Development and characterisation of Theobroma cacao bioplasticizer for sustainable polylactic acid biofilm fabrication Md Ameen, U. Sudhakar, K. Sravanthi, T. Senthil Vadivel, Murali B., Rantheesh J., Sunesh Narayanaperumal, K. Arun Kumar, K. Arunprasath Next Materials, 2026 The concern associated with environmental safety accelerated alternative source for petroleum based plastic material for packaging application. In this study, a bio based plasticizing filler was extracted from cocoa Theobroma outer shell by subjecting it to sequential pre-treatment, alkaline extraction and processing. The extracted bioplasticizer was characterized to check its suitability for packaging polymer composite material. The bio-based additive was mixed with polyethylene glycol (PEG 400) as plasticizer in improving the performance of polylactic acid (PLA) films. With differentiating contents of PEG 400 (10 and 20 wt%) and 5 wt% bio-additive, the films were fabricated using solvent casting method. The presence of characteristic functional groups in the FTIR analysis confirmed the presence of hydrogen bonding confirming the physical interactions. UV–visible analysis confirmed the UV-shielding ability of the bio-additive. SEM micrographs exhibited the improved dispersibility and interfacial capability of systems. Mechanical testing revealed that polyethylene glycol (PEG) 400 significantly increased elongation at break. Besides, the bio-additive improved the stiffness and strength. The mechanical and morphological properties of the optimized formulation (PPEG10) were balanced. The overall system established is capable of developing flexible, biodegradable PLA films with improved performance sustainably.
Optimization of TIG welding parameters and filler rod material selection for dissimilar aluminum alloy joints Kasu Karthick, K. Sravanthi, S. P. Jani, D. Antony Prabu, Senthil Vadivel T., Haiter Lenin Allasi Journal of Materials Science Materials in Engineering, 2025 The objective of this research is to enhance the mechanical characteristics of aluminum alloy welds by adjusting tungsten inert as (TIG) welding parameters. Different welding parameters, such as current (150, 170, and 190 amps), gas flow rate (10, 11, and 12 l/min), and filler rod diameter (1.6, 2.0, and 2.4 mm), were systematically analyzed using the TOPSIS technique used in industries like aerospace, automotive, and construction, where precise welding control ensures aluminum alloy reliability and performance. It engages in multiparameter optimization which systematically ranks welding parameters, helping identify key factors that enhance weld quality. The response parameters selected were ultimate tensile strength (UTS), Vickers hardness, and percentage of elongation. A total of 31 microhardness readings were obtained to assess hardness distribution across the welded joints. Analysis of the results indicated that the filler rod diameter significantly influenced all response parameters. Specifically, it had the highest impact on UTS, elongation, and hardness, with contribution percentages of 48.4%, 52.6%, and 51.41%, respectively. The gas flow rate and welding current also affected these properties but to a lesser extent. ANOVA results showed that the filler rod diameter was the most critical factor, with high F-values and low P-values for each response parameter. The study concludes that optimizing filler rod diameter can substantially improve weld quality, making it the most influential parameter in achieving desired mechanical properties in TIG welding of aluminum alloys.
Precision agriculture redefined: Combining machine learning and deep learning for enhanced crop yield prediction Kanaka Raju Kalla, Sonal Saluja, R. Ramya Swetha, K. Sravanthi, Deepika Gupta Recent Trends in Intelligent Computing and Communication Volume 1, 2025 Crop yield prediction plays a vital role in precision agriculture by enabling sustainable farming practices and efficient resource management. Modern agriculture faces numerous challenges, including unpredictable weather patterns, soil degradation, water scarcity, and the growing demand for food due to a rising global population. Apart from these challenges agriculture has to manage limited resources and to enhance productivity and farm yields. The new revolutionary technologies like machine learning and deep learning enables the use of an exhaustive database to achieve an effective and optimized utilization of the limited resources while addressing the desired or targeted output designed. Primarily this study is conducted to compare the effectiveness of the various tools available under machine learning and deep learning. The selected tools are Random Forest, AdaBoost, XGBoost, LightGBM, CatBoost, and a Hybrid Neural Network (HNN). The input data variables such as soil pH, temperature, humidity, wind speed, soil type, crop type and soil nutrients (N, P, K) for the period between 2014-2023 are put to analyse their best correlation with the desired output by using selected technology tools. It is concluded that though CatBoost recorded the best values for R2 of 0.9784 & with RMSE of 3.7749 however among the selected all models HNN achieved an error reduction with 5.49% & 1.4% improvement in the Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) respectively in comparison with CatBoost. Hence a combination of machine learning and deep learning tools are found to be effective in addressing the key agricultural challenges, enhancing productivity under resilient and sustainable agricultural ecosystem.
