A time-coupled multi-objective distributionally robust chance-constrained framework for grid resilience enhancement using mobile emergency generators D. Ashokaraju, M. L. Ramamoorthy, Deepa Simon, N. Ashok, Abhijit Bhowmik Scientific Reports, 2026 This study presents a time-coupled, multi-objective distributionally robust chance-constrained (MODRCC) framework for resilient grid restoration using Mobile Emergency Generators (MEGs). The model unifies (i) time-expanded logistics for MEG routing, crew scheduling, and refuelling, (ii) islanding-feasible DC-OPF under line outages, and (iii) Wasserstein-ball ambiguity to hedge uncertainty in attack severity and travel-time delays. Disjunctive linearization and second-order-cone (SOC) embeddings yield a tractable MISOCP that is evaluated inside an NSGA-II evolutionary search to generate the Pareto frontier between total cost and resilience. Experiments on IEEE-24 and IEEE-118 (12-hour horizon, 24 periods) show that, at comparable budgets, the proposed method reduces expected unserved energy (EUE) by 14-20% relative to static DRCC and classical robust baselines. On the IEEE-118 case, representative operating points illustrate a ~ 54% decrease in EUE (92→42 MWh) for a ~ 10% increase in cost along the frontier, evidencing smooth, convex trade-offs induced by Wasserstein regularization. The solver stack (Gurobi 12.0 + NSGA-II) scales efficiently; with parallel fitness evaluation it converges in ~ 2.8 h for IEEE-118 (16 MEGs). Results confirm that explicitly coupling mobility realism with distributionally robust modelling yields operationally credible, cost-aware restoration schedules suitable for disaster-prone regions.
Hybrid optimization of WEDM control parameters for Kovar using VIKOR-AHP and R method Kamal Ukey, Anil R. Sahu, Himadri Majumder, N. Ashok, Abhijit Bhowmik Scientific Reports, 2026 Kovar alloy is widely used in electronics, aerospace, and precision applications due to its thermal expansion compatibility with ceramics and glass, yet its difficult machinability demands optimized WEDM parameters for improved performance. To address this challenge, the present study aims to evaluate the influence of key WEDM factors and identify optimal machining conditions for Kovar. Experiments were conducted using a Taguchi L 27 orthogonal array considering servo voltage, pulse on-time, pulse off-time, and wire feed rate as machining parameters, and their effects on cutting speed, machining time, and surface roughness were systematically analyzed. A hybrid multi-criteria decision making approach combining AHP-based weighting with VIKOR compromise ranking was employed alongside the R-method for comparative validation. Results show that the parameter set Ton: 121 µs, Toff: 49 µs, SV: 20 V, and WF: 4 m/min. achieved the best overall machining performance. Importantly, both the AHP-VIKOR method and the R-method identified the same optimal settings, demonstrating strong agreement and confirming the robustness of the hybrid optimization framework. The study highlights the scientific contribution of integrating statistical ranking with structured multi-criteria analysis to enhance decision quality in multi-response WEDM optimization for Kovar alloy.
Constitutive behaviour and microstructural evolution in thermally deformed Al–Zn–Mg alloy Katika Harikrishna, Abeyram Nithin, Guttikonda Manohar, Kasagani Veera Venkata Nagaraju, Bethelehem Burju Bukate, Abhijit Bhowmik Scientific Reports, 2026 Commercial simulation software often lacks comprehensive material data for alloys fabricated through powder metallurgy (PM), creating challenges in developing accurate constitutive models. Establishing a clear understanding of the correlation between microstructure and mechanical behaviour during hot deformation is essential for optimizing alloy performance across diverse processing and service conditions. Thus, this study addresses these challenges by constructing and comparing the traditional Johnson Cook (JC) and Modified Johnson Cook (MJC) models for predicting flow stress. Additionally, the study investigates the correlation between microstructure and mechanical properties during the hot compression of an Al-Zn-Mg PM alloy. Experiments were conducted at various temperatures (300 °C and 500 °C) and strain rates (0.1 s⁻¹ and 0.0001 s⁻¹) to evaluate the effect of compression parameters on microhardness, flow stress and microstructural evolution. Electron Backscatter Diffraction (EBSD) analysis revealed that Kernel Average Misorientation (KAM), high-angle grain boundaries (HAGBs), low-angle grain boundaries (LAGBs), and average grain size are significantly influenced by the deformation conditions. The MJC model, with advanced features like a quadratic strain term and strain-rate-dependent temperature factor, achieves higher accuracy, evidenced by an R value of 0.994, AARE of 3.935%, and RMSE of 1.05 MPa. These results highlight the MJC model’s superiority in capturing complex deformation behaviours. At 300 °C and 0.1 s⁻¹, the microhardness reached 130 HV, with a high LAGB percentage (97.33%) and a fine average grain size of 10.91 μm, indicating a strain-hardened microstructure. Conversely, at 500 °C and 0.0001 s⁻¹, the microhardness decreased to 62 HV due to the dominance of dynamic recrystallization, which increased HAGBs percentage (7%) and grain size (19.72 μm). The Zener-Hollomon parameter and activation energy effectively correlate temperature and strain rate effects on microhardness and stress. Higher Z values indicate restricted grain growth and increased dislocation density, resulting in higher microhardness and stress values.
