Significant advancements in nanoscale material efficiency optimization have made it feasible to substantially adjust the thermoelectric transport characteristics of materials. Motivated by the prediction and enhanced understanding of the behavior of two-dimensional (2D) bilayers (BL) of zirconium diselenide (ZrSe2), hafnium diselenide (HfSe2), molybdenum diselenide (MoSe2), and tungsten diselenide (WSe2), we investigated the thermoelectric transport properties using information generated from experimental measurements to provide inputs to work with the functions of these materials and to determine the critical factor in the trade-off between thermoelectric materials. Based on the Boltzmann transport equation (BTE) and Barden-Shockley deformation potential (DP) theory, we carried out a series of investigative calculations related to the thermoelectric properties and characterization of these materials. The calculated dimensionless figure of merit (ZT) values of 2DBL-MSe2 (M = Zr, Hf, Mo, W) at room temperature were 3.007, 3.611, 1.287, and 1.353, respectively, with convenient electronic densities. In addition, the power factor is not critical in the trade-off between thermoelectric materials but it can indicate a good thermoelectric performance. Thus, the overall thermal conductivity and power factor must be considered to determine the preference of thermoelectric materials.
In this study, the effect of ceramic coating on the performance and gases emission on diesel engine was investigated. A four-stroke, direct injected, single cylinder, diesel engine was tested at constant speed and at different load conditions without coating. Then, the inlet and exhaust valves faces were coated by about 500µm with ceramic materials. Ceramic layers were made of YttriaStabilized Zirconia (YSZ), and NiCrAl as a bond coat. The coating technique adapted in this work is the flame spray method. The engine with valves ceramiccoated research was tested for the same operation conditions of the engine (without coating). The results indicate a reduction in both fuel consumption by about 7.6% and particulate emissions by about (13
... Show MoreAn experimental program was conducted to determine the residual of composite Steel Beams-Reinforced Concrete (SB-RC) deck floors fabricated from a rolled steel beam topped with a reinforced concrete slab, exposed to high temperatures (fire flame) of 300, 500, and 700ºC for 1 hour, and then allowed to cool down by leaving them in the lab condition to return to the ambient temperature. The burning results showed that, by exposing them to a fire flame of up to 300ºC, no serious permanent deflection occurred. It was also noticed that the specimen recovered 93% of 19.2 mm of the deflection caused by burning. The recovered deflection of burned composite SB-RC deck floor at 500ºC was 40% of 77.9 mm of the deflection caused by burning with a res
... Show MoreThe downhole flow profiles of the wells with single production tubes and mixed flow from more than one layer can be complicated, making it challenging to obtain the average pressure of each layer independently. Production log data can be used to monitor the impacts of pressure depletion over time and to determine average pressure with the use of Selective Inflow Performance (SIP). The SIP technique provides a method of determining the steady state of inflow relationship for each individual layer. The well flows at different stabilized surface rates, and for each rate, a production log is run throughout the producing interval to record both downhole flow rates and flowing pressure. PVT data can be used to convert measured in-situ rates
... Show MoreMetasurface polarizers are essential optical components in modern integrated optics and play a vital role in many optical applications including Quantum Key Distribution systems in quantum cryptography. However, inverse design of metasurface polarizers with high efficiency depends on the proper prediction of structural dimensions based on required optical response. Deep learning neural networks can efficiently help in the inverse design process, minimizing both time and simulation resources requirements, while better results can be achieved compared to traditional optimization methods. Hereby, utilizing the COMSOL Multiphysics Surrogate model and deep neural networks to design a metasurface grating structure with high extinction rat
... Show MoreWireless Body Area Sensor Networks (WBASNs) have garnered significant attention due to the implementation of self-automaton and modern technologies. Within the healthcare WBASN, certain sensed data hold greater significance than others in light of their critical aspect. Such vital data must be given within a specified time frame. Data loss and delay could not be tolerated in such types of systems. Intelligent algorithms are distinguished by their superior ability to interact with various data systems. Machine learning methods can analyze the gathered data and uncover previously unknown patterns and information. These approaches can also diagnose and notify critical conditions in patients under monitoring. This study implements two s
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