Bewertung alternativer Arbeitsmittel für Wärmepumpen im Gebäudesektor

Forschung im Ingenieurwesen - Das Arbeitsmittel in Wärmepumpen unterliegt einer Vielzahl von Anforderungen, welche für einen effizienten und sicheren Betrieb eingehalten werden...     

Designing optical glasses by machine learning coupled with a genetic algorithm

Engineering new glass compositions have experienced a sturdy tendency to move forward from (educated) trial-and-error to data- and simulation-driven strategies. In this work, we developed a computer program that combines data-driven predictive models (in this case, neural networks) with a genetic algorithm to design glass compositions with desired combinations of properties. First, we induced predictive models for the glass transition temperature (T_g) using a dataset of 45,302 compositions with 39 different chemical elements, and for the refractive index (n_d) using a dataset of 41,225 compositions with 38 different chemical elements. Then, we searched for relevant glass compositions using a genetic algorithm informed by a design trend of glasses having high n_d (1.7 or more) and low T_g (500 °C or less). Two candidate compositions suggested by the combined algorithms were selected and produced in the laboratory. These compositions are significantly different from those in the datasets used to induce the predictive models, showing that the used method is indeed capable of exploration. Both glasses met the constraints of the work, which supports the proposed framework. Therefore, this new tool can be immediately used for accelerating the design of new glasses. These results are a stepping stone in the pathway of machine learning-guided design of novel glasses.     

Effect of Drosophila suzukii on Blueberry VOCs: Chemical Cues for a Pupal Parasitoid,Trichopria anastrephae

Journal of Chemical Ecology - Biocontrol agents such as parasitic wasps use long-range volatiles and host-associated cues from lower trophic levels to find their hosts. However, this chemical...     

The structure,vacancy characteristics,and magnetic properties of GdMn1-xCrxO3 ceramics

To investigate the evolution of the structural and enhanced magnetic properties of GdMnO₃ systems induced by the substitution of Mn with Cr, polycrystalline GdMn_1-xCr_xO₃ samples were synthesized via solid-state reactions. XRD characterization shows that all GdMn_1-xCr_xO₃ compounds with single-phase structures crystallize well and that Cr³⁺ ions entering the lattice sites of GdMnO₃ induce structural distortion. SEM results indicate that the grain size of the synthesized samples (a few microns) decreases as the Cr substitution concentration increases. Positron annihilation lifetime spectroscopy reveals that vacancy-type defects occur in GdMn_1-xCr_xO₃ ceramics and that the vacancy size and concentration clearly change with the Cr content. The temperature and field dependence of the magnetization curves show that Cr substitution significantly influences the magnetic ordering of the gadolinium sublattice, improving the weak ferromagnetic transition temperature and magnetization of GdMn_1-xCr_xO₃. The enhanced magnetization of GdMn_1-xCr_xO₃ is closely related to the vacancy defect concentration.     

On the Growth of Thin-Film AlGaN/GaN Epitaxial Heterostructures on Hybrid Substrates Containing Layers of Silicon Carbide and Porous Silicon

Semiconductors - Abstract—In our work, we carry out a structural-spectroscopic study of AlGaN/GaN epitaxial layers grown by molecular-beam epitaxy with nitrogen-plasma activation on a hybrid...     

Influence of Continuous Wave Interference on the Efficiency of the Non-Threshold Search Procedure for a Noise-Like Signal by Delay Time with Transition to the Frequency Domain

Journal of Communications Technology and Electronics - A statistical study of the effectiveness of the non-threshold search procedure for a noise-like phase-shift keyed signal by the delay time is...     