Evaluation of cutting speed and surface roughness in WEDM of functionally graded A356-10 wt% Si3N4 composite S. Prathap Singh, D. Elil Raja, C. Ramesh Kumar, K. Gnanasekaran, Abhijit Bhowmik, Kedir Hussen, S. Sowndar, M. Sundara Cholan Scientific Reports, 2026 Functionally graded composites (FGCs) have planned spatial changes in the distribution of the reinforcement and thus radial gradients in hardness, thermal conductivity, and microstructure. In this research, Al (Aluminium) A356 alloy reinforced with Silicon Nitride (Si₃N4) FGC was fabricated through a vertical centrifugal casting technique. The optical microscope, X-ray Diffraction (XRD), and Vicker’s microhardness evaluator examined the gradient distribution of ceramic particles. Such gradients pose great problems in the Wire Electrical Discharge Machining (WEDM), where the distribution of spark energies and the capability to remove materials become a zone-dependent process. The main aim of the research work is to investigate the effect of various machining control variables on the Cutting Speed (CS) and surface roughness during the machining in WEDM. An L27 experimental design was employed to systematically evaluate the influence of pulse on duration, wire tension, wire drum speed, and different zones of the FGC. Analysis of Variance (ANOVA) revealed that pulse on duration had the dominant effect on CS (80.30%), while wire tension was the primary contributor to surface roughness (33.11%). The increase in CS is attributed to higher spark energy concentration and improved plasma stability, which enhance the rate of localized melting and material expulsion, whereas the uniform wire movement stabilized the spark discharge, thereby reducing surface roughness. These findings help optimize WEDM parameters for FGCs, improving engineering applications’ machining efficiency and surface quality.
Experimental evaluation of alumina nanoparticle additives in sunflower oil methyl ester for enhanced CI engine performance and emission control Jasgurpreet Singh Chohan, K. Prakash, P. Vijay, M. K. Aravindan, Premananda Pradhan, Ashwin Jacob, Yashwant Singh Bisht, Abhijit Bhowmik, Yalew Tamene Scientific Reports, 2026 This study experimentally investigates the performance, combustion, and emission characteristics of a compression ignition (CI) engine fueled with sunflower oil methyl ester (SOME) biodiesel–diesel blends, with specific emphasis on alumina (Al₂O₃) nanoparticle enhancement. Biodiesel blends ranging from 20% to 100% SOME were initially evaluated, among which the 40% blend (SOMED40) exhibited the most balanced fuel properties and combustion behaviour. Consequently, SOMED40 was further modified with 50 ppm of Al₂O₃ nanoparticles and tested under identical operating conditions. Engine experiments were conducted at a constant speed of 1500 rpm over varying load conditions, with key performance and emission improvements primarily observed at full engine load. At full load, the Al₂O₃-enriched SOMED40 blend demonstrated a 5.35% increase in brake thermal efficiency (BTE) and a 1.55% reduction in brake-specific fuel consumption (BSFC) compared to neat SOMED40. Emission analysis revealed substantial reductions, with carbon monoxide (CO) decreasing by 23.5%, hydrocarbons (HC) by 14.8%, nitrogen oxides (NOx) by 13.33%, and smoke opacity by 15.79% relative to SOMED40. When compared with conventional diesel at full load, the nano-enhanced blend achieved 25% lower NOx emissions and a 27.27% reduction in smoke opacity. These improvements are attributed to the catalytic activity and high thermal conductivity of Al₂O₃ nanoparticles, which promote improved atomization, enhanced combustion efficiency, and more uniform heat release. The findings demonstrate that alumina nanoparticle addition effectively mitigates the performance and emission limitations of biodiesel fuels. The SOMED40/Al₂O₃ blend emerges as a viable, cleaner alternative to conventional diesel fuel for CI engines without requiring any engine modifications.
