Devarajan Ramasamy

Currently, Assoc Prof. Ir. Ts. Dr. Devarajan is researcher and consultant at Faculty of Mechanical and Automotive Engineering Technology in Universiti Malaysia Pahang. He graduated from Universiti Sains Malaysia with a PHD in 2015 and University Teknologi Malaysia with Master of Engineering in 2006. After his first degree in UTM 2002, he worked at Kolej WIT (M) Sdn. Bhd. for about 2 year with last position as Lecturer of Mechanical Engineering. He continued his studies to master’s and later joined Scott and English as Production Engineer in 2005. As a franchise holder representative for TATAMOTORS LTE, he managed production of commercial vehicles in Scott and English (DRB-HICOM). He has shown vast interest in Thermofluid, Vehicle Technology, Nanotechnology, Engine Testing and Alternative Fuel research area. At present, involve in an internal and international research grants with research actively involved in CNG fuel, finite element, computational fluid mechanics and advanced material

EDUCATION

PHD in Mechanical Engineering

RESEARCH, TEACHING, or OTHER INTERESTS

Engineering, Automotive Engineering, Mechanical Engineering, Materials Science

Scopus Publications

Characterization and machine learning analysis of hybrid alumina-copper oxide nanoparticles in therminol 55 for medium temperature heat transfer fluid
G. Kadirgama, D. Ramasamy, K. Kadirgama, L. Samylingam, Navid Aslfattahi, Mohammad Reza Chalak Qazani, Chee Kuang Kok, Talal Yusaf, and Michal Schmirler
Springer Science and Business Media LLC
Abstract Efficient heat dissipation is crucial for various industrial and technological applications, ensuring system reliability and performance. Advanced thermal management systems rely on materials with superior thermal conductivity and stability for effective heat transfer. This study investigates the thermal conductivity, viscosity, and stability of hybrid Al2O3-CuO nanoparticles dispersed in Therminol 55, a medium-temperature heat transfer fluid. The nanofluid formulations were prepared with CuO-Al2O3 mass ratios of 10:90, 20:80, and 30:70 and tested at nanoparticle concentrations ranging from 0.1 wt% to 1.0 wt%. Experimental results indicate that the hybrid nanofluids exhibit enhanced thermal conductivity, with a maximum improvement of 32.82% at 1.0 wt% concentration, compared to the base fluid. However, viscosity increases with nanoparticle loading, requiring careful optimization for practical applications. To further analyze and predict thermal conductivity, a Type-2 Fuzzy Neural Network (T2FNN) was employed, demonstrating a correlation coefficient of 96.892%, ensuring high predictive accuracy. The integration of machine learning enables efficient modeling of complex thermal behavior, reducing experimental costs and facilitating optimization. These findings provide insights into the potential application of hybrid nanofluids in solar thermal systems, heat exchangers, and industrial cooling applications.


Multiplane vs. Single-Plane FDM Printing: A Study on Mechanical and Physical Properties of the PET-G
Jayabharty Mogan, Wan Sharuzi Wan Harun, Mahendran Samykano, Kumaran Kadirgama, Mohd Rizal Alkahari, Devarajan Ramasamy, and Faiz Ahmad
Akademia Baru Publishing
The dynamic landscape of additive manufacturing is rapidly evolving, with the fusion of fused deposition modelling (FDM) and multiplane printing emerging as a transformative technique for creating intricate 3D PET-G components. Utilizing a cutting-edge gantry-style FDM apparatus, this comprehensive research endeavour centred on the fabrication and subsequent meticulous evaluation of multiplane samples. These were contrasted against their single-plane counterparts, focusing on pivotal metrics such as tensile strength, flexural resilience, and inherent material density. The findings were enlightening: Multiplane samples exhibited marked superiority in tensile attributes, whereas the single-plane samples displayed pronounced advantages in flexural strength and overall density. Such distinct variations offer profound insights into the overarching influence of multiplane printing techniques within FDM processes. This investigative foray not only underscores the vast potentialities of multiplane printing but also signals its instrumental role in heralding future innovations within the expansive and multifaceted domain of additive manufacturing.


