the surface hardness of 640 HV 1 while maintaining a relatively smooth surface. Additionally, an FE model was built, and the optimal DR process was simulated to study the development of residual stresses. The local distribution of equivalent plastic stresses corresponds well with the measured hardness distribution.
This work presents a comprehensive analysis of the variability and reliability of the resistive switching (RS) behavior in Prussian Blue (a mixed-valence iron(III/II) hexacyanoferrate compound) thin films, used as the active layer. These films are fabricated through a simple and scalable electrochemical process, and exhibit robust bipolar resistive switching, making them suitable both for neuromorphic computing applications and hardware cryptography. A detailed statistical evaluation was conducted over 100 consecutive switching cycles using multiple parameter extraction techniques to assess cycle-to-cycle (C2C) variability in key RS parameters, including set/reset voltages and corresponding currents. One and two-dimensional coefficients of variation (1DCV and 2DCV) were calculated to quantify variability and identify application potential. Results demonstrate moderate variability compatible with neuromorphic computing and cryptographic functionalities, including physical unclonable functions and true random number generation. These findings position Prussian Blue-based memristors as promising candidates for low-cost, stable, and multifunctional memory.
Fs-Erbium-ring fiber laser as a simple training tool for enhancing laser engineering education
(2025)
Magnetic field effects (MFEs) in thermally activated delayed fluorescence (TADF) materials have been shown to influence the reverse intersystem crossing (RISC) and to impact on electroluminescence (EL) and conductivity. Here, we present a novel model combining Cole–Cole and Lorentzian functions to describe low and high magnetic field effects originating from hyperfine coupling, the Delta-g mechanism, and triplet processes. We applied this approach to organic light-emitting devices of third generation based on tris(4-carbazoyl-9-ylphenyl)amine (TCTA) and 2,2′,2″-(1,3,5-benzinetriyl)-tris(1-phenyl-1-H-benzimidazole) (TPBi), exhibiting blue emission, to unravel their loss mechanisms. The quality of the regression function was evaluated using k-fold cross-validation. The scoring was compared to various alternative fitting functions, which were previously proposed in literature. Density functional theory calculations, photoluminescence, and electroluminescence studies validated the formation of a TADF exciplex system. Furthermore, we propose successful encapsulation using a semi-permeable polymer, showing promising results for magnetic field sensing applications on arbitrary geometry. This study provides insights into the origin of magnetic field effects in exciplex-TADF materials, with potential applications in optoelectronic devices and sensing technologies.
Several aspects make this book different, and doing things not the usual way is its recurring motif. Therefore, in this chapter, we focus on establishing those unique aspects of the book that constitute its claimed titular “fresh look.” This expression has a double meaning here. On the one hand, it refers to the active disturbance rejection control (ADRC) as this unorthodox approach in the control landscape and on the other to the fresh look at how ADRC can be introduced to those interested in it. We will also answer here some basic important questions like what exactly is in the book, why is it constructed the way it is, to whom the book is for, and what is the best way to use it depending on the reader’s background.
The measurement of hydrogen concentration in fuel cell systems is an important prerequisite for the development of a control strategy to enhance system performance, reduce purge losses and minimize fuel cell aging effects. In this perspective paper, the working principles of hydrogen sensors are analyzed and their requirements for hydrogen control in fuel cell systems are critically discussed. The wide measurement range, absence of oxygen, high humidity and limited space turn out to be most limiting. A perspective on the development of hydrogen sensors based on palladium as a gas-sensitive metal and based on the organic magnetic field effect in organic light-emitting devices is presented. The design of a test chamber, where the sensor response can easily be analyzed under fuel cell-like conditions is proposed. This allows the generation of practical knowledge for further sensor development. The presented sensors could be integrated into the end plate to measure the hydrogen concentration at the anode in- and outlet. Further miniaturization is necessary to integrate them into the flow field of the fuel cell to avoid fuel starvation in each single cell. Compressed sensing methods are used for more efficient data analysis. By using a dynamical sensor model, control algorithms are applied with high frequency to control the hydrogen concentration, the purge process, and the recirculation pump.
Several studies indicate that epoxy resin exhibits a very wide range of mechanical behavior, in particular its strength, as a function of stress state. Especially when epoxy resin is used as matrix material for fiber reinforced composites (FRC), this becomes relevant due to complex stress conditions in the matrix. However, the knowledge about the behavior of epoxy resin under uni, bi, and triaxial stress conditions is lacking. Therefore, the mechanical properties of a typical epoxy resin for the production of FRC were investigated given such load conditions. The determined strengths were compared with the predictions of the extended paraboloid criterion. Uniaxial tension and compression tests, torsion tests with overlaid tension and compression, and triaxial tension tests were performed. An elastoplastic material model and a nonlocal damage model were formulated to demonstrate the application of the extended paraboloid strength criterion. In particular, large plastic strains under shear stress conditions, as well as a perfectly brittle material behavior with significantly reduced strength under triaxial tension, could be shown.
Significance of EEG-electrode combinations while calculating filters with common spatial patterns
(2024)
Objective: Common spatial pattern (CSP) is a common filter technique used for pre-processing of electroencephalography (EEG) signals for imaginary movement classification tasks. It is crucial to reduce the amount of features especially in cases where few data is available. Therefore, different approaches to reduce the amount of electrodes used for CSP calculation are tried in this research.
Methods: Freely available EEG datasets are used for the evaluation. To evaluate the approaches a simple classification pipeline consisting mainly of the CSP calculation and linear discriminant analysis for classification is used. A baseline over all electrodes is calculated and compared against the results of the approaches.
Results: The most promising approach is to use the ability of CSP to provide information about the origin of the created filter. An algorithm that extracts the important electrodes from the CSP utilizing these information is proposed.
The results show that using subject specific electrode positions has a positive impact on accuracy for the classification task. Further, it is shown that good performing electrode combinations in one session are not necessarily good performing electrodes in another session of the same subject. In addition to the combinations calculated using the developed algorithm, 26 additional electrode combinations are proposed. These can be taken into account when selecting well-performing electrode combinations. In this research we could achieve an accuracy improvement of over 10%.
Conclusions: Carefully selecting the correct electrode combination can improve accuracy for classifying an imaginary movement task.
In this work, iron hexacyanoferrate (FeHCF—Prussian blue) particles have been grown onto a reduced graphene oxide substrate through a pulsed electrodeposition process. Thus, the prepared FeHCF electrode exhibits a specific volumetric capacitance of 88 F cm−3 (specific areal capacitance of 26.6 mF cm−2) and high cycling stability with a capacitance retention of 93.7% over 10,000 galvanostatic charge–discharge cycles in a 1 M KCl electrolyte. Furthermore, two identical FeHCF electrodes were paired up in order to construct a symmetrical supercapacitor, which delivers a wide potential window of 2 V in a 1 M KCl electrolyte and demonstrates a large energy density of 27.5 mWh cm−3 at a high power density of 330 W cm−3.
In this work, iron hexacyanoferrate (FeHCF) particles have been grown onto graphene substrate through pulsed electrodeposition process. Thus, prepared FeHCF electrode exhibits volumetric capacitance of 88 F cm− 3 (a real capacitance of 26.6 mF cm− 2) and high cycling stability with capacitance retention of 93.7% under deep repeating of 10000 galvanostatic charge-discharge cycles in 1M KCl electrolyte. Furthermore, two identical FeHCF electrodes were paired up in order to construct a symmetrical supercapacitor, which delivers a wide potential window of 2 V in 1M KCl electrolyte, and demonstrates large energy density with an offer of high power density.