Plasmonics-driven graphene electronics for beyond-5G and 6G communication systems G. T. Danappa, Mahantesh M. Math, R. Vinayakumar, Vikram N. Bahadurdesai, G. R. Rajkumar, Sujan Chakraborty, Y. P. Deepthi, Abhijit Bhowmik, Bethelehem Burju Bukate Journal of Materials Science Materials in Engineering, 2026 Graphene, a two-dimensional monolayer of carbon atoms in a honeycomb lattice, has become a cornerstone material for plasmonics, offering unprecedented opportunities for next-generation communication and electronic platforms. Its ultra-high carrier mobility (> 200,000 cm 2 /Vs), superior thermal conductivity (≈5000 W/mK), and atomic-scale thickness enable strong light-matter interactions and support highly confined surface plasmon polaritons across terahertz to infrared frequencies. This review emphasizes graphene’s role in advancing plasmon-assisted technologies, with particular focus on terahertz communication, integrated photonic circuits, and reconfigurable plasmonic metamaterials. Emerging device architectures including graphene field-effect transistors (GFETs), plasmon-enhanced photodetectors, and tunable nanoantennas are discussed in terms of resonance tuning, bandwidth control, and energy efficiency. Advances in chemical vapor deposition (CVD), epitaxial growth, and hybrid graphene-metal plasmonic integration are highlighted as critical steps toward scalable, CMOS-compatible platforms. Key challenges such as plasmon damping, fabrication uniformity, and efficient coupling with dielectric waveguides are critically evaluated alongside novel strategies in doping, patterning, and heterostructure engineering. Finally, the future trajectory of graphene plasmonics is examined, positioning it as a transformative enabler for 6G communication, quantum-secure plasmonic networks, and energy-efficient Internet of Things (IoT) infrastructures.
Energy-efficient wireless sensor network for urban groundwater level monitoring using machine learning and sink mobility Rachit Manchanda, Ailaboina Vijaya Lakshmi, Gaganjot Kaur, Gadug Sudhamsu, Satish Kumar Samal, G. D. Anbarasi Jebaselvi, Ranjan Kumar, Abhijit Bhowmik, N. Ashok Scientific Reports, 2026 Urban groundwater level monitoring is vital for enabling data-driven decision-making and sustainable urban water resource management. Wireless Sensor Networks (WSNs) offer an effective solution for real-time observation of spatially distributed underground water sources. However, conventional WSN protocols often face significant limitations, such as unbalanced data routing, excessive energy consumption, and the energy hole problem near the sink. To overcome these challenges, this paper proposes an energy-efficient WSN protocol named Sleep Scheduled Data Aggregation with Sink Mobility (SSDA-SM), specifically designed for Urban Groundwater Monitoring (UGM) in heterogeneous sensor networks. The protocol incorporates a machine learning (ML)-based probabilistic clustering mechanism to optimize Cluster Head (CH) selection, considering residual energy, node density, and average network energy. To further conserve energy, a proximity-aware sleep scheduling strategy selectively deactivates redundant nodes, while dynamic sink mobility uniformly balances communication load and mitigates the energy hole problem. Moreover, to reduce transmission overhead, Compressive Sensing (CS) is applied at the CH level for data aggregation, and the original data is accurately reconstructed at the sink using an appropriate decoding algorithm. The SSDA-SM protocol is implemented and simulated in MATLAB. Performance evaluation shows that SSDA-SM significantly outperforms existing protocols such as OCNTMS, MEDF, SEI \(^{2}\) , and MACOA across various metrics including network lifetime, energy consumption per round, data throughput, packet delivery ratio, end-to-end delay, cluster stability, compression ratio, and reconstruction accuracy. These results demonstrate that SSDA-SM is a robust, scalable, and energy-efficient solution for long-term urban groundwater level monitoring using heterogeneous WSNs.
