Nickel-chromium-molybdenum (Ni-Cr-Mo) steel alloy systems are used in many automotive and aerospace industries for their strength, toughness, and resistance to fatigue. However, these steels are difficult to machine and tend to distort after heat treatment processes such as carburization, which increases manufacturing costs and decreases precision. This study presents an experimental and data-driven approach to improve machinability, and surface integrity, in Ni-Cr-Mo steel components. Two different heat treatment routes are compared and analyzed to reduce machining challenges and surface roughness. These include the conventional isothermal annealing (ITA) and a newly developed normalizing-subcritical annealing (NSA) process. The NSA process produced a uniform ferrite-pearlite-carbide structure that improved cutting performance and reduced property variation. Surface roughness decreased by nearly 90%, while tool life increased by 126%. The process also lowered machining cost per part by about 50%. Although strength dropped slightly, ductility and impact toughness improved by over 60%, showing a balanced mechanical response. Machine learning models, bolstered by the inclusion of explicit microstructural features, were applied to link material properties to machining outcomes. The integrated models achieved exceptional prediction accuracy, reaching R-2 = 0.9260 for the heterogeneous ITA samples, while predictions for the refined NSA samples reached R-2 = 0.7671 for surface roughness. The difference in model behavior reflected the variation in material uniformity. The NSA route further reduced energy consumption by 34% and CO2 emissions by about 31%, leading to an estimated annual saving of $18,000 for 10,000 parts. The combined experimental and data-driven approach provides a practical pathway to ensure process assurance, machining reliability, and sustainable manufacturing and processing of Ni-Cr-Mo steel components, laying the groundwork for future integration into smart manufacturing and digital twin systems.

This study investigates the influence of cooling rate on the solidification behavior and crystalline phase evolution of equiatomic Ni–Ti alloys using molecular dynamics (MD) simulations. The simulations were conducted by cooling the system from 2000 to 300 K at different rates (0.25 K/ps, 0.75 K/ps, and 2 K/ps). The results reveal that cooling rate plays a critical role in finding the final microstructure. At lowest cooling rate (0.25 K/ps), system exhibits partial formation of the B2 phase with a largely amorphous matrix, indicating limited crystallization due to kinetic constraints. At 0.75 K/ps, the structure remains mostly amorphous with minimal local ordering. At the highest rate (2 K/ps), the alloy shows the emergence of localized FCC and HCP regions, suggesting the onset of crystallization under rapid undercooling. These findings demonstrate that the thermal pathway significantly affects phase selection and microstructural evolution in Ni–Ti alloys, providing insights for tailoring material properties through controlled solidification.

The accelerated rate of technological progress in 3D printing has transformed various sectors like aerospace, medicine, construction, and consumer products. The key to such progress is the variety of feedstock materials, whose selection has a bearing on mechanical properties, printability, and sustainability of the final product. This paper highlights the need for adopting secondary resources like recycled polymer, metal waste, industrial wastes, and bio-based materials as feasible feedstock for additive manufacturing. The important discussion continues into emerging areas like up-cycled materials, high-performance composites, and bio-based printing materials, and then presents a discussion of challenges related to cost, availability, and reliability to reduce carbon foot prints. This article discusses innovative methods for incorporating waste-derived materials like recycled plastics and bio-based filaments for stimulating a circular economy for 3D printing.

Graphite cores in nuclear reactors are critical components subjected to severe irradiation conditions. Despite the known susceptibility of graphite to radiation-induced damage, detailed microstructural analyses are limited. Existing works of literature have identified changes in crystallite morphology and orientation as early indicators of structural degradation, but the precise micro-mechanisms are not fully understood. This research explicates these micro-mechanisms using advanced analytical transmission electron microscopy (TEM) to examine irradiated graphite at doses up to 1 dpa (displacements per atom). TEM imaging and diffraction analysis captured detailed changes in crystallite structure. Even at low radiation doses ( 0.1 dpa), a 15

Nitrogen-doping of platinum/carbon (Pt/C) catalysts in proton exchange membrane fuel cells (PEMFCs) have garnered significant attention due to its potential to enhance catalyst performance by improving the dispersion and stability of Pt nanoparticles. However, the leaching of nitrogen dopants (N-dopants) under the harsh operational conditions of PEMFCs presents a formidable challenge, leading to catalyst degradation and reduced fuel cell efficiency. Understanding this issue is critical for advancing the development of durable and cost-effective PEMFC catalysts. This review critically examines the mechanisms of N-dopant leaching, encompassing electrochemical factors. By integrating insights from recent experimental and theoretical studies, this review recognizes the primary causes of N-dopant leaching and evaluates various mitigation strategies. Key findings include the identification of specific degradation pathways and the effectiveness of different stabilization techniques. The implications of these findings suggest new directions for catalyst design, aiming to improve the stability and longevity of N-doped Pt/C catalysts for PEMFC. This review concludes with recommendations for future research, emphasizing the need for continued exploration of innovative approaches to enhance the durability of N-doped Pt/C catalysts.

