Krupajal Engineering College, Bhubaneswar, also called KEC is an engineering institution in the Eastern Zone of Odisha, which was established in 1995 under the Krupajal Group of institutions. The college certifies to ISO 9001:2000 and is rated as an A grade engineering college by NACC.The college is approved by AICTE, New Delhi, affiliated to Biju Patnaik University of Technology, Odisha and accredited by NBA & NAAC, New Delhi situated at Kausalya Ganga, Puba Sasan, Bhubaneswar. It has 30 acres of area with a built up area of 1.5 lac square feet.
The selective semi-synthesis of thymol from pulegone, a carcinogenic monoterpenoid, is crucial for regulatory compliance in nutraceutical, pharmaceutical, and flavor industries. A novel 2.5 %Al-1.5 %B-3 %Pd/AC composite was developed as well as validated Al3+-B interactions to facilitate cyclohexane ring dehydrogenation, and Pd active sites for selective hydrogenation of C--C and C--O groups. The catalyst achieved a high thymol yield of 98.5 % under moderate conditions (70 degrees C, 33 psi H2, 62 min), and exhibited excellent stability along with maintaining over 95 % activity after five regeneration cycles. Structural analyses confirmed the catalyst's robustness with minimal Pd sintering observed after reuse. Scale-up experiments using Mentha (CIM-Vishisht) and DMO oils successfully reduced pulegone content below 0.5 %, meeting stringent safety standards. Additionally, the thymol-enriched products demonstrated strong antimicrobial efficacy against both Gram-negative and Gram-positive strains. This study highlights a promising catalytic approach for selective monoterpenoid valorization and scalable bioactive compound production.
To tackle the challenges of environmentally friendly dielectric fluid, the current research focuses on the diverse biodegradable oils that are utilised as dielectric fluids in electro-discharge machining (EDM) processes. When it comes to machining extremely hard materials, EDM is a cutting-edge, non-traditional technology. As part of this research, Ti-6Al-4 V material has been machined in two phases: the first phase, using conventional EDM oil, and the second phase, utilising four distinct bio-dielectric fluids. Comparisons have been made between EDM oil and other bio-dielectric fluids in terms of machining performance measures such as material removal rates (MRR), tool wear rate (TWR), and surface roughness (SR). The primary goal of this research is to identify an appropriate bio-dielectric fluid that will be environmentally acceptable, cost-effective, and provide better machining performance when compared to other dielectric fluids on the market. When the MRR, TWR, and SR are taken into account, mixed vegetable oil is found to be the best bio-dielectric fluid, and in cases where only the MRR is considered, sunflower oil is the best dielectric. It was discovered that the surface obtained with sunflower oil is the best in terms of crack size and number of cracks when compared to other dielectric fluids.
This study delves into the realm of federated learning, focusing on its application in the private and accurate artificial intelligence (AI) diagnosis of schizophrenia. Leveraging the collaborative power of distributed datasets without compromising individual privacy, the research investigates the feasibility and effectiveness of federated learning models. The study employs advanced AI algorithms for schizophrenia diagnosis, ensuring the confidentiality of patient data. The results demonstrate the potential of federated learning as a secure and efficient approach for enhancing diagnostic capabilities in mental health, specifically in the context of schizophrenia. This research contributes to the ongoing efforts to harness cutting-edge technologies for improved mental health diagnostics while prioritizing individual privacy.
This research paper focuses on evaluating the performance of a Rayleigh step bearing under thermo-mixed-EHL condition combining the effect of deterministic and stochastic surface roughness. Sinusoidal and sawtooth waveforms are considered as the deterministic roughness on the bearing’s surface, whereas stochastic roughness such as isotropic, longitudinal, and transverse roughness is considered on both interacting surfaces. The shear flow factor has been taken into consideration for the stochastic roughness of different standard deviations in roughness heights. All related equations are iteratively solved using an advanced computational algorithm. A remarkable change in the bearing’s performance is witnessed due to the combined action of deterministic and stochastic roughness. In the contact area, generated pressure is maximum in bearing having sawtooth with transverse roughness, whereas this pressure is minimum in bearing having sinusoidal with longitudinal roughness. A significant change in bearing’s performance is witnessed upon changing the value of convergence ratios, base length ratios, and roughness parameters.
Fe2O3 was modified by doping Ni and Pd to obtain 3%Ni-1.5%Pd/Fe2O3HT catalyst via the hydrothermal process for selective hydrogenation of citral to nerol and geraniol. This catalyst was prepared by different techniques like co-precipitation, wet impregnation, and hydrothermal process, and their activity towards citral hydrogenation was thoroughly studied. The prepared catalysts were thoroughly characterized. Various parameters such as pressure, temperature, reaction time, and metal weight (%) have been optimized through the RSM-BBD module to attain high selectivity towards nerol and geraniol. The optimal reaction conditions of 6.45 bar pressure, 3%Ni-1.5%Pd loading at 72.1 degrees C for 84 min, the citral (>99%) was converted to nerol/geraniol with 97.2% of selectivity. The modified catalyst activated the oxygen species of the carbonyl atom and thus favours the selective hydrogenation of the C = O bond without reducing the C = C bond. This process is very effective for the selective transformation of citral (75%) in lemongrass essential oil to organoleptically superior nerol/geraniolrich oil using 3%Ni-1.5%Pd/Fe-2O3(HT) catalyst.