Data-driven optimization of machining parameters for Hastelloy C276 using PSO and TLBO frameworks Mosleh M. Abualhaj, B. Venkatesh, Kiran D. Parmar, Akanksha Mishra, D. T. Arunkumar, Ripendeep Singh, Abinash Mahapatro, V. K. Bupesh Raja, Abhijit Bhowmik, Yalew Tamene Scientific Reports, 2026 Hastelloy C276 is renowned for its exceptional resistance to corrosion and elevated temperatures, rendering it a preferred material for aerospace and chemical processing applications. However, its high strength and work-hardening tendency pose significant challenges during machining. This study systematically investigates the machinability of Hastelloy C276 under four sustainable lubrication and cooling environments—dry machining, minimum quantity lubrication (MQL), nano-enhanced MQL (NMQL), and cryogenic CO₂ (CCO₂). Experiments were designed using a Taguchi L16 orthogonal array, and the influence of cutting speed and feed rate on surface roughness, cutting force, tool wear, and cutting temperature was analysed using ANOVA. Compared to dry machining, cryogenic CO₂ cooling resulted in a reduction of surface roughness and cutting force by approximately 30–40%, along with a substantial decrease in tool wear and cutting temperature, whereas NMQL demonstrated moderate improvements due to enhanced lubrication at the tool–chip interface. ANOVA results revealed that feed rate and cutting speed were the most significant parameters, contributing up to 38.35% and 48.56% to variations in surface roughness and cutting temperature, respectively. To identify optimal machining conditions, Particle Swarm Optimization (PSO) and Teaching–Learning-Based Optimization (TLBO) algorithms were employed. Over 100 iterations, PSO achieved a higher optimization success rate of 83.6% compared to 79.1% for TLBO, while TLBO exhibited faster convergence with a computation time of 6.5 s against 9 s for PSO. The findings demonstrate that cryogenic CO₂-assisted machining combined with evolutionary optimization provides an effective and sustainable strategy for enhancing the machinability of Hastelloy C276.
Prediction of wear outcomes and mechanical characterization of innovative SiO2 incorporated aluminium matrix composites Abhijit Bhowmik, Raman Kumar, Kamal Sharma, Mahendrasinh R. Chauhan, Pardeep Singh Bains, Kamaljit Singh, Harjot Singh Gill, Valentin Romanovski, N. Ashok Scientific Reports, 2026 This study investigates the effect of SiO2 (silicon dioxide) powder as a reinforcement material in AA8011 aluminium matrix composites fabricated using the stir casting technique. The composites were produced with varying SiO2 contents of 0, 3, 6, and 9 wt% to evaluate their mechanical and tribological performance. The incorporation of SiO2 particles resulted in significant improvements in mechanical properties and wear resistance while maintaining a lightweight structure. The ultimate tensile strength increased from 156 MPa for the unreinforced alloy to 210 MPa for the composite containing 9 wt% SiO2, indicating substantial strengthening due to effective load transfer and grain refinement. Similarly, microhardness showed a noticeable improvement with increasing reinforcement content. However, the impact strength decreased by 11.42%, 22.85%, and 34.28% for composites containing 3 wt%, 6 wt%, and 9 wt% SiO2, respectively, compared with the base alloy. Wear tests conducted using a pin-on-disc apparatus demonstrated a considerable reduction in wear rate with increasing SiO2 reinforcement, particularly under higher loading conditions, due to the load-bearing capability and hardness of SiO2 particles. Microstructural analysis confirmed a relatively uniform distribution of reinforcement within the aluminium matrix, although minor particle agglomeration was observed at higher reinforcement levels. Overall, the results indicate that SiO2-reinforced AA8011 composites fabricated through stir casting offer improved mechanical strength and enhanced wear resistance, making them suitable for lightweight structural and tribological applications in automotive, aerospace, and engineering sectors.