Due to their exceptional mechanical capabilities and microstructural stability, high-entropy alloys (HEAs) have emerged as a revolutionary materials class. New opportunities for designing and producing sophisticated components with customised qualities have been made available due to incorporating HEAs with advanced additive manufacturing (AM) processes, including selective laser melting and direct laser deposition. Within the scope of this work, a critical analysis of the microstructural characterisation and mechanical behaviour of HEAs that were manufactured utilising AM is presented. The paper addresses the mechanical properties that develop due to the processing factors, such as hardness, ductility strength, and high-temperature stability. It also shows the effect that parameters put on processing have on the microstructure, which includes grain morphology and phase distribution. In addition to this, the article investigates the various uses of AM-processed HEAs in industrial sectors like the aerospace industry, automobile industry, biomedical industry, and the energy sector. To give a comprehensive summary of the current status of HEAs in additive manufacturing and the future prospects of these materials, the problems connected with the cost, process optimisation, and material design are also covered.

The suitability of alumina powder produced through radio frequency (RF) plasma spheroidization for ceramic 3D printing feedstock is investigated. The fundamental and essential physical and microstructural characteristics of alumina powders for 3D printing are presented in this study. Powder-based ceramic 3D printing requires specific properties, including particle morphology, purity, mechanical, chemical, and thermal attributes. RF plasma spheroidization is an advanced method for producing powders with desired properties on a commercial scale compared to traditional techniques. This technique involves heating and melting irregular alumina bulk particles using RF plasma and then cooling them rapidly to form spherical powders. The spheroidization process results in α-Al2O3 formation and a corundum structure. Particle morphology, structural characteristics, and purity of alumina powder were analyzed using various spectroscopy and microscopy methods, such as electron microscopy, x-ray diffraction, energy dispersive x-ray spectroscopy, and glow discharge mass spectroscopy techniques. Findings showed nearly spherical particles, with diameters ranging from a few to 200 μm and an average size of 84.5 ± 25.2 μm, high crystallization, and 99

Waste heat recovery involves “heat integration”, or utilising heat energy that would otherwise be discarded or released into the atmosphere. Waste heat recovery reduces energy prices, CO2 emissions, and energy efficiency in plants. The Seebeck effect makes thermoelectric generators (TEGs) a significant energy solution. These generators may directly transform waste heat into usable power. To transform heat into useable electrical energy, thermoelectric materials are essential. In general, inorganic materials have been prepared for developing thermoelectric devices. Due to the recent development in novel materials, organic materials will be used for thermoelectric devices, and it has more convenient and advantage than the inorganic materials. Toxicity, fragility, and cost limit the usage of inorganic crystalline semiconductors, which dominate thermoelectric materials. Instead, thermoelectric devices should use affordable, thermally conductive, easy-to-process organic thermoelectric materials. The findings of this study demonstrated both the improved performance and the continued viability of TE materials (carbon materials and inorganic materials).

The performance and durability of Proton Exchange Membrane Fuel Cells (PEMFCs) are critically hindered by the oxidation susceptibility of graphite felt gas diffusion layers (GDLs). This study addresses this challenge by employing a protective coating of 1-Ethyl-3-methylimidazolium Bis(trifluoromethyl sulfonyl)imide ([EMIM] [TFSI]) on the GDL through a dip-coating method, followed by thermal curing to ensure uniform distribution and strong adherence. Comprehensive characterization, including Scanning Electron Microscopy (SEM), X-ray Diffraction (XRD), X-ray Photoelectron Spectroscopy (XPS), and Fourier-Transform Infrared Spectroscopy (FTIR), confirmed the homogeneous coating, adhesion, and maintained porosity and gas diffusion properties of the GDL. The coated GDL exhibited a substantial increase in oxidation resistance, resulting in higher hydrophobicity with a contact angle of approximately 131 degrees, compared to 96 degrees for the uncoated GDL. Electrochemical analyses revealed that the [EMIM][TFSI]-coated GDL achieved a current density of 27 mA cm(-2) at 0.925 V, surpassing the 19 mA cm(-2) of the uncoated GDL at 0.91 V during cyclic voltammetry (CV) analysis. This study is limited by the shortterm stability tests and the specific environmental conditions under which the experiments were conducted. Future work will focus on optimizing the coating process for varied environmental conditions and exploring the scalability of this technique for practical applications.

