Enhancement of Photovoltaic Systems Using Plasmonic Technology Humam Al-Baidhani, Saif Hasan Abdulnabi, Maher A. R. Sadiq Al-Baghdadi Processes, 2025 The rise in temperature worldwide, especially in hot regions with extreme weather conditions, has made climate change one of the critical issues that degrades the solar photovoltaic (PV) system performance. In this paper, a new design of solar cells based on plasmonic thin-film Silver (Ag) technology is introduced. The new design is characterized by enhancing thermal effects, optical power absorption, and output power significantly, thus compensating for the deterioration in the solar cells efficiency when the ambient temperature rises to high levels. The temperature distribution on a PV solar module is determined using a three-dimensional computational fluid dynamics (CFD) model that includes the front glass, crystalline cells, and back sheet. Experimental and analytical results are presented to validate the CFD model. The parameters of temperature distribution, absorbed optical power, and output electrical power are considered to evaluate the device performance during daylight hours in summer. The effects of solar radiation falling on the solar cell, actual temperature of the environment, and wind speed are investigated. The results show that the proposed cells’ temperature is reduced by 1.2 °C thanks to the plasmonic Ag thin-film technology, which leads to enhance 0.48% real value as compared to that in the regular solar cells. Consequently, the absorbed optical power and output electrical power of the new solar cells are improved by 2.344 W and 0.38 W, respectively.
Super-high transmission, ultra-compact size, and very high modulation depth plasmonic de(multiplexer) based on elliptical disk resonator Mohammed Sabah Talib, Faris Mohammed Ali, Saif Hasan Abdulnabi Journal of Nanophotonics, 2025 Photonic devices face limits in size due to diffraction, whereas plasmonic technology allows for smaller devices. Plasmonic multiplexers/demultiplexers are crucial for all-optical arithmetic logic units, with performance measured for them by transmission (T), contrast ratio, modulation depth (MD), and insertion loss. We present, construct, and simulate a new design for an all-optical 2×1 Mux and 1×2 demultiplexer using elliptical disk insulator–metal–insulator plasmonic waveguides. A maximum transmission efficiency of 250% is displayed by this structure, a feature not investigated in previous studies. Given that the MD exceeded 98%, the proportions of this design are excellent and ideal. This entire feat was accomplished with a mere 300×250 nm size. The reason for obtaining these transmission efficiency values is that the suggested designs have three inputs. Using COMSOL Multiphysics, the proposed plasmonic Mux and Demux are simulated using the finite element method via trial and error.
All-Optical Demultiplexer/Multiplexer Based on Plasmonic Technology With Ultra-High Transmission, Ultra-Small Size, and Very High Modulation Depth Sajjad Mohanad Mustafa, Gholamreza Karimi, Mazdak Rad Malek Shahi, Saif Hasan Abdulnabi International Journal of Optics, 2025 Photonic devices are of paramount importance in various fields, particularly in the realm of electronics. Nevertheless, miniaturization and the diffraction limit are the two issues that have plagued the development of photonic devices. Plasmonic devices solve these issues by enabling nanophotonics and nanodevices. A plasmonic demultiplexer/multiplexer is one of the essential all‐optical logic devices used in an all‐optical arithmetic logic unit (ALU). It is considered as a fundamental building block for all‐optical computers. In this work, an all‐optical demultiplexer (Demux) and multiplexer (Mux) based on ring insulator–metal–insulator (IMI) plasmonic waveguides are designed in a new structure. The area of the proposed design is minimal (300 × 300 nm), and it operates at a wavelength of 1550 nm. The transmission threshold between the logic 0 and 1 states in Demux and Mux is 0.5. Five parameters describe the performance of the plasmonic Demux and Mux; these parameters are transmission (T), extinction ratio (contrast ratio (CR)), modulation depth (MD), insertion loss (IL), and contrast loss (CL). The maximum transmission efficiency of the device is 203%, and the proposed structure dimensions are excellent and optimal according to the value of MD for Demux and Mux, which are 96.42% and 98.51%, respectively. The CR for Demux is 3.01, indicating a moderated level of performance. On the other hand, the CR for Mux is 2.568, which is considered adequate. Furthermore, the IL value is moderate for Demux and Mux, with respective values of 2.67 and 2.5, respectively. Moreover, the CL is considered appropriated for Demux and Mux, with values of 0.33 and 0.068, respectively. In addition, the minimum value of crosstalk (XT) in Demux is −11.55 dB. The proposed plasmonic Demux and Mux structure significantly contributes to the nanophotonic integrated circuits and all‐optical signal processing nanocircuits. The proposed plasmonic Mux is simulated by the finite element method (FEM) using COMSOL Multiphysics software.
High data-rate two-three inputs all-optical and gate based on FWM in highly nonlinear fiber Adnan Sabbar, Saif Hasan Abdulnabi, Hassan Falah Fakhruldeen Journal of Optical Communications, 2024 In this paper, two-and-three channel all-optical AND logic gates based on four-wave mixing in a highly nonlinear fiber for 120 Gbps on–off keying signals were designed, simulated, and investigated. Simulation results show low bit error rate and consequently fairly high Q-factor at the receiving end in both two and three inputs AND gates, as well as the logic operation, is confirmed by the open eye diagrams with moderate power penalties for both designs.
Neural Network-based System Identification: A Comprehensive FPGA Design and Implementation Saif Hasan Abdulnabi, Yousif Samer Mudhafar, Ali Abdulhassan Kadhim, Mohammad Baqer Mahdi, Hassan Hadi Sojar International Conference on Artificial Intelligence and Mechatronics System Aims 2024, 2024 Neural networks are more commonly used to identify systems for system diagnostics without fully implementing and building the system. The project aims to design and implement the neural network identification system and implement it based on a Field Programmable Gate Array (FPGA) by interfacing between MATLAB / Simulink and Xilinx programs. The work was done thanks to God through two methods: the first through the simulation method through the coupling between MATLAB and Xilinx. While the second method was practically done by loading the simulation designs onto the FPGA. Work performance is measured by subtracting the value resulting from the actual system operation of the identification signal system and the simplified system and the difference between the simulation result and practical result. The use of FPGA with system identification in this project gives us a big advantage that simulation results are equal to practical results (difference is zero).
