Influence of rotational speed on the electrical and mechanical properties of the friction stir spot welded aluminium alloy sheets. - In: Welding in the world, ISSN 1878-6669, Bd. 66 (2022), 6, S. 1179-1190
An efficient and productive joining technique to weld aluminium has become a priority challenge for promoting the use of aluminium in the electrical industry. One of the challenges is to obtain welds with superior mechanical properties with the consistent quality of weld surface as well as low electrical resistance. In this paper, the influence of rotational speed during the friction stir spot welding of AA 5754-H111 was studied to analyse the mechanical and electrical properties of the welds. The results from two rotational speeds (1000 rpm and 4500 rpm) are presented and compared to the base material. It was observed that the samples welded at 1000 rpm showed a higher average shear failure load (˜ 1.1 kN) compared to the samples welded at 4500 rpm (˜ 0.94 kN). The microhardness of the samples welded at 1000 rpm was higher than that of the base material, while the microhardness of samples welded at 4500 rpm was lower. It was also found that the friction welded sheets, regardless of the rotational speed used, showed increased electrical resistance compared to the base material, albeit this increase for the samples welded at 1000 rpm was about 42%, compared to samples welded at 4500 rpm where this increase was just 14%.
https://doi.org/10.1007/s40194-022-01267-8
Reversible sodiation of electrochemically deposited binder- and conducting additive-free Si-O-C composite layers. - In: Energy technology, ISSN 2194-4296, Bd. 10 (2022), 5, 2101164, S. 1-9
Binder- and conducting additive-free Si-O-C composite layers are deposited electrochemically under potentiostatic conditions from sulfolane-based organic electrolyte. Quartz crystal microbalance with damping monitoring is used for evaluation of the layer growth and its physical properties. The sodiation-desodiation performance of the material is afterward explored in Na-ion electrolyte. In terms of specific capacity, rate capability, and long-term electrochemical stability, the experiments confirm the advantages of applying the electrochemically formed Si-O-C structure as anode for Na-ion batteries. The material displays high (722 mAh g^-1) initial reversible capacity at j = 70 mA g^-1 and preserves stable long-term capacity of 540 mAh g^-1 for at least 400 galvanostatic cycles, measured at j = 150 mA g^-1. The observed high performance can be attributed to its improved mechanical stability and accelerated Na-ion transport in the porous anode structure. The origin of the material electroactivity is revealed based on X-Ray photoelectron spectroscopic analysis of pristine (as deposited), sodiated, and desodiated Si-O-C layers. The evaluation of the spectroscopic data indicates reversible activity of the material due to the complex contribution of carbon and silicon redox centers.
https://doi.org/10.1002/ente.202101164
SEOSS-Queries - a software engineering dataset for text-to-SQL and question answering tasks. - In: Data in Brief, ISSN 2352-3409, Bd. 42 (2022), 108211, S. 1-11
https://doi.org/10.1016/j.dib.2022.108211
Automated analysis of acetaminophen toxicity on 3D HepaRG cell culture in microbioreactor. - In: Bioengineering, ISSN 2306-5354, Bd. 9 (2022), 5, 196, S. 1-16
Real-time monitoring of bioanalytes in organotypic cell cultivation devices is a major research challenge in establishing stand-alone diagnostic systems. Presently, no general technical facility is available that offers a plug-in system for bioanalytics in diversely available organotypic culture models. Therefore, each analytical device has to be tuned according to the microfluidic and interface environment of the 3D in vitro system. Herein, we report the design and function of a 3D automated culture and analysis device (3D-ACAD) which actively perfuses a custom-made 3D microbioreactor, samples the culture medium and simultaneously performs capillary-based flow ELISA. A microstructured MatriGrid® has been explored as a 3D scaffold for culturing HepaRG cells, with albumin investigated as a bioanalytical marker using flow ELISA. We investigated the effect of acetaminophen (APAP) on the albumin secretion of HepaRG cells over 96 h and compared this with the albumin secretion of 2D monolayer HepaRG cultures. Automated on-line monitoring of albumin secretion in the 3D in vitro mode revealed that the application of hepatotoxic drug-like APAP results in decreased albumin secretion. Furthermore, a higher sensitivity of the HepaRG cell culture in the automated 3D-ACAD system to APAP was observed compared to HepaRG cells cultivated as a monolayer. The results support the use of the 3D-ACAD model as a stand-alone device, working in real time and capable of analyzing the condition of the cell culture by measuring a functional analyte. Information obtained from our system is compared with conventional cell culture and plate ELISA, the results of which are presented herein.
