Motilal Nehru National Institute of Technology

ABSTRACT This investigation focuses on the development of dual‐layer coating of AlN and TiAlN by Chemical vapor deposition (CVD) to improve surface protection for advanced engineering applications. The Aluminium nitride (AlN) interlayer was first deposited on p ‐type c‐Si (100) substrates over a temperature range of 200°C to 800°C, followed by the TiAlN top layer. The effect of deposition temperature on the structural, morphological, mechanical, and electrochemical properties of the coatings was systematically investigated. Surface morphology and microstructure were examined using Field emission scanning electron microscope (FESEM), while phase composition was studied by X‐ray diffraction (XRD). Atomic force microscope (AFM) provided insights into nanoscale surface roughness, and Raman spectroscopy confirmed the vibrational modes of the coating phases. The X‐ray photoelectron spectroscopy (XPS) analysis confirmed the formation of strong Titanium‐Nitride (Ti─N), Aluminium nitride (Al─N), and Aluminium Titanium nitride (Al─Ti─N) bonds, indicating successful synthesis of a chemically stable dual‐layer structure. Nanoindentation revealed that the dual‐layer coating deposited at 700°C exhibited superior hardness and Young's modulus values of 29.64 and 209.69 GPa, respectively, indicating improved mechanical integrity. Electrochemical corrosion testing demonstrated excellent corrosion resistance, with the lowest corrosion current density observed for the coating formed at 700°C. Collectively, the results confirm that CVD‐deposited AlN/TiAlN dual‐layer coating offer a promising route for surface engineering applications that requires high hardness, better tribological property, and corrosion resistance in aggressive environments.

Button mushroom (Agaricus bisporus) cultivation in India is highly seasonal due to strict microclimatic requirements and limited access to controlled environment infrastructure among smallholder farmers.

Online credit card transactions have witnessed a steady year-to-year growth, making fraud detection an increasingly critical challenge. Credit card fraud detection is particularly difficult due to the extreme class imbalance between fraudulent and non-fraudulent transactions. Imbalanced data, where one class heavily dominates the other, must be addressed before effective fraud detection can be achieved. Traditional oversampling techniques such as the Synthetic Minority Over-sampling Technique (SMOTE) and its variants often generate synthetic samples without considering the importance of ranking performance in the minority class distribution, leading to suboptimal classification performance. To address this, an adaptive Weight and rank-based Minority (WRM-SMOTE) oversampling method is proposed that prioritizes the performance and its relative ranking. To the best of our knowledge, WRM-SMOTE is among the first method to combine performance-based weighting and ranking across multiple SMOTE variants for adaptive oversampling. This method transforms imbalanced datasets into balanced ones through adaptive synthetic sample generation. The process begins by computing a weight based on two componentsabsolute performance and relative ranking. This is done to provide a distinction between two variants with extremely similar performance when one outperforms the other. Our experimental results on real-world credit card fraud datasets and eleven other benchmark datasets demonstrate that WRM-SMOTE significantly improves fraud detection performance, achieving higher precision and recall while maintaining a balanced false-positive rate compared to traditional oversampling methods. The proposed method effectively enhances classification accuracy by generating synthetic samples in high-impact regions thereby improving the robustness of fraud detection models.

Abstract Bathymetry is a critical input to storm surge models on coastlines fronted by lagoon systems, yet few studies explore how variations in bathymetry influence flood impacts, flooded extent, and exposed population across these globally widespread morphologies. Here, we investigate the influence of variations in bathymetry on storm inundation impact estimates across a continental shelf lagoon system. We explore how flooded extents and exposed population estimates from a 1% storm for Belize vary with estimated depths by comparing three existing bathymetries over a northern shallow, enclosed lagoon and a central deeper, open lagoon system with a newly developed bathymetry data set, Satellite‐Derived Bathymetry Enhanced Data set‐SDBED. We compare multiple bathymetric data sets to understand the influence on the flood uncertainties and the quantity of the impact of exposed population estimates. Our results show that greater estimated lagoon depths consistently result in lower predicted flood impacts for both lagoon systems in almost all cases. Unexpectedly, for one bathymetry with a median depth of 2 m in the northern lagoon, we find that a reduction in lagoon volume by 59% reduces total inundation volume by 45%. Our findings also show how vertical uncertainties in the SDBED bathymetry propagate through the model, resulting in variations of up to 12% in flood extents and up to 2% in exposed populations.

This review focuses on the materials development utilized for enhancing long-term efficiency of hydropower plants and its sustainability. It begins by contextualizing the global transition toward renewable energy, distinguishing between renewable and non-renewable energy sources, and underscoring the strategic importance of hydropower in meeting growing ecological and energy demands. The study delves into the technological evolution of hydroelectric systems, with a focused analysis on the engineering design and materials employed in the underwater parts of hydro turbines susceptible to mechanical degradation. A comprehensive evaluation of materials is presented ranging from traditional options like wood and cast iron to modern solutions such as stainless steels, advanced steel alloys, polymer matrix composites, and nano-engineered materials, with a focus on their mechanical properties and resistance to cavitation, erosion, corrosion, and fatigue. The review also highlights surface modification and various processing such as heat treatment and thermomechanical processing techniques aimed at enhancing material performance under aggressive hydro-operating conditions. Finally, the paper identifies the key challenges in material selection and development for hydropower applications and outlines future directions needed to ensure improved durability, reduced maintenance, and overall enhancements in the efficiency of hydro turbine and sustainability of hydropower plants.

The photonic spin Hall effect (PSHE) originates from the spin–orbit interaction (SOI) of light. The literature indicates that the transverse spin-dependent shift, δH− (SDS), from the PSHE is weak (in the nanometer range) and difficult to measure directly. This study utilizes a plasmonic structure to improve the δH− in the PSHE. The obtained results of this study demonstrate that the inclusion of silicon nitride (Si3N4) significantly enhances the δH− relative to its absence; however, plasmonic material is present in both cases. The enhanced shifts exhibit a significant dependence on the resonance angle (θr) and the thickness of layers of the PSHE structure to attain the maximum increase in δH− of 350.82 µm at the plasmonic resonance condition. A systematic analysis of the centroid positions of the reflected beam indicates a distinct and constant separation of opposing spin components. Further, the improved δH− is utilized in cancer cell detection, as changes in the refractive index (RI) of cells facilitate the identification of cancer cells from healthy to cancerous. All examined cell types demonstrate that cancerous cells had a greater δH− than normal cells, owing to their elevated effective RI. These results illustrate that the proposed plasmonic-assisted PSHE structure offers significant enhancement and a high sensitivity of 439.30 µm/RIU for label-free detection of cancer cells.