Neodymium-Iron-Boron (NdFeB) magnets are widely used in various industries due to their exceptional magnetic properties, such as high coercivity, remanence, and maximum energy product. These magnets consist of rare earth elements (REEs) viz., neodymium (Nd), praseodymium (Pr), and Dysprosium (Dy), along with other metals. With the ever increasing demand for REEs and the need to bridge the supply gap, it is crucial to develop alternative methods for their extraction. Recycling metal from scrap magnets is a promising approach to address the pressure on the supply chain and work towards sustainable development. The primary goal of this study is to generate a predictive model based on machine learning to determine the optimal conditions for metal recovery from scrap NdFeB magnets through water leaching after chloridizing roasting. Bench-scale leaching experiments were carried out to generate a dataset for statistical process optimization and machine learning analysis. The leaching kinetics of neodymium was also explored, and mixed-controlled shrinking core model was found to be most suitable, with an activation energy of 58.11 kJ/mol in the temperature range of 25- 95 degrees C. This study is the first to utilize a machine learning approach to analyze the potential process variables and their impact on metal recovery from calcined NdFeB magnet powder. A comparative analysis between experimental and machine learning approaches is presented to predict the optimal conditions for selective recovery of metal values from scrap NdFeB magnets. The maximum efficiency of extraction of metal ions was found to occur at a temperature of 95 degrees C, solid to liquid ratio of 125 g/l, and leaching duration of 60 min.

The potential of green hydrogen to make India self-sufficient and energy-independent is reviewed in this study. We integrated technological advancements, economic analysis, and policy frameworks to provide a comprehensive overview of the green hydrogen landscape in India. This review examines cost reductions in electrolyzer technology, the potential for renewable energy integration, and the socio-economic benefits of green hydrogen adoption. Additionally, the study proposes innovative policy measures tailored to India’s unique conditions, such as targeted subsidies and incentives for green hydrogen production and use. The research highlights significant cost reductions and increased renewable power generation as key factors contributing to the economic viability of green hydrogen in India. It underscores the importance of large-scale production and advancements in electrolyzer technology. Furthermore, the study emphasizes the necessity of clear regulatory frameworks, infrastructure development, and financing to support the deployment of a green hydrogen economy in India. By implementing a strategic roadmap for green hydrogen, India can reduce its reliance on fossil fuels, lower greenhouse gas emissions, and become a major player in the global green hydrogen market. The proposed policy measures and technological advancements are crucial for successfully adopting and deploying green hydrogen, ensuring energy self-sufficiency and long-term economic sustainability for India.

Thermoelectric power generation from low-cost carbon-based materials represents an exciting frontier in renewable energy technology. It is a cutting-edge technology that effectively converts waste heat into electricity. By harnessing the principles of the Seebeck effect, this technology has the remarkable capability to tap into waste heat from diverse sources, ranging from industrial processes to automotive exhausts. In recent years, carbon materials have garnered significant attention for their potential as highly promising candidates for efficient thermoelectric generation. The purpose of this paper is to discuss the sustainability and eco-friendliness of carbon-based materials as alternative sources of thermoelectric power generation and to assess their enormous potential in this regard. Further it evaluates the physical properties to optimize their thermoelectric performances. It has been identified that there are various forms of carbon that can be used for a range of applications.

Proton exchange membrane fuel cells (PEMFCs) are an auspicious energy conversion technology with the potential to address rising energy demands while reducing greenhouse gas emissions. The stack's performance, durability, and economy scale are greatly influenced by the materials used for the PEMFC, viz., the membrane electrocatalyst assembly (MEA) and bipolar flow plates (BPPs). Despite extensive study, carbon-based materials have outstanding physicochemical, electrical, and structural attributes crucial to stack performance, making them an excellent choice for PEMFC manufacturers. Carbon materials substantially impact the cost, performance, and durability of PEMFCs since they are prevalently sought for and widely employed in the construction of BPPs and gas diffusion layers (GDLs)) and in electrocatalysts as a support material. Consequently, it is essential to assemble a review that centers on utilizing such material potential, focusing on its research development, applications, problems, and future possibilities. The prime focus of this assessment is to offer a clear understanding of the potential roles of carbon and its allotropes in PEMFC applications. Consequently, this article comprehensively evaluates the applicability, functionality, recent advancements, and ambiguous concerns associated with carbon-based materials in PEMFCs.