Thermal uniformity analysis of a hybrid battery pack using integrated phase change material, metal foam, and counterflow minichannels
Hasan Najafi Khaboshan, Kumaran Kadirgama, Devarajan Ramasamy, Virendra Talele, Peng Zhao, Harsh Tyagi, and Nenad Miljkovic
Elsevier BV



Artificial Intelligence Revolutionising the Automotive Sector: A Comprehensive Review of Current Insights, Challenges, and Future Scope
Md Naeem Hossain, Md. Abdur Rahim, Md Mustafizur Rahman, and Devarajan Ramasamy
Tech Science Press
: The automotive sector is crucial in modern society, facilitating essential transportation needs across personal, commercial, and logistical domains while significantly contributing to national economic development and employment generation. The transformative impact of Artificial Intelligence (AI) has revolutionised multiple facets of the automotive industry, encompassing intelligent manufacturing processes, diagnostic systems, control mechanisms, supply chain operations, customer service platforms, and traffic management solutions. While extensive research exists on the above aspects of AI applications in automotive contexts, there is a compelling need to synthesise this knowledge comprehensively to guide and inspire future research. This review introduces a novel taxonomic framework that provides a holistic perspective on AI integration into the automotive sector, focusing on next-generation AI methods and their critical implementation aspects. Additionally, the proposed conceptual framework for real-time condition monitoring of electric vehicle subsystems delivers actionable maintenance recommendations to stakeholders, addressing a critical gap in the field. The review highlights that AI has significantly expedited the development of autonomous vehicles regarding navigation, decision-making, and safety features through the use of advanced algorithms and deep learning structures. Furthermore, it identifies advanced driver assistance systems, vehicle health monitoring, and predictive maintenance as the most impactful AI applications, transforming operational safety and maintenance efficiency in modern automotive technologies. The work is beneficial to understanding the various use cases of AI in the different automotive domains, where AI maintains a state-of-the-art for sector-specific applications, providing a strong foundation for meeting Industry 4.0 needs and encouraging AI use among more nascent industry segments. The current work is intended to consolidate previous works while shedding some light on future research directions in promoting further growth of AI-based innovations in the scope of automotive applications.


Artificial neural network for performance modelling of shape memory alloy
Sivaraos, Rakesh Kumar Phanden, K. Y. Sara Lee, E. J. Abdullah, K. Kumaran, A. S. M. Al-Obaidi, and R. Devarajan
Springer Science and Business Media LLC
Abstract In recent years, significant strides in technological advancement have revolutionized our lifestyles, driving a surge in demand for multifunctional and intelligent materials. Among these materials, Shape Memory Alloy (SMA) stands out for its unique ability to memorize and revert to its original shape through phase transformation. Despite its remarkable properties, SMAs exhibit a minor limitation in accurately retaining their original shape or length. Furthermore, there is a notable dearth of information regarding the modelling of SMA behaviour with high precision. This study endeavors to address these challenges by integrating experimental data with neural network modelling to comprehensively examine SMA behaviour for mechanical applications. Leveraging an experimental dataset, this research employs feedforward backpropagation neural network (BPNN) modelling to forecast the strain recovery of SMA Nitinol alloy. The model aims to predict the recovery strain of SMA by utilizing three input parameters: temperature conditional, number of coils, and initial length. Remarkably, the achieved error rates of 0.29%, 0.80%, and 9.20% for various strain measurements significantly undercut the commonly accepted error threshold of 10% for nonlinear data predictions in SMA behaviour. The final results underscore the high prediction accuracy of the Artificial Neural Network (ANN), offering promising prospects for SMA applications involving temperature-strain interactions and enhancing engineering design.


Liquid immersion cooling with enhanced Al<inf>2</inf>O<inf>3</inf> nanofluid for large-format prismatic battery pack: numerical and statistical investigation
Elnaz Yousefi, Virendra Talele, Uğur Morali, Dhananjay Mishra, Devarajan Ramasamy, Kumaran Kadirgama, Hasan Najafi, Sarthak Kanthale, and Satyam Panchal
Springer Science and Business Media LLC



Performance evaluation of various training functions using ANN to predict the thermal conductivity of EG/water-based GNP/CNC hybrid nanofluid for heat transfer application
Md. Munirul Hasan, Md Mustafizur Rahman, Suraya Abu Bakar, Muhammad Nomani Kabir, Devarajan Ramasamy, and A. H. M. Saifullah Sadi
Springer Science and Business Media LLC



