Introduction. The huge demand of green energy over past few decades have drawn the interest of scientists and researchers. Solar energy is the most abundant and easily available source but there have been so many problems with its optimum extraction of output. The factors affecting the maximum power point tracking of PV systems are input irradiance, temperature, load etc. The variations in irradiance level lead to partial shading that causes reduction in performance by not letting system to operate at maximum power point. Many methods have been proposed in literature to optimize the performance of PV systems but each method has shortcomings that have failed all of them. The actual problem occurs when partial shading is very strong; this is where most of the methods totally fail. So proposed work addresses this issue and solves it to the fullest. The novelty in the proposed work is that it introduces a new nature-based algorithm that works on the principle of plant propagation. It is a natural optimization technique that plants follow to survive and propagate in different environmental conditions. The proposed method efficiently tracks the global peak under all shading conditions and is simple to implement with high accuracy and tracking speed. Purpose. Building an algorithm that can track global peak of photovoltaic systems under all shading conditions and extracts the maximum possible power from the system, and is simple and easy to implement. Methods. The method is implemented in MATLAB / Simulink on an electrical model that uses a PV array model. Different shadings are applied to check for the results. Results. The results have shown that for different photovoltaic configurations the algorithm performs very good under uniform and partial shadings conditions. Its accuracy, tracking efficiency and tracking time has increased reasonably. Practical value. The project can be very beneficial to people as it enhances the performances of PV systems that can make them self-sufficient in electrical energy, focuses on sustainable development and reduces pollution. This way it can have huge impact on human life.

Silver (Ag) nanoparticles (NPs) are synthesized and characterized by a low-cost chemical reduction method. Silver nanoparticles (Ag NPs) have pre-occupied the consideration of the scientific community due to their wide range of functions, utility and industrial applications, particularly in the fields of sensing technologies and medicine (particularly their efficiency against microbes, the ability of healing the wound and anti-inflammatory properties). Ag NPs are synthesized by a low-cost fabrication method. X-ray diffraction (XRD), scanning electron microscopy (SEM), energy dispersive X-ray diffraction (EDX) and photometry techniques are used in this work to identify their nature and potentiality for diverse applications in sensing technologies.

The paper is composed of distinct reviews on various fabrication technologies of the CMOS family and the characterization of MOS capacitors. The initial part of the article essentially presents a systemic review on an already conducted work on different fabrication technologies such as Si MOSFET, SiGe HBT, and InP HBT. Device and circuit-level performance for broadband and tuned millimetre-wave applications is discussed in detail relative to the underlying CMOS technologies. The comparison is made for various performance metrics for 180 nm, 130 nm, and 90 nm n-MOSFET devices for SiGe and InP HBTs. In the latter part of the study, a comprehensive review on a previously conducted research on electrical and physical characterization of metal-oxide-semiconductor (MOS) capacitors fabricated on a 2.5 μm epitaxial germanium layer grown on (100) silicon substrate is undertaken. The focus and crux of the study is the influence of germanium surface preparation on MOS electrical characteristics. It is observed that predielectric (HfO) deposition annealing in NH₃ ambience results in the performance upgradation in critical and key parameters such as equivalent oxide thickness and the gate leakage current.