Integration of green supply chain and logistics practices in textiles and their impact on united nations sustainable development goals M. Shamini, D. Mala, Ratchagaraja Dhairiyasamy, Deepika Gabiriel Discover Sustainability, 2026 The textile sector is a high-impact polluter with long, opaque supply chains, making credible measurement and coordinated action difficult; green supply chain management offers concrete levers to cut material and energy intensity while strengthening resilience. Yet decision makers lack a sector-specific, SDG-explicit map that shows which GSCM mechanisms matter most and where evidence is thin. This study addresses that gap by producing an SDG-linked cartography of textile GSCM. A PRISMA-style screen reduced 6,372 Scopus records to 1,224 eligible publications (2013–2025); bibliometric and science-mapping techniques (keyword co-occurrence, clustering, SDG tagging) were applied using VOSviewer and SciVal, with transparent parameters and sensitivity checks. Results resolve three thematic clusters—policy/management, Industry 4.0, and coordination/operations—and quantify goal salience: SDG 12 accounts for 55.7% of tagged papers, SDG 9 for 41.8%, and SDG 13 for 36.6%. Field activity expanded from 47 papers in 2013 to 198 in 2023 (≈ 321% increase), with a marked shift toward circularity and digitalisation after 2017. Contributions are geographically concentrated, with China accounting for 25.5% of items. Evidence indicates that digital traceability, analytics, and closed-loop logistics are associated with greater impact and tighter alignment with SDG 9 and SDG 12, while climate-action framing tends to follow digital adoption with a one-to-two-year lag. The map can guide firms toward investments in product passports, carbon-aware planning, and reverse flows, and can help policymakers target disclosure mandates, EPR design, and incentives for SME digitalization. The synthesis highlights underrepresented social goals and regions, motivating pilot studies that pair digital enablement with labor and equity indicators; future work should triangulate automated SDG tagging with manual multi-label coding and test causal links between specific GSCM levers and SDG targets using quasi-experimental designs.
Enhancing Photovoltaic (PV) System Efficiency Through Integrated Inclination Control and I-V Curve-Based Diagnostics S. M. Kamali, V. Malathy, Ratchagaraja Dhairiyasamy, Deekshant Varshney, Subhav Singh Nature Environment and Pollution Technology, 2026 Photovoltaic (PV) systems have become central to the global transition toward renewable energy; however, their efficiency is often compromised by environmental variability and inadequate monitoring integration. Therefore, advanced supervisory platforms that unify data acquisition, fault detection, and performance optimization have become increasingly important. Existing monitoring approaches do not adequately integrate grid-connected and isolated systems with real-time diagnostic capabilities. This study was undertaken to develop and validate a supervisory interface capable of simultaneously monitoring multiple PV configurations while incorporating image-based shading detection and tilt optimization. The methodology combined the hardware implementation of rooftop and ground-mounted PV modules, sensor-based data acquisition through LabVIEW, integration with MATLAB/ Simulink modeling for system validation, and camera-based analysis for shading and tilt detection. The results demonstrated that shading of a single cell could reduce the total power output by nearly 50%, whereas tilt optimization of approximately 34° increased the energy yield by 14%. The integrated operation of rooftop and ground-mounted systems improved the daily energy output by 11% compared to standalone systems. Statistical analysis confirmed the robustness of these findings, with performance ratio and efficiency indices showing consistent alignment across trials. The developed interface effectively linked the manufacturer specifications of modules and inverters with field performance, enabling accurate benchmarking and anomaly detection. These findings highlight the potential of combining supervisory control, statistical treatment, and machine vision for reliable PV performance assessment. The work suggests that future research should extend the supervisory platform toward predictive maintenance and integration with smart grid infrastructures to further enhance scalability and resilience.
Innovative syngas-biodiesel blends: a step towards cleaner and greener engine technology Manikandan Ezhumalai, Mohan Govindasamy, Ratchagaraja Dhairiyasamy, Deekshant Varshney, Subhav Singh Energy Conversion and Management X, 2026 • Dual-fuel CI engine: biodiesel pilot with hydrogen-rich, glycerol syngas. • RSM (CCD) models BTE and NOx versus engine load and syngas flow. • Load dominates BTE; syngas yields small, additive efficiency gains. • NOx grows with load and flow; slight positive A × B interaction. • Optimum: 56.76% load, 5 L·min −1 syngas (BTE 27.1%, NOx 579 ppm). The increasing demand for sustainable and cleaner alternatives to fossil fuels has intensified research on Biodiesel and gaseous fuels for internal combustion engines. However, most existing studies focus on individual biodiesel feedstocks or diesel–syngas combinations, leaving limited understanding of the synergistic effects of blended biodiesels enriched with Syngas. This study aims to evaluate the performance, combustion, and emission characteristics of Juliflora and Pine Oil Methyl Ester Biodiesel blends integrated with hydrogen-rich Syngas in a dual-fuel compression ignition engine. Experiments were conducted on a Kirloskar SV1 engine at varying loads and syngas flow rates, and performance metrics were analyzed using Response Surface Methodology (RSM) and ANOVA. Results revealed that the J60 + P40 blend with 20 L/min syngas achieved a brake thermal efficiency of 31.2%, a 12% improvement over neat Biodiesel, while reducing brake-specific fuel consumption by 8% and smoke opacity by 25%. CO and HC emissions decreased by 18% and 22%, respectively, though NO x increased marginally by 5% due to elevated combustion temperatures. These findings demonstrate that syngas enrichment enhances combustion efficiency and supports the utilization of cleaner energy. Future research should focus on integrating exhaust gas recirculation (EGR) or catalytic after-treatment to mitigate NO x emissions and further optimize Biodiesel–syngas blending ratios.