Thermal and Flow Characteristics of Alumina Nanofluids in Microfluidic Systems: A Low-Concentration Study
Lingenthiran Samylingam, Navid Aslfattahi, Kumaran Kadirgama, Devarajan Ramasamy, Kuang Kok Chee, Norazlianie Sazali, Wan Sharuzi Wan Harun, Nor Atiqah Zolpakar, and Mohd Fairusham Ghazali
Akademia Baru Publishing
Microfluidic technologies and nanofluids represent a synergistic combination with significant potential for enhancing heat transfer and thermal management applications. This study investigates the thermal and flow characteristics of a 0.001 wt.% alumina (Al₂O₃)-water nanofluid within a custom-designed serpentine microfluidic channel. The nanofluid was prepared and characterized for its thermal conductivity, viscosity, specific heat, and density. Experimental microfluidic studies, supplemented by numerical simulations, were conducted to evaluate the fluid's behavior under controlled conditions. Results indicated a slight increase in thermal conductivity for the Al₂O₃ nanofluid compared to pure water, with increments ranging from 0.16% at 20°C to 0.30% at 80°C, attributed to enhanced Brownian motion of the nanoparticles. Viscosity measurements revealed marginal increases, suggesting minimal impact on fluid flow dynamics. The microfluidic experiments demonstrated a consistent pressure gradient and laminar flow regime, essential for precise control and efficient thermal management. Temperature contours showed effective heat dissipation, with a steady thermal gradient from the inlet to the outlet. The study concludes that low-concentration Al₂O₃ nanofluids can enhance thermal performance in microfluidic systems without significantly affecting flow characteristics, making them suitable for applications requiring efficient heat dissipation, such as electronic cooling and chemical reactions. These findings provide a foundation for future research into higher nanoparticle concentrations and different base fluids, aimed at optimizing the thermal and flow properties of nanofluids in microfluidic environments. The integration of nanofluids with microfluidic technologies holds promise for advancing the performance and reliability of next-generation thermal management systems.


Deep learning-based vehicular engine health monitoring system utilising a hybrid convolutional neural network/bidirectional gated recurrent unit
Md. Abdur Rahim, Md. Mustafizur Rahman, Md. Shofiqul Islam, Abu Jafar Md. Muzahid, Md. Arafatur Rahman, and Devarajan Ramasamy
Elsevier BV



Unveiling the future: A simulation and analysis of hydrogen production using 1kW electrolyzer with MATLAB approach
Yaw Chong Tak, Johnny Koh Siaw Paw, K. Kadirgama, D. Ramasamy, Oday A. Ahmed, Jagadeesh Pasupuleti, F. Benedict, L. Samylingam, and Chee Kuang Kok
Elsevier BV



Rice Bran Oil as Emerging Green Fuels: Exploration on Combustion Behaviours of Single Cylinder Diesel Engine (Light-Duty Engine)
Norhafana Mohamed, Che Ku Ihsan, Muhamad Mat Noor, Abdul Aziz Hairuddin, Teuku Meurah Indra Mahlia, Kumaran Kadirgama, Devarajan Ramasamy, Mahendran Samykano, Mohd Fairusham Ghazali, and Md Mustafizur Rahman
Akademia Baru Publishing
In the current work, an experiment was conducted to examine the combustion properties of a single cylinder compression ignition direct ignition engine fuelled with rice bran oil at different engine loads. The investigation focused on the analysis of cylinder pressure and exhaust gas temperature as key factors in combustion. The fuel blends utilized in this study consist of various proportions of diesel and rice bran oil, including 100% pure diesel (RBO00), a blend of 25% rice bran oil and 75% pure diesel (RBO25), a blend of 50% rice bran oil and 50% pure diesel (RBO50), a blend of 75% rice bran oil and 25% pure diesel (RBO75), and 100% rice bran oil (RBO100). Comparisons are made between the results of an experiment using rice bran oil (RBO25, RBO50, RBO75, and RBO100) and a diesel engine (RBO00). RBO00 exhibits a greater heat output per unit mass compared to RBO25, RBO50, RBO75, and RBO100 blends because of the highest value of calorific value (CV) among others blends. Consequently, RBO00 demonstrated a higher measurement of exhaust gas temperature (EGT). One further contributing factor was the increased exhaust gas temperature (EGT), which led to an extended ignition delay, resulting in a lengthier fuel combustion process and the egress of combustion gas from the combustion chamber at higher temperatures. RBO100 achieved the highest cylinder pressure in both 50 % and 100 % engine load settings. The RBO100 blends fuel successfully achieved the optimal cylinder pressure in both 50 % and 100 % engine load conditions. The cylinder pressure for RBO00 (pure diesel) was the lowest at both half and full loads. The observed decrease in peak pressure can be attributed to the decreased cetane number (CN) and oxygen concentration found in RBO00 in comparison to the mixed fuels of RBOs. This will affect the completion of combustion such as wear and tear for the cylinder and piston. Under both 50 % and 100 % engine load condition, the cylinder pressure for RBO00 (pure diesel) was the lowest. In summary, rice bran oil showed superior combustion behaviour compared to pure diesel, and the mixture blends RBO75 and RBO100 can be thought of as ideal in terms of exhaust gas temperature and cylinder pressure.