A comprehensive study on tic additions and sliding speed effects governing wear in aluminium matrix composites Abhijit Bhowmik, Vignesh Packkirisamy, Raman Kumar, N. Beemkumar, Dhirendra Nath Thatoi, Ruby Pant, Parveen Kumar, Ankush Mehta, Nagaraj Ashok Scientific Reports, 2026 Particulate-reinforced aluminium matrix composites (PRAMCs) have gained significant attention for their high strength, good ductility, and excellent thermal conductivity, making them suitable for a wide range of modern engineering applications. In this study, micro-sized titanium carbide (TiC) particles were incorporated into an aluminium matrix through liquid-state stir casting, with TiC added at 0%, 3%, 6%, and 9% by weight. The investigation examined the combined influence of TiC content and sliding speed (0.75, 1.5, 2.25, and 3 m/s) on the wear behaviour of the composites when tested against an EN31 steel disc. All wear tests were performed under a constant load of 30 N over a sliding distance of 2000 m. The results show that increasing TiC content leads to a higher wear rate, whereas the coefficient of friction decreases correspondingly. Conversely, increasing sliding speed reduces the wear rate but results in a higher coefficient of friction. These findings demonstrate the coupled effects of TiC reinforcement and sliding velocity on the tribological performance of aluminium matrix composites and provide valuable insights for tailoring their behaviour in industrial applications.
Sound absorption properties of natural Bari bamboo composite Raja Kumar, Ankuran Saha, Nabarun Biswas, Gurbhej Singh, N Beemkumar, Ambati Vijay Kumar, Abhijit Bhowmik, Biplab Bhattacharjee Proceedings of the Institution of Mechanical Engineers Part L Journal of Materials Design and Applications, 2026
A systematic review of nanotechnology for electric vehicles battery Pulkit Kumar, Harpreet Kaur Channi, Atul Babbar, Raman Kumar, Javed Khan Bhutto, T M Yunus Khan, Abhijit Bhowmik, Abdul Razak, Anteneh Wogasso Wodajo International Journal of Low Carbon Technologies, 2024
Microstructure, mechanical and wear Behaviour of AL7075/SIC Aluminium matrix composite fabricated by stir casting Indian Journal of Engineering and Materials Sciences, 2021
Surface roughness and sem analysis of aluminium 6061 HOT-forged components using bio-lubricants R Rajendran, R Ramalingan, M Subramaniam, A Bhowmik Next Materials 12, 102270 , 2026 2026
Mechanical Performance of Diamond-Reinforced Zinc Composite Coatings for Heat Sink Applications: Experimental and GA–PSO Optimization S Awasthi, A Srivastava, L Kumar, A Goyal, A Bhowmik Journal of Bio-and Tribo-Corrosion 12 (2), 64 , 2026 2026
Machine learning-driven optimization of performance and emissions in a butanol/diesel CI engine K Siva Prasad, TR Vijaybabu, G Kiran Kumar, S Srinivasa Rao, VRK Raju, ... Scientific Reports , 2026 2026
Experimental investigation of ZnO nanoparticle–enhanced pongamia biodiesel for performance, combustion, emission, and sustainability assessment in a CI engine D Patel, SMF Azam, PSR Rao, JS Chohan, R Singh, S Samantaray, ... Scientific Reports , 2026 2026
Semi-Analytical and Hybrid Solution Methods for Nonlinear Ordinary and Partial Differential Equation Systems: Recent Advances and Applications VS Devi, K Saranya, R Kumar, R Makwana, M R, A Sharma, ... Archives of Computational Methods in Engineering, 1-34 , 2026 2026
Impact of Al 2 O 3 particles on the hardness, metallurgical and corrosion behaviour of Al 6061–10 wt. % Al 2 O 3 functionally graded composite SP Singh, K Yugandar, S Arunkumar, A Bhowmik, A Jemal Scientific Reports , 2026 2026
Tribological performance enhancement of SiO₂ reinforced AA8011 composites through grey fuzzy based optimization A Bhowmik, B Sen, D Patel, N Beemkumar, A Alhazaa, S Magibalan, ... Scientific Reports , 2026 2026