Optimization of Fill Ratio and Angle Improved Energy Efficiency in Two-Phase Copper Heat Pipes Wasurat Bunpheng, Prabhu Alphonse, Sivakumar Elumalai, Alagarasan Ilango, Kodela Rajkumar, Ratchagaraja Dhairiyasamy, Subhav Singh, Choon Kit Chan Heat Transfer, 2026 High heat‐flux dissipation in compact low‐voltage direct current (LVDC) power electronics is limited by temperature gradients that elevate thermomechanical stress, and two‐phase copper heat pipes provide passive heat transport. Nanofluid working fluids can strengthen phase‐change heat transfer when stable dispersions are maintained in sealed devices. An optimization that couples nanoparticle concentration, heat input, inclination, and filling ratio for copper heat pipes has not been reported. The objective of this study is to identify operating conditions that minimize thermal resistance (TR) and maximize the heat‐transfer coefficient for copper heat pipes charged with deionized water or Al 2 O 3 , CuO, or Ag nanofluids. Nanofluids were prepared via a two‐step route, screened for zeta potential over 30 days, and charged into copper heat pipes with axial thermocouples. Experiments were conducted within the defined factor bounds, and a rotatable CCD–RSM framework was used to fit quadratic models and optimize desirability. Thermal performance, supporting energy efficiency in LVDC hardware, is maximized at 1.98 vol%, 99.47 W, 89.44°, and 74.74% fill, at which a TR of 0.0736 K/W and a heat‐transfer coefficient of 1710 W/(m 2 ·K) were predicted, and this operating point provides a target for LVDC implementation. A pronounced interior optimum in filling ratio is identified, and heat input dominates the linear response while two‐factor interactions remain nonsignificant within the explored region. These model‐derived set points enable heat‐pipe integration into LVDC modules with predictable thermal margins. Long‐duration aging, corrosion‐compatibility screening, and independent verification at the predicted optimum are targeted to extend the validated operating window.
Self-healing catechol–metal PDMS networks with ultra-low WVTR for flexible photovoltaic roof encapsulation in solar electric vehicles Wasurat Bunpheng, V. Gopinath, Ratchagaraja Dhairiyasamy, Deekshant Varshney, Subhav Singh, Choon Kit Chan Next Materials, 2026 Flexible photovoltaic modules integrated into vehicle roofs require encapsulants that combine optical transparency, low moisture permeability, mechanical compliance, and self-repairing capability. Conventional EVA and POE systems exhibit limited barrier performance and lack dynamic bonding, restricting their durability under damp heat and cyclic loading. The research gap lies in the absence of a transparent, self-healing elastomer that simultaneously delivers ultralow water vapor transmission and long-term device stability across multiple metal coordination chemistries. This study aims to develop and systematically evaluate catechol-grafted PDMS networks coordinatively cross-linked by Fe³ ⁺, Al³ ⁺, Zr⁴⁺, or Ti⁴⁺ for flexible solar roof encapsulation. films were synthesised via hydrosilylation grafting, followed by controlled metal coordination, cast to ∼150 µm thickness, and characterised using FT-IR, XPS, DMTA, DSC, WVTR/OTR testing, peel adhesion, healing assays, and mini-module reliability under 85 °C/85% RH, UV, thermal cycling, and bending. Zr⁴⁺ and Ti⁴⁺ networks achieved WVTR values of ∼0.07–0.15 g m⁻² d⁻¹ with T₅₅₀ ≈ 96–97% and haze ≤ 0.8%, and modules retained ∼97% and ∼96% power after 1000 h at 85/85. A WVTR threshold near ∼0.10 g m⁻² d⁻¹ was identified, below which ≥ 95% power retention was sustained. Fe³ ⁺ networks exhibited rapid healing with barrier recovery of ∼95% and tensile recovery of ∼80% within 24 h at 50 °C. Metal–catechol coordination provides an adjustable platform for high-barrier, self-healing photovoltaic encapsulation compatible with curved vehicle modules. Future research should focus on mixed-metal architectures and full-scale automotive validation.
Enhanced heat transfer in copper heat pipes using hybrid nanofluids: experimental and RSM analysis Department of Electronics, Communication Engineering, Saveetha School of Engineering, Saveetha Institute of Medical, Technical Sciences, Saveetha University, Chennai, Tamilnadu, India, R. Dhairiyasamy, M. Venkatasudhahar, Vel Tech Rangarajan Dr Sagunthala R&D Institute of Science, Technology, Chennai 600062, Tamilnadu, India, S. Mahendren, Department of Agricultural Engineering, Kongunadu College of Engineering, Technology,Trichy, B. Saleh, Department of Mechanical Engineering, College of Engineering, Taif University, Taif 21944, Saudi Arabia, D. Varshney, Division of Research & innovation, Uttaranchal University, Dehradun, India, S. Singh, et al. Digest Journal of Nanomaterials and Biostructures, 2025
