High performance photothermal carbon nanotubes/nanostructured hydrogel for solar electricity production and solar water sterilization. - In: Applied surface science, Bd. 643 (2024), 158680
Solar energy is a promising renewable energy source with the potential to contribute to sustainable development. Efficient photothermal conversion is critical for solar energy acquisition and conversion. Here, carbon nanotubes (CNTs) were gelatinized to obtain the nanostructured CNT/hydrogel, and then highly light-absorbing CNT/n-hydrogels with surface texture were obtained by replicating the micrometer structure from the black silicon (b-Si) surface onto CNT/hydrogels by using a PDMS mold. Through the synergistic effect of both surface texture and nanostructures, it demonstrates high efficiency of solar electricity production and solar sterilization. A small thermoelectric (TE) module with an area of 4 × 4 cm2 is integrated with CNT/n-hydrogel absorber for the investigation of photo-thermoelectric conversion. The output power of the CNT/n-hydrogel TE device is 1.42 W•m−2 under 1 sun. And by connecting four devices in series, it has successfully demonstrated for charging mobile phones under two different solar illuminations. This work provides a cost-effective and easy fabrication method for opening up the hydrogel as a photothermal absorber, which is low-cost, reproducible, high-efficiency solar water sterilization and high photothermal conversion efficiency.
https://doi.org/10.1016/j.apsusc.2023.158680
High-resolution patterning on LTCC by transfer of photolithography-based metallic microstructures. - In: International journal of applied ceramic technology, ISSN 1744-7402, Bd. 21 (2024), 2, S. 1180-1190
The growing applications and constant miniaturization of electronic devices and of low-temperature co-fired ceramics (LTCC) in various fields, such as aviation, telecommunications, automotive, satellite communications, and military, have led to an increase in the demand for LTCC. Such prospects arise due to the continuous scaling down of components and high-density interconnection in electronics packaging. This paper reports a technique for the transfer of high-resolution microstructures from silicon substrates to LTCC. In this method, gold and copper patterns were formed by photolithography, electrodeposition, and residual layer stripping on silicon substrate. Lithography provides the opportunity to create and transfer complex patterns for use in several different applications and electroplating enables the use of pure metal for excellent electrical properties. The developed structures were transferred onto a top layer of LTCC tape using hot embossing. Then, the subsequent layers were stacked, laminated, and sintered. A resolution of 1.5 μm after free sintering and 4.5 μm after pressure-assisted sintering was achieved. This distinctive method can be useful for several applications requiring high-resolution and superior electrical properties.
https://doi.org/10.1111/ijac.14569
A framework for developing and evaluating algorithms for estimating multipath propagation parameters from channel sounder measurements. - In: IEEE transactions on wireless communications, Bd. 23 (2024), 5, S. 4424-4441
A framework is proposed for developing and evaluating algorithms for extracting multipath propagation components (MPCs) from measurements collected by channel sounders at millimeter-wave frequencies. Sounders equipped with an omni-directional transmitter and a receiver with a uniform planar array (UPA) are considered. An accurate mathematical model is developed for the spatial frequency response of the sounder that incorporates the non-ideal cross-polar beampatterns for the UPA elements. Due to the limited Field-of-View (FoV) of each element, the model is extended to accommodate multi-FoV measurements in distinct azimuth directions. A beamspace representation of the spatial frequency response is leveraged to develop three progressively complex algorithms aimed at solving the single-snapshot maximum likelihood estimation problem: greedy matching pursuit (CLEAN), space-alternative generalized expectation-maximization (SAGE), and RiMAX. The first two are based on purely specular MPCs whereas RiMAX also accommodates diffuse MPCs. Two approaches for performance evaluation are proposed, one with knowledge of ground truth parameters, and one based on reconstruction mean-squared error. The three algorithms are compared through a demanding channel model with hundreds of MPCs and through real measurements. The results demonstrate that CLEAN gives quite reasonable estimates which are improved by SAGE and RiMAX. Lessons learned and directions for future research are discussed.
