Sudhanshu Shekhar Pati

In this study, we developed a capping‐agent‐free synthesis of GNPs using an L‐Phenylalanine‐derived organic compound (PHY) as both a reducing and stabilizing agent. The synthesis was monitored using UV‐Vis spectroscopy, which confirmed GNP formation with a plasmonic extinction band at 520 nm, and is in good correlation with the TEM results. FTIR studies indicated the involvement of hydroxyl (─OH) and carboxyl (─COO ⁻ ) functional groups in gold binding. TEM imaging revealed the formation of uniformly dispersed GNPs with an average size of 4 nm, while ESI‐MS analysis confirmed PHY‐gold interactions. The catalytic potential of the synthesized GNPs was evaluated through the reduction of p‐nitrophenol (4‐NP) to p‐aminophenol (4‐AP), yielding a rate constant of 0.456 min ^{− 1} . The results suggest that PHY‐derived GNPs offer an efficient alternative for catalytic applications, providing new insights into nanoparticle stabilization without the need for capping agents.

The pure Ca₂V₂O₇ nanomaterial was successfully synthesized via a coprecipitation technique followed by annealing at 550 °C. Comprehensive characterization using XRD, UV–vis DRS, FTIR, BET, HRTEM, and XPS confirmed its crystalline phase, optical properties, surface morphology, and elemental composition. Photocatalytic evaluations under visible light irradiation (250 W metal halide lamp) revealed remarkable activity in the degradation of organic pollutants, achieving 79.5% removal of safranine O dye and 80.6% removal of tetracycline hydrochloride antibiotics within 180 min. These pollutants are of global environmental concern due to their persistence and harmful impacts on aquatic ecosystems. In addition to environmental remediation, the Ca₂V₂O₇ nanomaterial was employed for photocatalytic hydrogen generation as a sustainable energy approach to reduce reliance on fossil fuels. Using Na₂S and Na₂SO₃ as sacrificial electron donors, bare Ca₂V₂O₇ exhibited a significantly higher hydrogen evolution rate compared to TiO₂ and pure water, producing a total of 1474 μmol H₂ over 26 h with only 0.05 g catalyst. Electrochemical analysis and band structure evaluations indicated that its superior performance arises from efficient charge separation and favorable band edge positions. Furthermore, XRD analysis after prolonged photocatalysis confirmed the structural stability of Ca₂V₂O₇, underscoring its potential for long-term practical applications in both clean energy production and environmental remediation.

To optimize the cathodic electro deposition paint film on automobile body for corrosion protection, AI driven solutions are generated. Cathodic electro deposition technique has been adopted for coating process by controlling process variables such as surface area, non-volatile matter, processing time, bath temperature, and electrode voltage. An artificial neural network model has been developed using the experimental dataset to train and enable it to predict dry film thickness. The proposed ANN model has been evaluated with an error rate of 6% which is well within the accepted limit of 10%. The study also shows that mild steel’s dry film thickness was more responsive to electrode voltage and bath temperature than other metals. The study suggests that to achieve the most economical output, it is recommended to maintain the bath chemistry while adjusting the physical characteristics such as voltage and temperature, as indicated by the findings.