Mechanical Engineering, Ceramics and Composites, Renewable Energy, Sustainability and the Environment, Polymers and Plastics
30
Scopus Publications
Scopus Publications
Mechanical and Tribological Properties of Synthetic and Agricultural Reinforced LM26-AlN-Coconut Shell Ash Hybrid Composites Fabricated via Powder Metallurgy Technique Puneet Kumar Sonker, Thingujam Jackson Singh, Ashish Srivastava, Binayak Nahak, Sandeep Kumar Singh Advanced Engineering Materials, 2026 In this study, LM26 Al‐alloy reinforced with 5 wt% aluminum nitride powder (AlNP) and varying coconut shell ash powder (CSAP) content (0.0, 1.5, 3.0, 4.5, and 6.0 wt%) is synthesized using powder metallurgy (P/M). The influence of these reinforcements on the physical properties, microstructure, mechanical behavior, and tribological performance of the composites is systematically investigated. Phase identification and elemental composition are assessed using X‐ray diffraction and energy‐dispersive spectroscopy, whereas field emission scanning electron microscopy is used to examine the powder morphology and microstructure of composites. The results indicate that increasing the CSAP content led to a decrease in both green and sintered density, reaching values of 2.36 and 2.42 g cm−3, respectively. The composite containing 5 wt% AlN and 4.5 wt% CSAP exhibits the highest microhardness (54.15 HV) and compressive strength (406.03 MPa), showing improvements of 26.23% and 119.80%, respectively. Fretting wear tests demonstrated that wear loss and the coefficient of friction (COF) decrease up to 4.5 wt% CSAP, followed by an increase beyond this concentration. Furthermore, higher normal loads intensify both wear rate and COF. Worn surface analysis indicates that delamination and abrasion wear are the dominant mechanisms.
Synergetic Effect of Surface-Functionalized 2D Carbon-Based Polymer Nanocomposite to Enhance the Mechanical and Thermal Properties of Lightweight Materials for Electric Vehicles Sandeep Kumar Singh, Thingujam Jackson Singh, S. Prashanth, Puneet Kumar Sonker, Laishram Dhanabir Singh, Yogendra Kumar Verma Lightweight Materials for Electric Vehicles Sustainable Materials Production Process and Modeling Techniques, 2026 Two-dimensional carbon-based polymer nanocomposites represent an intriguing category of materials, consistently showing improved mechanical and thermal properties due to synergistic effects compared to their individual components. Research has shown that the performance of carbon-based nanomaterials can be significantly influenced by interface engineering, which involves aspects such as structural design, material synthesis, surface functionalization, and the detailed analysis of well-defined interfaces within 2D carbon structures (such as GNPs, graphene, CNTs, CNFs, etc.) and various non-carbon functionalizing agents (like APTES, dopamine, GPTMS, etc.) have significant potential for enhancing the physical, chemical, and thermal properties. This approach leverages the high surface area, thermal stability, and sustainability of surface-functionalized nanofillers to enhance the mechanical and thermal performance of 2D carbon-based polymer composites for diverse applications in automobile parts (such as body panels and chassis components, battery enclosures, brake components, interior structural parts, etc.). Key challenges include understanding nanoparticle–matrix and filler–filler interfaces, tracking load-transfer mechanisms, and assessing load-carrying capacity, with recent advancements in experimental techniques highlighting their role in reinforcing nanomaterials. A comprehensive review highlighting advancements in this field has been conducted through a systematic evaluation of relevant literature from both academic and industrial perspectives, focusing on lightweight, high-strength, wear-resistant, and low-friction components, as well as noise and vibration reduction of electric vehicles.