Effect of heat treatment and zircon addition on the properties of low-cement castables based on recycled alumina grog

In this investigation, low-cement castables were prepared using 70% alumina grog aggregates obtained from crushed alumina brick waste. The aggregates were thermally treated at 1550 °C for 3 h. Four types of low-cement castables were prepared with various types of aggregates (alumina grog with or without thermal treatment) and fillers (with or without zircon addition), and they were evaluated in terms of their physical, thermal, and chemical properties. Microstructural analysis via scanning electron microscopy (SEM) was performed on the castables before and after slag attack. Compared to the other fabricated castables, the thermally treated alumina grog castables with zircon showed better physical properties, such as a higher bulk density, cold crushing strength, and modulus of rupture and a lower apparent porosity and water absorption. In addition, they had a higher positive linear thermal expansion, refractoriness under load, permanent linear change, and hot modulus of rupture. The results of the SEM with energy dispersive X-ray analysis of the prepared castables confirmed that the mullite and anorthite phases were predominant when zircon was not added and the zircon–mullite phase additionally appeared upon the incorporation of zircon. A quantitative elemental analysis via X-ray fluorescence spectroscopy was employed to determine the composition of the castables. X-ray diffraction analysis showed that the alumina grog castables had a high mullite and low anorthite content, and the thermally treated alumina grog had a high anorthite, low mullite, and high zircon content. The improvement in the mechanical and thermo-mechanical properties of the castables with thermally treated alumina grog and added zircon can be attributed to the formation of the zircon–mullite phase with a low mullite phase content.     

Surface Reconstruction Engineering with Synergistic Effect of Mixed-Salt Passivation Treatment toward Efficient and Stable Perovskite Solar Cells

Surface passivation treatment is a widely used strategy to resolve trap-mediated nonradiative recombination toward high-efficiency metal-halide perovskite photovoltaics. However, a lack of passivation with mixture treatment has been investigated, as well as an in-depth understanding of its passivation mechanism. Here, a systematic study on a mixed-salt passivation strategy of formamidinium bromide (FABr) coupled with different F-substituted alkyl lengths of ammonium iodide is demonstrated. It is obtained better device performance with decreasing chain length of the F-substituted alkyl ammonium iodide in the presence of FABr. Moreover, they unraveled a synergistic passivation mechanism of the mixed-salt treatment through surface reconstruction engineering, where FABr dominates the reformation of the perovskite surface via reacting with the excess PbI₂. Meanwhile, ammonium iodide passivates the perovskite grain boundaries both on the surface and top perovskite bulk through penetration. This synergistic passivation engineer results in a high-quality perovskite surface with fewer defects and suppressed ion migration, leading to a champion efficiency of 23.5% with mixed-salt treatment. In addition, the introduction of the moisture resisted F-substituted groups presents a more hydrophobic perovskite surface, thus enabling the decorated devices with excellent long-term stability under a high humid atmosphere as well as operational conditions.     

Optimization methods in inverse problems and applications to science and engineering

Optimization and Engineering -     

A novel strategy based on salp swarm algorithm for extracting the maximum power of proton exchange membrane fuel cell

Cell temperature and water content of the membrane have a significant effect on the performance of fuel cells. The current-power curve of the fuel cell has a maximum power point (MPP) that is needed to be tracked. This study presents a novel strategy based on a salp swarm algorithm (SSA) for extracting the maximum power of proton-exchange membrane fuel cell (PEMFC). At first, a new formula is derived to estimate the optimal voltage of PEMFC corresponding to MPP. Then the error between the estimated voltage at MPP and the actual terminal voltage of the fuel cell is fed to a proportional-integral-derivative controller (PID). The output of the PID controller tunes the duty cycle of a boost converter to maximize the harvested power from the PEMFC. SSA determines the optimal gains of PID. Sensitivity analysis is performed with the operating fuel cell at different cell temperature and water content of the membrane. The obtained results through the proposed strategy are compared with other programmed approaches of incremental resistance method, Fuzzy-Logic, grey antlion optimizer, wolf optimizer, and mine-blast algorithm. The obtained results demonstrated high reliability and efficiency of the proposed strategy in extracting the maximum power of the PEMFC.