Sustainable Development of Layer-wise Graded Aluminium Composites Reinforced with Silicon Nitride: Microstructural, Hardness and Drilling Performance Analysis SP Singh, D Ananthapadmanaban, S Muralidharan, A Bhowmik, ... Materials Today Communications, 115368 , 2026 2026
Intelligent hybrid optimization of sustainable machining parameters for Inconel 718 using ANN driven evolutionary and swarm algorithms JS Chohan, R Yadav, KK Nagori, T Ramachandran, S Biswal, R Singh, ... Scientific Reports , 2026 2026
Intelligent optimization of micro-electrical discharge machining of aluminum nitride ceramics using nano abrasive zirconium oxide-enhanced biodegradable dielectric M Ravi, G Thangavel, M Raja, TG Sakthivel, N Ashok, A Bhowmik Scientific Reports , 2026 2026
Artificial Intelligence, Machine Learning, and Deep Learning for Solid Particle Erosion: Computational Modeling, Predictive Optimization, and Research Roadmap C Jindal, R Kumar, R Kumar, M Ghouse, MA Khan, A Bhowmik, V John, ... Archives of Computational Methods in Engineering, 1-43 , 2026 2026
Carbon nanotube reinforced soybean oil for sustainable machining of Monel 400: experimental investigation and FIS-based optimization M Abdullah, PS Bains, KK Nagori, T Ramachandran, S Juneja, H Sarangi, ... Scientific Reports , 2026 2026
Electrical discharge machining of Wire-LMD Inconel 718: Surface integrity and process optimization using a Taguchi–ANOVA approach R Koganti, PS Sundar, B Sen, A Bhowmik The International Journal of Advanced Manufacturing Technology, 1-15 , 2026 2026
Performance Benchmarking of Optimized Stacked Ensemble Frameworks in Blood Glucose Level (BGL) Prediction A Kharola, H Singh, J Singh, PS Pandey, N Kumar, A Kumar, A Bhowmik, ... Engineering Reports 8 (5), e70787 , 2026 2026
A data-driven approach for high-accuracy tool wear prediction in machining Hastelloy C276 M Abdullah, ACU Rao, T Ramachandran, S Biswal, SP Chaudhary, ... Scientific Reports , 2026 2026
Influence of Aging Duration on the Tribological Performance of LM25-Based SiC/TiO₂ Hybrid Composites SP Singh, DE Raja, M Sindhu, SP Selvan, R Subramaniyan, S Vijayan, ... Results in Engineering, 110674 , 2026 2026
Hydrogen as a low-temperature combustion HCCI engine fuel: a review VK Mishra, N Kumar, A Bhowmik, A Kumar, V John, K Kumar, P Samal Journal of Thermal Analysis and Calorimetry, 1-15 , 2026 2026
Experimental study of myristic acid–xylitol eutectic PCM in a wing-structured solar air collector for medium-temperature thermal storage KS Prasad, S Uppada, GK Kumar, KN Prasad, R Shasidhar, A Bhowmik, ... Scientific Reports , 2026 2026
Features of structural transformations in Cu-Fe-Ni alloy nanoparticles N Nepsha, S Roslyakov, K Savina, D Moskovskikh, A Kolosov, X Su, ... Next Materials 11, 101742 , 2026 2026 Citations: 1
Advancing sustainable machining of inconel 718 through nanoparticle-enhanced coconut oil and RSM–GA optimization O Almomani, V Rajput, ACU Rao, S Samantaray, N Patil, R Singh, ... Scientific Reports , 2026 2026
MOST CITED SCHOLAR PUBLICATIONS
Comparative Study of Microstructure, Physical and Mechanical Characterization of SiC/TiB 2 Reinforced Aluminium Matrix Composite A Bhowmik, D Dey, A Biswas Silicon 13 (6), 2003-2010 , 2021 2021 Citations: 117
Effect of SiC content on mechanical and tribological properties of Al2024-SiC composites D Dey, A Bhowmik, A Biswas Silicon 14 (1), 1-11 , 2022 2022 Citations: 88
Nanoparticle-enhanced biodiesel blends: A comprehensive review on improving engine performance and emissions V Modi, PB Rampure, A Babbar, R Kumar, M Nagaral, A Bhowmik, ... Materials Science for Energy Technologies 7, 257-273 , 2024 2024 Citations: 67
Application of minimum quantity GnP nanofluid and cryogenic LN2 in the machining of Hastelloy C276 B Sen, A Bhowmik Tribology International 194, 109509 , 2024 2024 Citations: 65