Improvement of Fracture Toughness of Epoxy Nanocomposites Through In-Plane Crack Propagation Resistance Offered by Wet Ball-Milled Graphene Oxide Sandeep Kumar Singh, Thingujam Jackson Singh, Sudipta Halder, Nazrul Islam Khan, Puneet Kumar Sonker Polymers for Advanced Technologies, 2025 Fascinating features of 2D graphene oxide (GO) have very high potential to enhance the mechanical performance and fracture toughness of epoxy composites after successful dispersion in the epoxy matrix. The dispersion of GO in a highly viscous epoxy matrix was achieved by lateral exfoliation and longitudinal size reduction of graphene sheets. GO was synthesized via an improved Hummer's method, exfoliated through dual‐mode ultrasonication for 20, 30, and 60 min, and reduced to nanoscale (~217 to 227 nm) using high‐energy wet ball milling for 9 h. The synthesized GO and BGO were characterized using XRD, FT‐IR, Raman spectroscopy, FESEM, and TGA to confirm crystal structure, functional groups, defect density, surface morphology, and thermal stability respectively. It was observed that even at higher filler loadings of 1 wt.% of GO and BGO exfoliated for 60 min (GO60@1% and BGO60@1%), the resulting nanocomposites showed a substantial improvement in tensile strength by 39.92% and 41.91%, respectively, and modulus by 6.92% and 12.90%, respectively compared to the NE. Whereas, incorporation of GO60@1% and BGO60@1% into epoxy matrix significantly enhanced fracture toughness ( K IC ) by ~72% and ~140% respectively and the fracture energy ( G IC ) by ~322% and ~356%, respectively with respect to NE. The enhancement is attributed to the superior dispersibility of BGO, which facilitates strong and consistent interfacial interactions with the epoxy matrix, thereby improving the material's resistance to fracture. The exfoliation of GO through ball milling can be a suitable method for industries to prepare graphene‐based nanocomposites with significantly high tensile and fracture properties.
Compaction modeling and physicomechanical characterization of LM26 alloy powder via powder metallurgy P. K. Sonker, T. J. Singh, A. Srivastava, A. Kumar, S. K. Singh Materialwissenschaft Und Werkstofftechnik, 2025 This study investigates the densification behavior and mechanical properties of LM26 aluminum alloy powder subjected to various compaction pressures in powder metallurgy. The powder's flowability and compressibility were evaluated using the angle of repose, Carr's index, and Hausner ratio, confirming its suitability for compaction processes. Particle characterization through dynamic light scattering, energy‐dispersive x‐ray spectroscopy, field emission scanning electron microscopy, and x‐ray diffraction revealed insights into particle size, elemental composition, morphology, and crystalline phases. Green density, determined by mass‐to‐volume ratio, ranged from 77.45 % to 96.02 % at pressures of 100 MPa–550 MPa, with a notable linear relationship between applied pressure and density. The Panelli and Ambrosio Filho model best described the compressibility behavior. Mechanical testing showed significant increases in Vickers hardness, reaching 42.89 HV 0.2 for cube specimens at 550 MPa and 44.12 HV 0.2 for cuboid specimens at 250 MPa. Flexural strength reached a peak of 30.44 MPa at 250 MPa, highlighting the benefits of higher compaction pressures. Weibull distribution analysis confirmed the uniformity and reliability of hardness and strength characteristics, reinforcing the applicability of powder metallurgy for structural applications.