Hybrid CNC–MXene Nanolubricant for Tribological Application: Characterization, Prediction, and Optimization of Thermophysical Properties Evaluation
Sakinah Muhamad Hisham, Norazlianie Sazali, Kumaran Kadirgama, Devarajan Ramasamy, Mohd Kamal Kamarulzaman, Lingenthiran Samylingam, Navid Aslfattahi, and Chee Kuang Kok
MDPI AG
In the present work, hybrid Cellulose Nanocrystal–MXene (CNC–MXene) nanolubricants were prepared via a two-step method and investigated as potential heat-transfer hybrid nanofluids for the first time. CNC–MXene nanolubricants were synthesized via a two-step method by varying the weight percentage of CNC–MXene nanoparticles (ranging from 0.01 to 0.05 wt%) and characterized using Fourier-Transform Infrared Spectroscopy and TGA (Thermogravimetric Analysis). Response surface methodology (RSM) was used in conjunction with the miscellaneous design model to identify prediction models for the thermophysical properties of the hybrid CNC–MXene nanolubricant. Minitab 18 statistical analysis software and Response Surface Methodology (RSM) based on Central Composite Design (CCD) were utilized to generate an empirical mathematical model investigating the effect of concentration and temperature. The analysis of variance (ANOVA) results indicated significant contributions from the type of nanolubricant (p &lt; 0.001) and the quadratic effect of temperature (p &lt; 0.001), highlighting non-linear interactions that affect viscosity and thermal conductivity. The findings showed that the predicted values closely matched the experimental results, with a percentage of absolute error below 9%, confirming the reliability of the optimization models. Additionally, the models could predict more than 85% of the nanolubricant output variations, indicating high model accuracy. The optimization analysis identified optimal conditions for maximizing both dynamic viscosity and thermal conductivity. The predicted optimal values (17.0685 for dynamic viscosity and 0.3317 for thermal conductivity) were achieved at 30 °C and a 0.01% concentration, with a composite desirability of 1. The findings of the percentage of absolute error (POAE) reveal that the model can precisely predict the optimum experimental parameters. This study contributes to the growing field of advanced nanolubricants by providing insights into the synergistic effects of CNC and MXene in enhancing thermophysical properties. The developed models and optimization techniques offer valuable tools for tailoring nanolubricant formulations to specific tribological applications, potentially leading to improved efficiency and durability in various industrial settings.


Underlying Developments in Hydrogen Production Technologies: Economic Aspects and Existent Challenges
L. Samylingam, Navid Aslfattahi, Chee Kuang Kok, K. Kadirgama, Michal Schmirler, T. Yusaf, D. Ramasamy, and M. F. Ghazali
Springer Science and Business Media LLC



X to y axes industrial laser cutting machine quality investigation
Sivaraos, Theebenraj, M. S. Salleh, R. Dharsyanth, M. A. M. Ali, K. Kadirgama, S. Pujari, D. Ramasamy, S. Maidin, U. K. Vatesh,et al.
AIP Publishing



Analysis of treated magnetic repulsion dynamics and their implications for future engineering applications
Sivaraos, K. P. Prasath, M. S. Salleh, R. Dharsyanth, M. A. M. Ali, K. Kadirgama, S. Pujari, D. Ramasamy, U. K. Vatesh, S. Maidin,et al.
AIP Publishing



Microscale Thermal Management: A Review of Nanofluid Applications in Microfluidic Channels
Lingenthiran Samylingam, Navid Aslfattahi, Kumaran Kadirgama, Devarajan Ramasamy, Norazlianie Sazali, Wan Sharuzi Wan Harun, Chee Kuang Kok, Nor Atiqah Zolpakar, and Mohd Fairusham Ghazali
Engineering, Technology & Applied Science Research
This critical review study focuses on the integration of nanofluids with microfluidic channels. This emerging field, which combines nanotechnology and microfluidics, has the potential to transform the control of temperatures and monitoring completely. Nanofluids, which are fluids containing nanoparticles like metals or oxides, greatly improve the heat management capabilities of base fluids. These materials are highly efficient in transferring and conducting heat, making them ideal for applications such as cooling electronics and medical diagnostics. The addition of nanofluids to microfluidic routes, typically measured in micrometers, greatly simplifies fluid flow and heat transfer regulation. The article includes several research studies demonstrating how nanofluids enhance the performance of microfluidic systems compared to conventional fluids. The benefits are examined, including the potential for reduced size and increased energy efficiency of heat exchanges and cooling systems. As a result, these technologies are better suited for implementation in the healthcare and industry sectors.


