College of Engineering Pune (COEP), is a college affiliated to Savitribai Phule Pune University in Pune, Maharashtra, India. Established in 1854, it is one of the oldest engineering colleges in India, after College of Engineering, Guindy, Chennai (1794) and IIT Roorkee (1847). The students and alumni of College of Engineering, Pune are colloquially referred to as COEPians.
The soil properties have a strong impact on agricultural productivity, crop selection, and sustainable land management. Soil pH is one of the most significant factors influencing nutrient availability, microbial activity, and soil fertility. Conventional soil testing approaches have proven to be time-consuming, taking time, problems with symmetry, and expensive, making them difficult to scale for fieldwork in agriculture. This work explores the use of DL methodologies that will utilize basic soil attributes such as electrical conductivity (EC), phosphorus, potassium, organic carbon, and lime to predict soil pH. A real time soil data collected from different villages in Sangli, Miraj district, Maharashtra, India and developed neural network model. The model was fitted with regression metrics, resulting in a MAE 0.732, showing depth of its prediction capabilities on soil pH. Soil analysis based on Feedforward Deep Neural Network provides a data-driven technique for precision agriculture with applications in the real-time monitoring of soil health and the precise application of fertilizers. The results emphasize how AI can revolutionize conventional agriculture by enabling farmers to make data-driven decisions based on precision soil data, leading to sustainable agricultural practices and improved crop yields. Ongoing research will involve a larger data corpus, further environmental parameters, and network architecture optimization to improve prediction accuracy.
Copper Indium Gallium Diselenide (CIGS) solar cells are regarded as promising due to their good electrical and optical features. In this work we have simulated substrate structure of CIGS thin film solar cell using SCAPS-1D software. The current study investigates the effect of different window layers on the electrical parameters of a solar cell. Different window layers have been used, including ZnO, In2S3, ITO, AZO, and ZnMgO. The dependence of efficiency on window layer and defect density is clearly visible in this work. Efficiency shows variation from 25.81% to 28.14%. Apart from efficiency, the current and voltage generated are dependent on the window layer and the defect concentrations connected with it. AZO yields the efficiency of about 28 % whereas, ITO contribute least efficiency near about 25%. Thickness optimization of window layers simulated in this work was carried out. This study demonstrates that AZO and ZnMgO are favorable materials for creating the window layer in CIGS solar cells. Small deviation was found in efficiency upon change in defect density. The thickness of window layers employed in this work was optimized. Thickness of window layers shows an adverse effect on photovoltaic features. Band alignment shows variation upon change in window layer.
Formula Student (FS) Competition provides a platform for engineering students to showcase their ability to conceptualize, design and produce a working model of a formula style race car. With aim to tackle growing concerns of fossil fuel stock, environmental impact and climate change, governments around the world are embracing new technologies. One such technology being electric vehicles (EV). In light of this push to move away from fossil fuels and to embrace electric technology, the host organization has put together a series of initiatives under the Formula Student banner to build a platform for students interested in switching to the Formula Student Electric category. But EVs is still in its nascent stage of development; and thus, the field is highly esoteric from student’s point of view. Accumulator is one of the most important parts of an electric race car; it powers the entire car along with its tractive system. The paper demonstrates a simple approach at achieving a suitable battery design and its thermal management. Beginning with selection of suitable motor for drivetrain followed by estimation of energy requirement through MATLAB OpenLap simulation. Basis this requirement, a suitable cell configuration is designed. The battery pack is a potential source of heat generation and for its optimal performance during the race day, thermal management system is of utmost importance. A fan-based cooling system is devised to handle this heat load. This approach though not too complex provides a comprehensive method, right from motor selection to thermal system design for Formula Student racecar.
Remazol Brilliant Blue R (RBBR), an anthraquinone-based dye, has emerged as a contaminant in water sources, posing ecological threats. This study explores the photocatalytic degradation and adsorption of RBBR and its byproducts using a biocompatible HAp-ZnO nanocomposite. The nanocomposite was synthesized for its optical and antibacterial properties. The combined experimental and theoretical approach aims to elucidate the degradation mechanism. Under UV irradiation, the nanocomposite effectively eliminates RBBR (> 93