Investigation of mechanical and thermo-mechanical properties of dopamine-functionalized TiO2/epoxy nanocomposites Sandeep Kumar Singh, Thingujam Jackson Singh, Sudipta Halder, Nazrul Islam Khan Polymer Composites, 2025 In the last decades, tremendous research has been performed to enhance the thermo‐mechanical properties of polymer composites with lightweight, high strength, and low density with respect to conventional materials. The present investigation deals with an approach towards the enhancement of thermo‐mechanical properties of nanocomposite by incorporating bio‐inspired dopamine functionalized titanium dioxide (TiO2) nanofiller. Material characterization has been performed via XRD, SEM, FT‐IR, and TGA to confirm the synthesis of TiO2 and ensure proper surface functionalization over TiO2 nanopowder. The epoxy nanocomposite was fabricated by blending varying weight percentages (0–2%) of surface functionalized DTiO2 nanoparticles, using a dual mixing probe ultrasonication technique to achieve uniform dispersion. The most significant enhancements in mechanical properties, counting tensile strength, flexural strength, and work of fracture (WOF), showed an optimum increase of 29%, 24%, and 63%, respectively, notably at a 1 wt% concentration of DTiO2 60 particles as compared to the base composite. Additionally, the tensile and flexural moduli enhanced by 26% and 30%, respectively, at 2 wt% TiO2. Examination of fracture surfaces using FESEM indicated that the surface‐modified DTiO2 nanofillers were uniform and dispersed within the epoxy matrix, highlighting improved interfacial adhesion. The incorporation of 1 wt% TiO2 resulted in a substantial increase in storage modulus of 179%, along with improvements in glass transition temperature (110°C) and damping factor (0.6), while maintaining other thermal properties. To expand industrial usability, eco‐friendly nanofillers need to meet established standards, confirming the fabrication of robust epoxy nanocomposite systems suitable for structural composite manufacturing.Highlights Surface functionalization of TiO2 with dopamine has been done by the sol–gel method. An avg. particle size of DTiO2 powder is approximately 120 nm with a rough surface after functionalization. DTiO2‐infused epoxy nanocomposites were prepared, and their thermo‐mechanical properties were examined. Tensile strength and storage modulus were improved by ~29% and ~179%, respectively. FESEM fracture surface analysis showed improved mechanical interlocking between the filler and matrix, leading to shearing –yielding.
A Robust Freeway Accident Detection System with Deep Learning Methods Using Connected Vehicle Trajectory Data Avinash Haorongbam, Dushmanta Kumar Das, Thingujam Jackson Singh Advances in Transdisciplinary Engineering, 2025 Optimizing last-mile Hyper-local Networks (HLN) has gained immense importance due to the challenges posed by limited storage capacity and the unpredictable nature of customer demand, especially in the context of same-day or on-demand deliveries. The paper addresses the formulation of a last-mile Hyper-local Networks (HLN) problem, emphasizing the challenges posed by high demand with uncertainty. In the context of last-mile hyperlocal networks (HLN), the focus is on specific areas like megacities or tier-1 cities. Traditionally, last-mile logistics used remote fulfillment centers and large vehicles, but growing demand for same-day delivery and unpredictable customer needs have led to the adoption of decentralized local fulfillment centers and satellite stations. This paper addresses the need to optimize last-mile HLN, proposing the Opposition-Based Criminal Search Optimization Algorithm (OBCSO) to enhance efficiency. Comparative analysis shows OBCSO’s superiority over traditional methods, with significant performance improvements and reduced computational time as demand increases.
Optimal design and performance evaluation of last-mile hyper-local network problem with uncertain demand Avinash Haorongbam, Dushmanta Kumar Das, Thingujam Jackson Singh Journal of Intelligent Transportation Systems Technology Planning and Operations, 2025 The growing demand for rapid, same-day deliveries has made the optimization of last-mile Hyper-local Networks (HLN) increasingly critical. These networks face challenges such as limited storage capacity and highly variable customer demand, which complicates delivery planning and resource allocation. This study aims to address the HLN design problem under uncertain and fluctuating demand conditions, to enhance delivery efficiency and system robustness. To achieve this, we propose a novel meta-heuristic optimization algorithm: the Composite Learning Strategy Criminal Search Optimization Algorithm (CLS−CSOA), enhanced with a Time-varying Inertia Weight mechanism. This approach is designed to balance exploration and exploitation phases during optimization, thereby producing more efficient and adaptive solutions. We assess the method using a combination of benchmark functions and realistic last-mile delivery scenarios. Comparative experiments show that CLS−CSOA consistently outperforms conventional algorithms in solution quality, robustness, and computational efficiency. Statistical validation via the Wilcoxon Signed-Rank test confirms its superiority, with a notably low Type II error rate. Three real-world case studies, reflecting varying levels of customer demand, demonstrate the practical applicability of the model. The results show significant improvements in delivery performance and a reduction in computational time. Importantly, the algorithm maintains high performance under increasing demand variability, underscoring its scalability and adaptability. This research provides practical implications for urban logistics by offering a lightweight, high-performance alternative to data-intensive methods, supporting agile and cost-effective last-mile delivery systems, especially for small and medium-scale logistics providers.