https://doi.org/10.3390/bioengineering9050196
Colored Petri net modelling and evaluation of drone inspection methods for distribution networks. - In: Sensors, ISSN 1424-8220, Bd. 22 (2022), 9, 3418, S. 1-20
https://doi.org/10.3390/s22093418
Comparison of the performance and reliability between improved sampling strategies for polynomial chaos expansion. - In: Mathematical biosciences and engineering, ISSN 1551-0018, Bd. 19 (2022), 8, S. 7425-7480
As uncertainty and sensitivity analysis of complex models grows ever more important, the difficulty of their timely realizations highlights a need for more efficient numerical operations. Non-intrusive Polynomial Chaos methods are highly efficient and accurate methods of mapping input-output relationships to investigate complex models. There is substantial potential to increase the efficacy of the method regarding the selected sampling scheme. We examine state-of-the-art sampling schemes categorized in space-filling-optimal designs such as Latin Hypercube sampling and L1-optimal sampling and compare their empirical performance against standard random sampling. The analysis was performed in the context of L1 minimization using the least-angle regression algorithm to fit the GPCE regression models. Due to the random nature of the sampling schemes, we compared different sampling approaches using statistical stability measures and evaluated the success rates to construct a surrogate model with relative errors of < 0.1 %, < 1 %, and < 10 %, respectively. The sampling schemes are thoroughly investigated by evaluating the y of surrogate models constructed for various distinct test cases, which represent different problem classes covering low, medium and high dimensional problems. Finally, the sampling schemes are tested on an application example to estimate the sensitivity of the self-impedance of a probe that is used to measure the impedance of biological tissues at different frequencies. We observed strong differences in the convergence properties of the methods between the analyzed test functions.
https://doi.org/10.3934/mbe.2022351
Improving the computational accuracy of the dynamic electro-geometrical model using numerical solutions. - In: Scientific reports, ISSN 2045-2322, Bd. 12 (2022), 5742, S. 1-13
The dynamic electro-geometrical model has been applied in various studies to investigate the probability of a lightning strike to parts of a structure. The numerical computation of the dynamic electro-geometrical model (DEGM) follows an iterative step by determining lightning strike points from above to a point on a structure of interest. This computation is often time-consuming and requires extensive computational resources. This study delves into the inner workings of DEGM striking distance computation. It highlights sources of computational numerical errors, such as the effect of the discretisation size. It proposes ways to eliminate such by using a conversion factor while also significantly reducing computation time from more than 14 h to approximately 6 min for a cuboid structure by eliminating ground surface points. The performance of the proposed improved DEGM (IDEGM) was investigated using a floating roof tank and a cuboid structure with a central air termination, and an interception efficiency of 61% was achieved. An alternative case using catenary wires with a total lightning interception efficiency of 99.1% was also implemented. The percentage strike probability for the cases considered shows a close approximation to published results, and this confirms the accuracy of the implemented model. The IDEGM has the benefit of generating results with a significantly reduced computation time of just a few minutes as compared to several hours in previous models.