https://doi.org/10.1109/TWC.2023.3318532
Dynamic-controlled principal component analysis for fault detection and automatic recovery. - In: Reliability engineering & system safety, ISSN 1879-0836, Bd. 241 (2024), 109608
To effectively implement the prognostic and health management for industrial processes, a dynamic-controlled principal component analysis (DCPCA) for pattern extraction and deviation diagnosis is proposed under the framework of multivariate statistical modelling, which can accurately detect and automatically rectify the faults. Significantly, the geometric properties of DCPCA are analysed, revealing the spatial structure relationships of different variables and how the data space is partitioned. In addition, the model relationships in DCPCA are explored, including the dynamic characteristics of time-series variables and the algebraic ones of static variables. Based on these results, statistics are derived for monitoring both the dynamic and static relationships of the process, and under the abnormal circumstance, by diagnosing the deviations between the fault pattern and the setpoint, a fault regulator for automatic recovery is designed. The case study of prognostic and health management for an industrial distillation column illustrates the advantages of DCPCA in fully extracting the process dynamics into pattern, as well as fault detection and automatic recovery.
https://doi.org/10.1016/j.ress.2023.109608
Melt flow, heat transfer and solidification in a flexible thin slab continuous casting mold with vertical-combined electromagnetic braking. - In: Journal of iron and steel research, international, ISSN 2210-3988, Bd. 31 (2024), 2, S. 401-415
During continuous casting of steel slabs, the application of electromagnetic braking technology (EMBr) provides an effective tool to influence solidification by controlling the pattern of melt flow in the mold. Thus, the quality of the final product can be improved considerably. A new electromagnetic braking (EMBr) method, named vertical-combined electromagnetic braking (VC-EMBr), is proposed to be applied to a flexible thin slab casting (FTSC) mold. To evaluate the beneficial effects of the VC-EMBr, the melt flow, heat transfer, and solidification processes in the FTSC mold are studied by means of numerical simulations. In detail, a Reynolds-averaged Navier-Stokes turbulence model together with an enthalpy-porosity approach was used. The numerical findings are compared with respective simulations using the traditional Ruler-EMBr. The results demonstrate that the application of the VC-EMBr contributes significantly to preventing relative slab defects. In contrast to the Ruler-EMBr, the additional vertical magnetic poles of the VC-EMBr preferentially suppress the direct impact of jet flow on the narrow face of FSTC mold and considerably diminish the level fluctuation near the meniscus region. For instance, by applying a magnetic flux density of 0.3 T, the maximum amplitude of meniscus deflection reduces by about 80%. Moreover, the braking effect of the VC-EMBr effectively improves the homogeneity of temperature distribution in the upper recirculation region and increases the solidified shell thickness along the casting direction. On this basis, the newly proposed VC-EMBr shows a beneficial effect in preventing relative slab defects for FTSC thin slab continuous casting.
https://doi.org/10.1007/s42243-023-01062-9
Numerical research for the effect of magnetic field on convective transport process of molten salt in Rayleigh-Bénard system. - In: International journal of thermal sciences, ISSN 1778-4166, Bd. 195 (2024), 108605, S. 1-21
The effects of external applied magnetic field on heat and momentum transfer of Rayleigh-Bénard convection in a closed cavity filled with electrically conductive molten salt are investigated by direct numerical simulation. Such arrangements are of strong interest in the context of thermal energy storage systems from renewable resources. To discretize the governing equations, the Chebyshev collocation spectral method is developed. A series of numerical results for 5000 ≤ Ra ≤ 10^6, 5 ≤ Pr ≤ 20 and 0 ≤ Ha ≤ 150 are obtained. First, we conduct two-dimensional numerical simulations to investigate the effect of Pr without and with magnetic field and find that Pr has little influence on heat and momentum transfer. Then, taking Pr as a fixed value of 7 and considering the effects of Ra and Ha, 2D and 3D direct numerical simulations are conducted. From both 2D and 3D numerical results, we conclude that, the heat and momentum transfer are enhanced with Ra at Ha = 0 and the fluid motion is stabilized by magnetic field at Ha 0. More phenomena of heat transfer and fluid flow, together with scaling correlations of Nu ∼ Ra, Nu ∼ Re for Rayleigh-Bénard convection without magnetic field, and, Nu ∼ RaHa and Re ∼ RaHa for Rayleigh-Bénard convection with magnetic field, are revealed under specified ranges of Ra and Ha.