Orthogonal criminal search optimisation algorithm with time-varying inertia weight for last-mile hyper-local network problem with uncertain demand Avinash Haorongbam, Dushmanta Kumar Das, Thingujam Jackson Singh International Journal of Systems Science Operations and Logistics, 2025 Given the constraints of limited storage space and unpredictable customer demand in last-mile Hyper-local Networks (HLN), optimising this process has become crucial for on-demand and same-day delivery, especially for megacities and metropolitan entrepreneurs, startups, and small firms with limited space and also to demand fulfilling e-commerce giant. To address this challenge, a novel metaheuristic algorithm called the Orthogonal Criminal Search Optimisation Algorithm (OCSOA), inspired by Criminal Search Optimisation, is introduced in this paper. The effectiveness of the algorithm is assessed through simulations of benchmark functions and a real-world problem associated with last-mile HLN. Comparative analysis reveals that OCSOA outperforms traditional optimisation methods by demonstrating robust exploration and exploitation capabilities. Through extensive testing, it emerges as the leading algorithm with a low Type II error rate in the Wilcoxon Signed Rank test. Additionally, three case studies are conducted, considering the varying levels of customer demand, and the results highlight significant performance enhancements and reduced computational time as demand increases. These simulated results contribute valuable insights into last-mile data, providing perspectives distinct from the high-cost data associated with e-commerce giants. The model also improved the necessity for convenience and cost optimality as per the end consumers' dire requirements.
Experimental analysis of performance and emission of a turbocharged diesel engine operated in dual-fuel mode fueled with bamboo leaf-generated gaseous and waste palm oil biodiesel/diesel fuel blends Biswajeet Nayak, Thingujam Jackson Singh, Anh Tuan Hoang Energy Sources Part A Recovery Utilization and Environmental Effects, 2025 In the present situation of emergencies of energy demand, rising oil cost, exhaustion of nonrenewable energy source assets. Biodiesel as well as producer gas acquired from vegetable oil, that is, waste palm cooking oil and biomass, that is, waste bamboo leaves are likely to be designated as the promising substitute fuel. Therefore, the goal of this research is to access the reduction in global warming gases mostly NOx and smoke associated with the introduction of producer gas along with waste cooking oil biodiesel. The current investigation draws out a test of preparing biodiesel from used waste palm cooking oil at different blending proportions and its application on a dual fuel mode turbocharged direct injection diesel engine, with varying load at a fixed speed of 1500 rpm. From the experimentation, it was seen that exhaust gas temperature and brake thermal efficiency reduced while, brake specific energy consumption increased by 10.81%↓, 14.08%↓, and 46%↑ relative to diesel fuel in single fuel mode. Taking into account the emission characteristics of smoke intensity, nitric oxide lowered by 63.59%↓, 91.71%↓but on the cost of higher hydrocarbon and carbon monoxide value of 40.63%↑ and 65.71%↑ in comparison to diesel mode when loaded to the maximum limit. Hence, it can eventually be concluded that waste palm cooking oil methyl ester blended biodiesel with bamboo leaf generated gaseous fuel can partially substitute existing diesel fuel with few engine alternations.
Effect of stacking sequence on mechanical strength of bamboo/kevlar K29 inter-ply laminated hybrid composite Indian Journal of Fibre and Textile Research, 2017
