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    On the Multi-parallel Diodes Model in Au/PVA/n-GaAs Schottky Diodes and Investigation of Conduction Mechanisms (CMs) in a Temperature Range of 80-360 K

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    Au/PVA/n-GaAs (MPS) type Schottky diodes (SDs) were fabricated and investigated in a temperature range of 80-360 K to explain their possible conduction mechanisms (CMs). Three distinct linear regions with different slopes were observed in ln(I)-Vplots. The first region (R1), is within the range of 0.22-0.60 V, the second region (R2), is within the range of 0.64-0.90 V, and the third region (R3), is within the range of 1.1-1.5 V. It was shown that both ideality factor (n) and zero-bias barrier height (phi(Bo)) are strong functions of temperature for all three regions. It was noticed thatnvalues decreased and phi(Bo)values increased with increasing temperature. In order to ascertain the possible CMs, phi(Bo) - n, - phi(Bo) - q/2kT, and (n(-1) - 1) - q/2kTplots were also examined. In each of these plots, two linear regions were obtained within each of the three regions. The region from 80-180 K is called the low-temperature range (LTR), and the region from 200-360 K is called the high-temperature range (HTR). It has been revealed that the reason for the deviation from the classical thermionic emission (TE) theory cannot be explained only by the existence of the interface layer, interface states (N-SS) or quantum mechanical tunneling mechanisms, which can be also explained by the double Gaussian distribution (DGD) due to barrier inhomogeneity. Finally, the experimental Richardson constants (A{*}) were calculated from the interception point of the modified Richardson curve in LTR and HTR for all three regions. It was calculated as 6.22 and 8.13 A/cm(2)K(2)for RI, 7.77 and 8.14 A/cm(2)K(2)at R2, and 7.07 and 8.13 A/cm(2)K(2)at R3 for low- and high-temperature ranges, respectively. It is clear that especially HTR results are quite close to the known theoreticalA{*} value of 8.16 A/cm(2)K(2)for n-GaAs

    An adaptation of pseudo-score confidence interval method for linear mixed models

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    We adapt a confidence interval method based on a generalized Chi-Square test for fixed effect parameters of linear mixed models. Under different correlation structure of a response variable of a linear mixed model, the performances of the adaptation method pseudo-score and some of the existing confidence interval methods are investigated by carrying out a Monte Carlo simulation study. The simulation study suggests that pseudo-score method provides better results for small to moderate sample size cases with dependent observations in terms of coverage probability rates and average expected lengths. A depression study is analyzed for demonstrating the adaptation method

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