Chandigarh Group of Colleges

This study investigates the enhancement of mechanical performance in polylactic acid (PLA) components fabricated using fused deposition modeling (FDM) through the application of a zinc coating via the electric arc thermal spray process. Three major parameters of FDM processing such as infill density (60, 80 and 100 percent), printing speed (20, 40 and 60 mm/s) and the infill pattern (linear, triangular and hexagonal) were systematically studied on tensile and flexural strengths of the coated PLA specimens. Moreover, the experimental design was optimized by means of Taguchi L9 orthogonal array and mechanical properties (tensile and flexural strength) were determined with the help of a universal testing machine (UTM). The findings indicate that tensile and flexural behaviors are controlled by unique optimum combinations of the parameters. The highest tensile strength of 53.44 MPa was achieved at 100 percent infill density, a print speed of 40 mm/s and triangular infill pattern. However, the highest flexural strength of 146.6 MPa was achieved at 100 percent infill density, a print speed of 20 mm/s and hexagonal infill pattern. These results reveal that incorporating FDM with electric arc thermal spray coating could provide a promising path to boosting dramatically the mechanical performance of 3D-printed PLA components to expand their scope of use in high-end engineering disciplines.

Magnesium ferrite (MgFe₂O₄) is increasingly recognised as a sustainable, visible-light-active, and magnetically recoverable photocatalyst for dye degradation. This review provides a comprehensive and critical analysis of the structural, optical, and magnetic characteristics of MgFe2O4. It further examines how synthesis routes, dopant incorporation, and nanostructural morphology influence its photocatalytic efficiency toward Malachite Green degradation. Special emphasis is placed on understanding the mechanistic aspects of photoexcitation, charge-carrier separation, defect engineering, and the generation of reactive oxygen species (ROS) that underpin its catalytic performance. The article further evaluates recyclability, long-term stability, and process scalability, integrating techno-economic and sustainability perspectives which are very crucial for the industrial implementation. Finally, the review identifies existing knowledge gaps and outlines emerging research opportunities aimed at developing an efficient, durable, and truly green MgFe₂O₄-based photocatalytic systems for the sustainable wastewater treatment applications.

Through the Tridosha system of Ayurveda, doctors evaluate human operations through physical and mental features using the Pitta, Kapha, Vata classifications. The researchers developed a combination learning system to process structured Ayurvedic records containing 25 physical and behavioral characteristics of $\mathbf{6, 6 1 5}$ cases for accurate Tridosha type assignments. The preprocessing stage included label conversion as the core operation before SelectKBest executed feature selection and SMOTE performed data balancing on standardized features. The research team created Random Forest and Gradient Boosting and Stacked Ensemble models separately before performing evaluation. The highest performance level was achieved by using Random Forest along with Gradient Boosting as base learners joined by a Logistic Regression meta-learner which generated 99.15% training accuracy and 98.93% validation accuracy, followed by 92.44% external test accuracy. The model demonstrated complete results because it achieved high precision performance along with high recall and an F1-score and an AUC value of 1.00. The use of Ensemble learning methods led to the development of real-time diagnostic tools featuring processed features suitable for Ayurvedic medical diagnostics. The modeling field works to enhance reliability features through developing complex systems and acquiring additional medical data in order to deliver individualized healthcare services.

This study examines the influence of graphene reinforcement on WC-17Co coatings applied to AISI 304 stainless steel via high-velocity oxy-fuel (HVOF) spraying. The goal was to improve the turbine blade resistance to wear, friction, and erosion. SEM analysis showed that the WC-17Co coating had a dense, low-porosity microstructure. Adding graphene added nanosheets that made it easier to bridge cracks and spread stress. EDS showed that the composite had more carbon, and XRD showed that the WC and Co phases were still there, but with small changes that were thought to be due to graphene interaction. Scratch tests showed that WC-17Co + Graphene coatings were better at stopping cracks from starting. They could hold loads of up to 75 N with fewer interfacial failures than WC-17Co. Pin-on-disc sliding wear tests showed that graphene-reinforced coatings lost up to 30% less weight and had lower friction coefficients when loads of 2-6 kg were applied. Tests of slurry erosion at different speeds, impact angles, and slurry concentrations showed that WC-17Co + Graphene coatings lost an average of 33% less weight than WC-17Co. The dual role of graphene in strengthening and lubricating materials was thought to be the reason for these improvements.

OBJECTIVE:The primary aim of the study is to highlight the application of Quality by Design (QbD) in the formulation of parenterals, with a focus on academic and industrial aspects. SIGNIFICANCE:Parenteral formulations, particularly those administered intravenously, provide substantial therapeutic benefits and 100% bioavailability. However, problems like drug solubility, stability, sterility, and manufacturing viability hinder their development. By methodically tackling these issues, QbD helps guarantee consistent patient safety and product quality, while minimizing wastage of time and resources. METHODS:This review was carried out by focusing on the implementation of ICH Q8-Q10 guidelines and QbD frameworks to parenteral drug development, while emphasizing tools such as critical process parameters (CPPs), critical quality attributes (CQAs), design of experiments (DoE), and process analytical technology (PAT). To illustrate real-world applications, case studies from academia and industries were additionally examined. KEY FINDINGS:The study demonstrates how QbD enables robust parenteral formulations by facilitating a thorough understanding and control of both formulation and process factors. QbD implementation, as shown in the case studies, improved formulation robustness, risk mitigation, regulatory compliance, and lifecycle management. CONCLUSION:The review concludes that QbD implementations in parenteral formulation increase the quality of the product. It also states that the safety of parenteral products can be ensured by considering factors such as contamination, particle size, osmolarity, and others when designing the formulation.