Statistical analysis to examine the influence of thermal aging on hybrid glass epoxy polymer composites with fillers of multi-walled carbon nanotubes K. Sravanthi, V. Mahesh, B. Nageswara Rao, S. P. Jani SPE Polymers, 2024 E‐glass fibers are widely preferred due to ease of processing and its low cost, which has substantial scope in the fields of electronics and electrical insulation applications. Because of its low strength and corrosion resistance, use of E‐glass fibers is limited in aerospace and automotive applications. There is a need for enhancing the properties of the composite to overcome such limitations. Therefore, an attempt is made to introduce multi‐walled carbon nanotubes (MWCNT) as fillers into E‐glass fibers to meet the industry needs. In the current study, woven glass fiber of 5 layers and multi‐walled nano carbon fillers of 2, 4 and 6 by wt%, LY556 epoxy resin, and HY951 hardener were used to prepare 4 different type of composites along with the neat epoxy glass fiber reinforced polymer composites (GFRP). The hand‐layup route was used in the composite preparation due to its low cost, technological feasibility, and simple process setup. The developed samples were characterized for mechanical properties via tensile, flexural and impact tests. Tribological characteristics were performed by air jet erosion test. Chauvenet's criterion is applied for identifying the outliers (if any) from the data of repeated test properties. Taguchi's (orthogonal array) is selected for obtaining optimal hybrid composite, which yield better mechanical properties. Empirical relations are developed for the material properties in terms of process variables. The sample (4 wt% MWCNT) exhibited enhancement of 17.27% in tensile strength, 6% of impact strength and 7.3% of flexural strength when compared with neat epoxy GFRP. This hybrid composite is considered for thermal aging and observed at 60°C, 8% increase in tensile, 7% increase of impact and 15% in flexural strength due to the precipitation on carbon nano tubes along the gain boundaries. The present study recommends 4% MWCNT fillers in developing hybrid glass epoxy polymer composites for use in aerospace, automotive and civil construction industries due to economic and technological feasibility.Highlights Utilize low‐cost E‐glass fibers in electronics and electrical insulation applications. Improve composite properties for aerospace and automotive industries. Develop hybrid glass epoxy composites with 2 to 6 wt% MWCNT fillers. Examine wear characteristics under air jet erosion and study the impact of thermal aging on mechanical properties. Apply Chauvenet's criterion for outlier identification in measured properties datasets.
Distortion measurement of Laser beam welding for Similar and Dissimilar joints using a Coordinate Measuring Machine N V BasiReddy Peddapudi, K.Sravanthi, Sudhakar Uppalapati, S.P.Jani, Lakshman Rao Muppa, Harinadh Vemanaboina 1st International Conference on Innovative Engineering Sciences and Technological Research Iciestr 2024 Proceedings, 2024 The most common welding use is to join two components permanently. Many modern wonders would not be possible without welding, including skyscrapers, vehicles, ships, aerospace applications, etc. This work used two materials and combinations of super duplex stainless steel (UNSS32750) and Inconel 625 for welding. The surface and internal defects of the manufactured components are verified with visual inspection, X-ray radiographic testing, and non-destructive testing. The distortion measurement in the weldments is carried out using the coordinate measuring machine. The X-ray radiographic test confirms that the joints are free from surface and internal defects. The distortion in the welds is within the limits of industrial standards.
Evaluation of mechanical properties of ABS-based fiber composite with infill using 3D printing technology Venkataramana, P., Jani, S.P., Sudhakar, U., Adam Khan, M., Sravanthi, K. Materials Physics and Mechanics, 2023 This research explores the utilization of acrylonitrile butadiene styrene (ABS) material for structural applications, addressing the growing demand for polymer composites. Employing fused filament fabrication (FFF) 3D printing with a 2 mm shell thickness, ABS samples were reinforced with basalt, hemp, and glass fibers using epoxy resin to enhance material strength. Mechanical behavior under axial, flexural, and impact loading conditions was investigated, revealing the basalt-reinforced ABS composite's superior performance with a maximum load of 9540 N - three times that of pure ABS (2975 N). The load-bearing capacity of basalt-epoxy reinforced ABS reached 880 N, surpassing glass-epoxy and hemp-epoxy variants. Impact energy was notably higher for reinforced composites (28.9-32.2 KJ/m2) compared to pure ABS (10.3 KJ/m2). The SEM analysis also carried out for better understanding of fracture surface of composites. This study recommends the application of these reinforced ABS composites in structural contexts.
Effect of Natural Filler on Natural Fibre Hybrid Composite P. Sai Vardhan Reddy, K. Sravanthi, S.P. Jani Materials Science Forum, 2022 The natural filler material is reinforced along with natural fibers in the composite to improve the quality and property of the component materials based on the requirements and its applications. In this paper, the hybrid composite was developed with Hemp/ Basalt fiber. Various wt% (15%,20%,25%) of Hemp fiber and filler materials were used as reinforcement. The Hemp fiber was surface treated with 5% of KMnO4. The developed hybrid natural fiber composites were performed with various mechanical properties studies like tensile, bending, impact, and Brinell hardness all these tests were performed as per ASTM standards. From the mechanical property study, 25 wt% Hemp fiber hybrid composite hold good mechanical properties compared to all other wt% developed hybrid composite.