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Bilayer MSe<sub>2</sub> (M = Zr, Hf, Mo, W) performance as a hopeful thermoelectric materials
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Abstract<p>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 (ZrSe<sub>2</sub>), hafnium diselenide (HfSe<sub>2</sub>), molybdenum diselenide (MoSe<sub>2</sub>), and tungsten diselenide (WSe<sub>2</sub>), 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-MSe<sub>2</sub> (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.</p>
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Publication Date
Mon Jun 05 2023
Journal Name
Journal Of Economics And Administrative Sciences
Fuzzy Bridge Regression Model Estimating via Simulation
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      The main problem when dealing with fuzzy data variables is that it cannot be formed by a model that represents the data through the method of Fuzzy Least Squares Estimator (FLSE) which gives false estimates of the invalidity of the method in the case of the existence of the problem of multicollinearity. To overcome this problem, the Fuzzy Bridge Regression Estimator (FBRE) Method was relied upon to estimate a fuzzy linear regression model by triangular fuzzy numbers. Moreover, the detection of the problem of multicollinearity in the fuzzy data can be done by using Variance Inflation Factor when the inputs variable of the model crisp, output variable, and parameters are fuzzed. The results were compared usin

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Publication Date
Mon Nov 01 2010
Journal Name
Al-nahrain Journal Of Science
Chemical Elements Diffusion in the Solar Interior
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