https://doi.org/10.1038/s41598-022-09674-z
Well-defined nanostructuring with designable anodic aluminum oxide template. - In: Nature Communications, ISSN 2041-1723, Bd. 13 (2022), 2435, S. 1-11
Well-defined nanostructuring over size, shape, spatial configuration, and multi-combination is a feasible concept to reach unique properties of nanostructure arrays, while satisfying such broad and stringent requirements with conventional techniques is challenging. Here, we report designable anodic aluminium oxide templates to address this challenge by achieving well-defined pore features within templates in terms of in-plane and out-of-plane shape, size, spatial configuration, and pore combination. The structural designability of template pores arises from designing of unequal aluminium anodization rates at different anodization voltages, and further relies on a systematic blueprint guiding pore diversification. Starting from the designable templates, we realize a series of nanostructures that inherit equal structural controllability relative to their template counterparts. Proof-of-concept applications based on such nanostructures demonstrate boosted performance. In light of the broad selectivity and high controllability, designable templates will provide a useful platform for well-defined nanostructuring.
https://doi.org/10.1038/s41467-022-30137-6
Direct data-driven forecast of local turbulent heat flux in Rayleigh-Bénard convection. - In: Physics of fluids, ISSN 1089-7666, Bd. 34 (2022), 4, 045106, S. 045106-1-045106-14
A combined convolutional autoencoder-recurrent neural network machine learning model is presented to directly analyze and forecast the dynamics and low-order statistics of the local convective heat flux field in a two-dimensional turbulent Rayleigh-Bénard convection flow at Prandtl number Pr=7 and Rayleigh number Ra=10^7. Two recurrent neural networks are applied for the temporal advancement of turbulent heat transfer data in the reduced latent data space, an echo state network, and a recurrent gated unit. Thereby, our work exploits the modular combination of three different machine learning algorithms to build a fully data-driven and reduced model for the dynamics of the turbulent heat transfer in a complex thermally driven flow. The convolutional autoencoder with 12 hidden layers is able to reduce the dimensionality of the turbulence data to about 0.2% of their original size. Our results indicate a fairly good accuracy in the first- and second-order statistics of the convective heat flux. The algorithm is also able to reproduce the intermittent plume-mixing dynamics at the upper edges of the thermal boundary layers with some deviations. The same holds for the probability density function of the local convective heat flux with differences in the far tails. Furthermore, we demonstrate the noise resilience of the framework. This suggests that the present model might be applicable as a reduced dynamical model that delivers transport fluxes and their variations to coarse grids of larger-scale computational models, such as global circulation models for atmosphere and ocean.
https://doi.org/10.1063/5.0087977
Stationary, continuous, and sequential surface-enhanced raman scattering sensing based on the nanoscale and microscale polymer-metal composite sensor particles through microfluidics: a review. - In: Advanced optical materials, ISSN 2195-1071, Bd. 10 (2022), 7, 2102757, S. 1-25
Surface-enhanced Raman scattering (SERS) is a label-free and accurate analytical technique for the detection of a broad range of various analytes such as, biomolecules, pesticides, petrochemicals, as well as, cellular and other biological systems. A key component for the SERS analysis is the substrate which is required to be equipped with plasmonic features of metal nanostructures that directly interact with light and targeted analytes. Either metal nanoparticles can be deposited on the solid support (glass or silicon) which is suitable for stationary SERS analysis or dispersed in the solution (freely moving nanoparticles). Besides these routinely utilizing SERS substrates, polymer-metal composite particles are promising for sustained SERS analysis where metal nanoparticles act as plasmon-active (hence SERS-active) components and polymer particles act as support to the metal nanoparticles. Composite sensor particles provide 3D interaction possibilities for analytes, suitable for stationary, continuous, and sequential analysis, and they are reusable/regenerated. Therefore, this review is focused on the experimental procedures for the development of multiscale, uniform, and reproducible composite sensor particles together with their application for SERS analysis. The microfluidic reaction technique is highly versatile in the production of uniform and size-tunable composite particles, as well as, for conducting SERS analysis.
https://doi.org/10.1002/adom.202102757