Review of Ti<inf>3</inf> C<inf>2</inf> T<inf>x</inf> MXene Nanofluids: Synthesis, Characterization, and Applications
Ilancheliyan Samylingam, Kumaran Kadirgama, Lingenthiran Samylingam, Navid Aslfattahi, Devarajan Ramasamy, Norazlianie Sazali, Wan Sharuzi Wan Harun, and Chee Kuang Kok
Engineering, Technology & Applied Science Research
MXene-based nanofluids are important because of their thermal and rheological properties, influencing scientific and industrial applications. MXenes, made of titanium carbides and nitrides, are investigated for nanofluid enhancement. This review covers MXene nanofluid creation, characterization, and application. To produce nanoscale MXene particles, two-dimensional materials are dissolved and dispersed in a base fluid. The stability and efficacy of MXene nanofluids depend on production methods, such as chemical exfoliation, electrochemical etching, and mechanical delamination. Improved heat transfer coefficients and thermal conductivity from MXene nanofluids help resolve heat transfer, energy efficiency, and thermal control problems. This extensive review also addresses long-term safety and the necessity for standardized characterization methodologies, helping researchers optimize MXene-based nanofluids in many technological fields


Enhancing stability and tribological applications using hybrid nanocellulose-copper (II) oxide (CNC-CuO) nanolubricant: An approach towards environmental sustainability
Sakinah Hisham, K. Kadirgama, Jasem Ghanem Alotaibi, Ayedh Eid Alajmi, D. Ramasamy, Norazlianie Sazali, Mohd Kamal Kamarulzaman, T. Yusaf, L. Samylingam, Navid Aslfattahi,et al.
Elsevier BV



A Comprehensive Review on Tribological Behaviour of Hybrid Nanocellulose-CuO as Nanolubricant for Piston Ring Cylinder Liner Application
Sakinah Muhamad Hisham, Norazlianie Sazali, Kumaran Kadirgama, and Devarajan Ramasamy
Akademia Baru Publishing
Friction coefficient and wear rate are crucial performance for the development of nanolubricants, which are of great significance for realizing energy conservation and prolonging service life of mechanical components. Herein, this review systematically describes the progress on nanocellulose (CNC) and Copper (II) oxide (CuO) as effective nanoparticles for developments of nanolubricant as oil additives for improving the anti-friction and wear resistant for piston ring-cylinder liner contact. Additionally, we point out several problems existing in the applications of CuO and CNC additives propose the possible solutions. Finally, the research prospects of CNC-CuO in the field of tribology are prospected.


Comparative Performance Evaluation Of PID And Fuzzy PID Controller Using Genetic Algorithm For A Robotic Manipulator System
Aditi Saxena, Kamal Sharma, K. Kadirgama, R. Devarajan, and M. M. Noor
AIP Publishing



Design of NPID Controller for Nonlinear Trajectory Tracking of Robotic 3DPrinter System Manipulator
Aditi Saxena, Kamal Sharma, K. Kadirgama, R. Devarajan, and M. M. Noor
AIP Publishing



Thermal Stability and Performance Evaluation of Hitec Molten Salt for High-Temperature Energy Storage Applications
Subbarama Kousik Suraparaju, Mahendran Samykano, Satesh Namasivayam, K. Kadirgama, and D. Ramasamy
EDP Sciences
The quest for advanced materials in thermal energy storage (TES) has become paramount in a world grappling with pressing demands for sustainable and reliable energy solutions. Among these materials, molten salts have emerged as up-and-coming contenders, owing to their exceptional thermal properties and wide operational temperature ranges. HITEC, a eutectic blend of sodium nitrate, sodium nitrite, and potassium nitrate, distinguishes itself as a superior choice due to its unique amalgamation of favorable thermal characteristics. This comprehensive review delves into the thermal properties of HITEC molten salt and its manifold applications in thermal energy storage, illuminating its potential as a pivotal element in addressing contemporary global challenges. The review examines HITEC's specific heat capacity, thermal conductivity, and thermal stability, presenting critical insights into its efficacy as a TES medium. Such comprehension fosters the advancement of Sustainable Development Goal 7. The article explores strides made in HITEC-based TES systems, underscoring inventive engineering approaches and burgeoning technologies that bolster progress towards Sustainable Development Goal 9. Furthermore, the article discusses challenges associated with HITEC molten salts, such as corrosion and material compatibility issues, and investigates ongoing research efforts to overcome these limitations. A comparative evaluation of HITEC with other molten salt mixtures elucidates its competitive advantages. This review consolidates knowledge about HITEC molten salt for thermal energy storage applications, providing valuable perspectives for researchers, engineers, and policymakers dedicated to advancing sustainable energy technologies. The review underscores the pivotal role of HITEC molten salt in advancing thermal energy storage technologies, directly influencing the achievement of several SDGs.


