To acquire the optimal value of the performance parameter, a bilayer graphene with silicon on insulator (SOI) was enhanced and analyzed on 22 nm NMOS device. After the predictive modeling, both FF and PCE of the perovskite photovoltaic cell have been improved for ~5.93% and ~5.78% respectively. The final results reveal that the proposed hybrid L27 OA Taguchi-based GRA-MLR-GA approach has effectively optimized the device parameters in which SnO2:F thickness, SnO2:F donor density, ZnO thickness, ZnO donor density, CH3NH3PbI3-xClx thickness, CH3NH3PbI3-xClx donor density, Spiro-OMeTAD thickness and Spiro-OMeTAD acceptor density are predictively tuned at 0.198 μm, 8.973 x 1018 cm-3, 0.039 μm, 8.827 x 1017 cm-3, 0.386 μm, 1.929 x 1013 cm-3, 0.233 μm and 8.984 x 1018 cm-3 respectively. The Perovskite photovoltaic cell model is initially constructed and simulated using solar cell capacitance simulator (SCAPS). In this paper, a predictive modeling using a hybrid L27 orthogonal array (OA) Taguchi-based Grey relational analysis (GRA), multiple linear regression (MLR) and genetic algorithm (GA) was proposed to optimize the device parameters for better overall performance. Perovskite photovoltaic cell is regarded as an alternative configuration for the conventional photovoltaic cells predominantly due to its high efficiency. 174 keV of halo implant energy, 1.63 × 10¹⁴ atom/cm³ of S/D implant dose, 17 keV of S/D implant energy, 24° of halo implant tilt angle and 9° of S/D implant tilt angle are the best parameter setting in obtaining the highest Ion/Ioff ratio of the device which is measured at 4.811 × 10⁵. The final results indicate that the 1.99 × 10¹³ atom/cm³ of halo implant dose. The largest factor effects on SNR of S/D implant energy shows that it has dominantly affected the ION/IOFF ratio. Utilizing both signal-to-noise ratio (SNR) and analysis of variance (ANOVA), the most dominant process parameters upon ION/IOFF ratio are identified as S/D implant energy and S/D implant dose with 56% and 37% factor effects on SNR respectively. The process parameters and the noise factors are optimized using the L9 orthogonal array (OA) of Taguchi method to achieve the highest possible ION/IOFF ratio. halo implant energy, source/drain (S/D) implant dose and source/drain (S/D) implant energy, while the noise factors are halo implant tilt angle and source/drain (S/D) implant tilt angle. The investigated process parameters are halo implant dose. The retardation of B diffusion can well be explained by the phosphorus doping level resulting in a Fermi level shift and pairing of B and P ions, both reducing the B diffusivity.The simulation and statistical modeling are conducted using Silvaco TCAD tools and L9 orthogonal array (OA) of Taguchi method respectively to design a proposed layout of 10 nm gate length (Lg) Bilayer Graphene Field Effect Transistor (Bi-GFET). Based on the observations the B diffusion retardation was classified into three groups: (i) no reduction of B diffusivity, (ii) reduced B diffusivity, and (iii) blocking of the B diffusion. A secondary ion mass spectrometry (SIMS) analysis of the BSG layer after the B diffusion revealed that the B diffusion retardation is not due to potential P content in the BSG layer but rather caused by the n-type doping of the crystalline silicon itself. The influence of the initial P concentration was investigated in moremore » detail by varying the P implantation dose. Here, it was found that not the defects created during ion implantation but the P doping itself results in the observed B diffusion retardation. First, the influences of ion implantation induced point defects as well as the initial P doping on B diffusivity were studied independently. The implantation of Phosphorus leads to a substantial blocking of Boron during the subsequent Boron diffusion. A dramatic reduction in the number of interstitials bound in furnace diffusion and preceding Phosphorus ion implantation. Phosphorus concentrations ranging from 2.0 x 1017 to 4.0 x 1019 cm-3 and Si+ doses ranging from 5.0 x 1013 cm-2 to 2.0 x 1014 cm-2 are studied during 650-800Â☌ anneals. The effects of background phosphorus concentration, self implant dose, and anneal temperature are investigated. Damage recovery of 40keV Si+ implants in phosphorus doped wells is experimentally analyzed. This research focuses on experimentally investigating and modeling the clustering of phosphorus dopant atoms with silicon interstitials. In order to control these effects, it is vital to have a clear understanding of dopant-defect interactions and develop models that account for these interactions. Ion implantation of dopant atoms into silicon generates nonequilibrium levels of crystal defects that can lead to the detrimental effects of transient enhanced diffusion (TED), incomplete dopant activation, and p-n junction leakage. Phosphorus-defect interactions during thermal annealing of ion implanted silicon
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