https://doi.org/10.1016/j.ijthermalsci.2023.108605
Master memory function for delay-based reservoir computers with single-variable dynamics. - In: IEEE transactions on neural networks and learning systems, ISSN 2162-2388, Bd. 35 (2024), 6, S. 7712-7725
We show that many delay-based reservoir computers considered in the literature can be characterized by a universal master memory function (MMF). Once computed for two independent parameters, this function provides linear memory capacity for any delay-based single-variable reservoir with small inputs. Moreover, we propose an analytical description of the MMF that enables its efficient and fast computation. Our approach can be applied not only to single-variable delay-based reservoirs governed by known dynamical rules, such as the Mackey-Glass or Stuart-Landau-like systems, but also to reservoirs whose dynamical model is not available.
https://doi.org/10.1109/TNNLS.2022.3220532
Der Studiengang "Biomedizinische Technik". - In: Medizintechnik, ISSN 0344-9416, (2023), 1, S. 31-37
Deep learning enhanced medical microwave imaging. - In: Electromagnetic imaging for a novel generation of medical devices, (2023), S. 179-201
This chapter is devoted to the thriving field of deep learning enhanced medical microwave imaging. Microwave imaging is a technology with applications in different fields involving the inspection of hidden or nested targets. Thanks to its non-ionizing nature and low-cost, it represents an emerging modality for non invasive medical diagnostics, with potential to compensate the limitations of well-established medical imaging modalities. However, microwave imaging faces several challenges that are slowing down its adoption. In particular, the underlying problem at the core of microwave imaging is a non-linear and ill-posed inverse scattering problem. Recently, employing deep learning techniques to address the difficulties in solving inverse scattering problems has received a significant attention. In this regard, this chapter reviews the main aspects concerned with the adoption of deep learning to enhance microwave imaging and then provides two examples to outline its potential in medical imaging applications. The first application is concerned with monitoring of thermal treatments (hyperthermia) whereas the second is dedicated to imaging the brain.
https://doi.org/10.1007/978-3-031-28666-7_6
Microwave ultra-wideband imaging for non-invasive temperature monitoring during hyperthermia treatment. - In: Electromagnetic imaging for a novel generation of medical devices, (2023), S. 293-330
Microwave medical imaging can become a good alternative for common imaging approaches in the very near future since it is safe due to non-ionizing radiation, cost-efficient and to this end promising for clinical applications. This chapter is devoted to microwave imaging for non-invasive temperature monitoring during hyperthermia therapy. To ensure a constant desired temperature level in the cancerous tissue and to prevent damage of healthy cells, accurate temperature control is necessary during thermal treatment. We present a temperature estimation approach based on the ultra-wideband M-sequence radar technology developed at the Technische Universitaet Ilmenau. The methodology is based on the knowledge of temperature dependencies of tissue physical parameters and on ongoing ultra-wideband measurements, followed by imaging and estimation of dielectric properties which are converted to temperature values. The prototype components from both sensing and heating parts of the system are investigated numerically so that suitable configurations of the antenna array can be defined. Furthermore, the system is experimentally validated on a neck phantom filled with corresponding tissue mimicking materials, which well imitate the dielectric properties of the specific tissues. Exemplary results of these developments are presented in this chapter.
https://doi.org/10.1007/978-3-031-28666-7_10