Thermal Properties of Engine Oils through the Integration of Graphene Nanoparticles: A Greener Approach for Sustainable Mechanical Systems
G. Kadirgama, Muhammad A.M.A. Lee, D. Ramasamy, K. Kadirgama, M. Samykano, and T. Yusaf
EDP Sciences
Tribology is a high demand mechanical system with friction and wear. Mechanical systems lose efficiency as a result. One answer for this issue is to utilize an oil that can limit contact and wear, bringing about improved effectiveness. The advancement of effective lubricating added substances for tribological properties improvement and improved thermal conductivity has gotten huge modern and scholarly consideration. By and large, nano-sized particles scattered in lubricants, referred to as nano-based lubricant, are utilized in mechanical structures to lessen heat and forces of frictions. Moreover, new guidelines will empower the utilization of greener lubrication advancements in oils. To resolve this issue, lubricants should satisfy guidelines while able to give exceptional oil characteristics. As another green material, this research will investigate the dissolving of Graphene nanoparticles in lubricants. The objective of this study is to perceive what Graphene added 10W40 motor oil means for the thermal properties and tribological characteristics. Graphene, which was added to 10W40 lubricant, was used to study the best design. Graphene nanoparticles were distributed in baseline engine oil in a two-step process. In the preparation of Graphene-based motor oil with a low volume mixture in the scope of 0.01% to 0.07% was used. Thermal conductivity and viscosity are estimated for all volume mixtures. Testing uncovered that Graphene added 10W40 motor oil were steady all through the review, with very little deposits in the following 30 days. The thermal conductivity of Graphene in SAE 40 motor oil expanded as the volume mixture is added.


Energizing the Thermal Conductivity and Optical Performance of Salt Hydrate Phase Change Material Using Copper (II) Oxide Nano Additives for Sustainable Thermal Energy Storage
Reji Kumar Rajamony, Mahendran Samykano, Subbarama Kousik Suraparaju, A.G.N. Sofiah, Satesh Namasivayam, K. Rajkumar, Kumaran Kadirgama, and Devarajan Ramasamy
EDP Sciences
Due to intermittent nature of solar energy, scientists and researchers are working to develop thermal energy storage (TES) systems for effectively use the solar energy. One promising avenue involves utilizing phase change materials (PCMs), but primary challenge lies in their limited thermal conductivity, which results in slower heat transfer rate and lower thermal energy storage density. The present research work demonstrates, to develop and explore a PCM composite by embedding salt hydrate and coper (II) oxide to enhance the heat transfer mechanism for potential utilization of TES material. The optical behavior, and thermal conductivity were analyzed by using Ultraviolet visible spectrum, and thermal property analyzer. The developed copper oxide dispersed PCM composite displayed the thermal conductivity was energized up to 71.5 % without affecting the other properties. Also, the optical absorptance was remarkably enhanced and the transmittance reduced to 87 %. Increasing the concentration of copper oxide nanoparticles in the salt hydrate PCM improves the optical absorptivity and heat conductivity. With these extraordinary abilities the nanocomposite could play a significant role in progress of sustainable TES with significance to contribute towards sustainable development goal of affordable and clean energy and climate change.


Enhancing Lubrication Efficiency and Wear Resistance in Mechanical Systems through the Application of Nanofluids: A Comprehensive Review

RECENT SCHOLAR PUBLICATIONS

Characterization and machine learning analysis of hybrid alumina-copper oxide nanoparticles in therminol 55 for medium temperature heat transfer fluid
G Kadirgama, D Ramasamy, K Kadirgama, L Samylingam, N Aslfattahi, ...
Scientific Reports 15 (1), 8383 2025



Artificial Intelligence Revolutionising the Automotive Sector: A Comprehensive Review of Current Insights, Challenges, and Future Scope.
MN Hossain, MA Rahim, MM Rahman, D Ramasamy
Computers, Materials & Continua 82 (3) 2025



Liquid immersion cooling with enhanced Al2O3 nanofluid for large-format prismatic battery pack: numerical and statistical investigation
E Yousefi, V Talele, U Morali, D Mishra, D Ramasamy, K Kadirgama, ...
Journal of Thermal Analysis and Calorimetry, 1-19 2025



Thermal uniformity analysis of a hybrid battery pack using integrated phase change material, metal foam, and counterflow minichannels
HN Khaboshan, K Kadirgama, D Ramasamy, V Talele, P Zhao, H Tyagi, ...
Applied Thermal Engineering 259, 124910 2025



Performance evaluation of various training functions using ANN to predict the thermal conductivity of EG/water-based GNP/CNC hybrid nanofluid for heat transfer application
MM Hasan, MM Rahman, S Abu Bakar, MN Kabir, D Ramasamy, ...
Journal of Thermal Analysis and Calorimetry, 1-26 2025