Nano-structured coatings have been used to simulate adiabatic engines with the aim of not only reducing heat rejection and thermal fatigue protection of the metallic surfaces but also potentially reducing internal combustion engine emissions. With this research work, the main emphasis is on optimizing the best coating thickness and studying the effects of nano-structured coatings on the engine's fuel consumption and thermal efficiency with the support of varying conditions. Emission measurements of hydrocarbon (HC), nitrogen oxide (NO x ), and carbon dioxide (CO 2 ) were also conducted in this study. In this study, the inlet and exhaust valves were coated with titanium nitride (TiN) material, using a magnetron sputtering technique. TiN was deposited at different thicknesses, such as 2, 3, 4, 5, and 6 microns, over the whole surface of the internal and exhaust valves. The results showed that the brake thermal efficiency (BTE) and NO x emissions were increased, and the specific fuel consumption, CO, and HC emissions were decreased for the thermal coated exhaust valve compared to the standard engine. Peak cylinder pressures for 4 µm thick coatings increased by up to 8.30% in the thermal barrier coating (TBC) engine, particularly at high power outputs; however, exhaust gas temperatures were generally lower, indicating noble gas expansion in the power stroke that initiated the peak cylinder pressure rise and impacted BTE, which increased by 1.6%. The result demonstrates that the TiN coating on the valve serves superior performance to the engine up to an optimum coating thickness beyond which the performance drops off. The characteristics are examined by using an experimental setup and measuring experimental values from the setup for different conditions.

Graphite is used as a moderator and reflector in many nuclear reactors, where it is exposed to high temperatures, stress, radiation, and other harsh conditions. Under these conditions, graphite undergoes microstructural changes, the consequences of which can lead to deformation, cracking, and ultimately fracture. This research highlighted aims to investigate the microstructural based micromechanics of graphite materials and focus is on understanding the micromechanics based on microstructural degradation and changes in crystalline grain structure, their orientations, and boundaries in polycrystalline graphite for predicting structural damages in the graphite material. This study utilises analytical transmission electron microscopy to examine the nature of grain boundaries and extract important microstructural parameters. The crystallites and contained boundaries, including their orientations in a polycrystalline structure, all have the potential to influence the properties of the material. Under the harsh conditions of temperatures, radiation, and stress that graphite experiences in the reactor core, it is crucial to understand its microstructural behaviour and its influence on its properties. This research brings insight into the potential mechanisms of structural damage based on the nature of grain boundaries and crystalline orientations. The key investigations are the bending of crystallites along the interfaces, causing the division of coherently scattered domains into smaller crystallites. On analysing the traces across the crystallites, it was also observed that each crystallite was rotated in a similar direction. These crystallites bending is referred to as a micro-bending feature in graphite. This micro-bending deformation mode is less commonly observed in graphite, and the identification of these micro-mechanisms and their correlation with crystallite bending and rotation within polycrystalline structure provides insights into the deformation behaviour and potential degradation mechanisms in the graphite material.

Raman spectroscopy is a powerful, noninvasive, and non-contactual vibrational spectroscopic technique. As an optical surface scanning technique, it is capable of detecting endogenous biomolecules inside cells and tissues and used to detect changes in structure and composition during the dysplastic transformation of cellular components. A combination of Raman spectroscopy and microscopy has also been used to study biomolecular processes at the cellular level. Moreover, Raman microscopy may be used to diagnose diseases noninvasively because it offers features such as in vivo and ex vivo imaging, rapid spectral acquisition, superior molecular sensing, deeper depth profiling, and superior chemical sensitivity. Additionally, it has capabilities for 3D sectioning, non-label imaging, pharmacokinetics analysis, and in situ monitoring of diseases and drugs. Raman microscopy has been shown to be successful in biomedical applications because healthy tissues differ significantly from diseased tissues in terms of chemical composition. Furthermore, various tags have been examined for the identification, diagnosis, and control of disease development based on a fundamental understanding of chemical processes with Raman imaging and spectroscopic measurements. This article provides an overview of Raman microscopy in biomedical research and applications. An emphasis is placed on how Raman imaging has been applied to different biomedical domains, such as disease monitoring and medical diagnostics. Further, the article discusses technological developments, data processing, and emerging technologies such as machine learning, before concluding with a discussion of the potential uses of these methods.