Casting of particle reinforced metal matrix composite by liquid state fabrication method: A review A Bhowmik, R Kumar, N Beemkumar, AV Kumar, G Singh, A Kulshreshta, ... Results in Engineering 24, 103152 , 2024 2024 Citations: 62
Development and wear resistivity performance of SiC and TiB2 particles reinforced novel aluminium matrix composites A Bhowmik, B Sen, N Beemkumar, JS Chohan, PS Bains, G Singh, ... Results in Engineering 24, 102981 , 2024 2024 Citations: 62
Recent advances in graphene-enabled materials for photovoltaic applications: a comprehensive review P Jain, RS Rajput, S Kumar, A Sharma, A Jain, BJ Bora, P Sharma, ... ACS omega 9 (11), 12403-12425 , 2024 2024 Citations: 58
Characteristics Study of Physical, Mechanical and Tribological Behaviour of SiC/TiB 2 Dispersed Aluminium Matrix Composite A Bhowmik, D Dey, A Biswas Silicon 14 (3), 1133-1146 , 2022 2022 Citations: 56
Prediction of specific cutting energy consumption in eco-benign lubricating environment for biomedical industry applications: Exploring efficacy of GEP, ANN, and RSM models B Sen, A Bhowmik, C Prakash, MI Ammarullah AIP advances 14 (8) , 2024 2024 Citations: 51
Exploring the role of computer vision in product design and development: a comprehensive review L Yang, R Kumar, R Kaur, A Babbar, GS Makhanshahi, A Singh, R Kumar, ... International Journal on Interactive Design and Manufacturing (IJIDeM) 18 (6 … , 2024 2024 Citations: 49
Influence of TiB2 addition on friction and wear behaviour of Al2024-TiB2 ex-situ composites DEY Dipankar, A Bhowmik, A Biswas Transactions of Nonferrous Metals Society of China 31 (5), 1249-1261 , 2021 2021 Citations: 43
Tribological behaviour of aluminium-titanium diboride (Al7075-TiB2) metal matrix composites prepared by stir casting process A Bhowmik, D Dey, A Biswas Materials Today: Proceedings 26, 2000-2004 , 2020 2020 Citations: 43
Sustainable machining of superalloy in minimum quantity lubrication environment: leveraging GEP-PSO hybrid optimization algorithm B Sen, S Debnath, A Bhowmik The International Journal of Advanced Manufacturing Technology 130 (9), 4575 … , 2024 2024 Citations: 42
Optimizing wire-cut EDM parameters through evolutionary algorithm: a study for improving cost efficiency in turbo-machinery manufacturing B Sen, A Dasgupta, A Bhowmik International Journal on Interactive Design and Manufacturing (IJIDeM) 19 (3 … , 2025 2025 Citations: 41
Characterization of physical and mechanical properties of aluminium based composites reinforced with titanium diboride particulates D Dey, A Bhowmik, A Biswas Journal of Composite Materials 55 (14), 1979-1991 , 2021 2021 Citations: 41
Exploring cryo-MQL medium for hard machining of hastelloy C276: a multi-objective optimization approach B Sen, A Bhowmik, N Rachchh, N Patil, A Khatibi, R Kumar International Journal on Interactive Design and Manufacturing (IJIDeM) 19 (7 … , 2025 2025 Citations: 40
Alumina-enriched sunflower bio-oil in machining of Hastelloy C-276: a fuzzy Mamdani model-aided sustainable manufacturing paradigm B Sen, A Bhowmik, G Singh, V Mishra, S Debnath, R Zairov, ... Scientific Reports 14 (1), 29194 , 2024 2024 Citations: 40
Evaluation of constitutive equations for modeling and characterization of microstructure during hot deformation of sintered Al–Zn–Mg alloy K Harikrishna, A Bhowmik, MJ Davidson, R Kumar, AE Anqi, AA Rajhi, ... Journal of Materials Research and Technology 28, 1523-1537 , 2024 2024 Citations: 40
Analysis of physical, mechanical and tribological behavior of Al7075-fly ash composite for lightweight applications A Bhowmik, R Kumar, A Babbar, V Romanovski, S Roy, L Patnaik, ... International Journal on Interactive Design and Manufacturing (IJIDeM) 18 (6 … , 2024 2024 Citations: 39
Investigation on wear behaviour of Al7075-SiC metal matrix composites prepared by stir casting A Bhowmik, D Chakraborty, D Dey, A Biswas Materials today: proceedings 26, 2992-2995 , 2020 2020 Citations: 35