Prediction of Battery Thermal Management System Performance by AI Method
D Ramasamy, S Subramaniam, MDZ Bin Ezani
The Nexus of Sustainability and Energy Technology Journal 1 (1), 7-17 2025



Investigation of Heat Transfer Rate in Automotive Radiator with Graphene Nanofluid with Simulation
M Aziz, D Ramasamy, R Kumaresan, S Subramaniam
The Nexus of Sustainability and Energy Technology Journal 1 (1), 26-39 2025



Sustainable Viscosity Prediction of Hybrid Alumina-Copper Oxide Nanofluid for Green Heat Transfer Applications Using Adaptive Neuro-Fuzzy Inference System (ANFIS)
MRC Qazani, G Kadirgama, N Aslfattahi, D Ramasamy, L Samylingam, ...
The Nexus of Sustainability and Energy Technology Journal 1 (1), 40-55 2025



Deep learning-based vehicular engine health monitoring system utilising a hybrid convolutional neural network/bidirectional gated recurrent unit
MA Rahim, MM Rahman, MS Islam, AJM Muzahid, MA Rahman, ...
Expert Systems with Applications 257, 125080 2024



Unveiling the future: A simulation and analysis of hydrogen production using 1kW electrolyzer with MATLAB approach
YC Tak, JKS Paw, K Kadirgama, D Ramasamy, OA Ahmed, J Pasupuleti, ...
Results in Engineering 24, 103460 2024



Artificial Intelligence-Driven Vehicle Fault Diagnosis to Revolutionize Automotive Maintenance: A Review.
MN Hossain, MM Rahman, D Ramasamy
CMES-Computer Modeling in Engineering & Sciences 141 (2) 2024



Hybrid CNC–MXene Nanolubricant for Tribological Application: Characterization, Prediction, and Optimization of Thermophysical Properties Evaluation.
SM Hisham, N Sazali, K Kadirgama, D Ramasamy, MK Kamarulzaman, ...
Processes 12 (10) 2024



Underlying developments in hydrogen production technologies: economic aspects and existent challenges
L Samylingam, N Aslfattahi, CK Kok, K Kadirgama, M Schmirler, T Yusaf, ...
Korean Journal of Chemical Engineering 41 (11), 2961-2984 2024



Analysis of treated magnetic repulsion dynamics and their implications for future engineering applications
S Sivaraos, KP Prasath, MS Salleh, R Dharsyanth, MAM Ali, K Kadirgama, ...
AIP Conference Proceedings 3161 (1) 2024



X to Y axes industrial laser cutting machine quality investigation
S Sivaraos, T Theebenraj, MS Salleh, R Dharsyanth, MAM Ali, ...
AIP Conference Proceedings 3161 (1) 2024



Microscale Thermal Management: A Review of Nanofluid Applications in Microfluidic Channels
L Samylingam, N Aslfattahi, K Kadirgama, D Ramasamy, N Sazali, ...
Engineering, Technology & Applied Science Research 14 (4), 15575-15580 2024



Advancements, challenges, and implications for navigating the autonomous vehicle revolution
MN Hossain, MM Rahman, D Ramasamy, K Kadirgama, MM Noor
Journal of Mechanical Engineering and Sciences, 10077-10093 2024



Review of Ti3C2Tx MXene Nanofluids: Synthesis, Characterization, and Applications
I Samylingam, K Kadirgama, L Samylingam, N Aslfattahi, D Ramasamy, ...
Engineering, Technology & Applied Science Research 14 (3), 14708-14712 2024



Enhancing stability and tribological applications using hybrid nanocellulose-copper (II) oxide (CNC-CuO) nanolubricant: An approach towards environmental sustainability
S Hisham, K Kadirgama, JG Alotaibi, AE Alajmi, D Ramasamy, N Sazali, ...
Tribology International 194, 109506 2024



Artificial neural network modeling for predicting thermal conductivity of EG/water-based CNC nanofluid for engine cooling using different activation functions
MM Hasan, MM Rahman, MS Islam
Water-Based CNC Nanofluid for Engine Cooling Using Different Activation 2024

MOST CITED SCHOLAR PUBLICATIONS

Evolution of IoT-enabled connectivity and applications in automotive industry: A review
MA Rahim, MA Rahman, MM Rahman, AT Asyhari, MZA Bhuiyan, ...
Vehicular Communications 27, 100285 2021
Citations: 215



Sustainable hydrogen energy in aviation–A narrative review
T Yusaf, ASF Mahamude, K Kadirgama, D Ramasamy, K Farhana, ...
international journal of hydrogen energy 52, 1026-1045 2024
Citations: 168



Ultrasonication an intensifying tool for preparation of stable nanofluids and study the time influence on distinct properties of graphene nanofluids–A systematic overview
M Sandhya, D Ramasamy, K Sudhakar, K Kadirgama, WSW Harun
Ultrasonics sonochemistry 73, 105479 2021
Citations: 154



Improvement in the performance of solar collectors with nanofluids—A state-of-the-art review
K Farhana, K Kadirgama, MM Rahman, D Ramasamy, MM Noor, G Najafi, ...
Nano-Structures & Nano-Objects 18, 100276 2019
Citations: 154



Hydrogen energy demand growth prediction and assessment (2021–2050) using a system thinking and system dynamics approach
T Yusaf, M Laimon, W Alrefae, K Kadirgama, HA Dhahad, D Ramasamy, ...
Applied Sciences 12 (2), 781 2022
Citations: 121



Study on friction and wear of Cellulose Nanocrystal (CNC) nanoparticle as lubricating additive in engine oil
NW Awang, D Ramasamy, K Kadirgama, G Najafi, NAC Sidik
International Journal of Heat and Mass Transfer 131, 1196-1204 2019
Citations: 111



Sustainable aviation—Hydrogen is the future
T Yusaf, L Fernandes, AR Abu Talib, YSM Altarazi, W Alrefae, ...
Sustainability 14 (1), 548 2022
Citations: 110



A review of micro-EDM
S Mahendran, R Devarajan, T Nagarajan, A Majdi
Proceedings of the international multi conference of engineers and computer 2010
Citations: 100



Copper (II) oxide nanoparticles as additve in engine oil to increase the durability of piston-liner contact
M Asnida, S Hisham, NW Awang, AK Amirruddin, MM Noor, K Kadirgama, ...
Fuel 212, 656-667 2018
Citations: 99



Experimental analysis on the performance, combustion/emission characteristics of a DI diesel engine using hydrogen in dual fuel mode
RA Bakar, K Kadirgama, D Ramasamy, T Yusaf, MK Kamarulzaman, ...
International Journal of Hydrogen Energy 52, 843-860 2024
Citations: 97



A comprehensive review on fused deposition modelling of polylactic acid
L Sandanamsamy, WSW Harun, I Ishak, FRM Romlay, K Kadirgama, ...
Progress in Additive Manufacturing 8 (5), 775-799 2023
Citations: 94



Analysis of efficiency enhancement of flat plate solar collector using crystal nano-cellulose (CNC) nanofluids
K Farhana, K Kadirgama, HA Mohammed, D Ramasamy, M Samykano, ...
Sustainable Energy Technologies and Assessments 45, 101049 2021
Citations: 69



Statistical and optimize of lattice structures with selective laser melting (SLM) of Ti6AL4V material
K Kadirgama, WSW Harun, F Tarlochan, M Samykano, D Ramasamy, ...
The International Journal of Advanced Manufacturing Technology 97, 495-510 2018
Citations: 69



An experimental study on characterization and properties of nano lubricant containing Cellulose Nanocrystal (CNC)
NW Awang, D Ramasamy, K Kadirgama, M Samykano, G Najafi, ...
International Journal of Heat and Mass Transfer 130, 1163-1169 2019
Citations: 68



Significance of alumina in nanofluid technology: an overview
K Farhana, K Kadirgama, MM Rahman, MM Noor, D Ramasamy, ...
Journal of Thermal Analysis and Calorimetry 138, 1107-1126 2019
Citations: 67



A systematic review on graphene-based nanofluids application in renewable energy systems: Preparation, characterization, and thermophysical properties
M Sandhya, D Ramasamy, K Sudhakar, K Kadirgama, M Samykano, ...
Sustainable Energy Technologies and Assessments 44, 101058 2021
Citations: 66



Wear analysis when machining AISI 304 with ethylene glycol/TIO₂ nanoparticle-based coolant
Y Muthusamy, K Kadirgama, MM Rahman, D Ramasamy, KV Sharma
The International Journal of Advanced Manufacturing Technology 82, 327-340 2016
Citations: 62



An overview on synthesis, stability, opportunities and challenges of nanofluids
WT Urmi, MM Rahman, K Kadirgama, D Ramasamy, MA Maleque
Materials Today: Proceedings 41, 30-37 2021
Citations: 55



Numerical study of engine parameters on combustion and performance characteristics in an n-heptane fueled HCCI engine
MM Hasan, MM Rahman, K Kadirgama, D Ramasamy
Applied Thermal Engineering 128, 1464-1475 2018
Citations: 55



Thermal analysis of cellulose nanocrystal-ethylene glycol nanofluid coolant
L Samylingam, K Anamalai, K Kadirgama, M Samykano, D Ramasamy, ...
International Journal of Heat and Mass Transfer 127, 173-181 2018
Citations: 51