Volume 3, Issue 1, January-June, 2026
Physicochemical Comparison of Rambutan Nephelium lappaceum Seed Fat and Dairy Butter Fat for Alternative Use
Open Access | Original Article | 04 May 2026 | Article Number: 261002
Abstract
Rambutan (Nephelium lappaceum) seed fat is an underexplored plant-based lipid which shows potential for both functional and nutritional applications. In this study, its physicochemical properties along with its fatty acid profile were compared with those of the dairy butter. The Rambutan seed fat showed a melting point of 28.5°C, which is about 3–6°C lower than butter (32–35°C) indicating a softer consistency. Saponification value of Rambutan seed fat (201.54 mg KOH/g) was also lower than that of butter (225–240 mg KOH/g), suggesting the presence of longer-chain fatty acids. The peroxide value was less than the quantitation limit of 0.2 meq O2/kg of fat, reflecting minimal primary oxidation at the time of analysis. The fatty acid composition was dominated by monounsaturated fatty acids (74.3%), mainly oleic and eicosenic acids, which is substantially higher than in butter (28–30%). In contrast, saturated fatty acids were markedly lower (15.2% vs. 63–65%), while polyunsaturated fatty acids were relatively higher (10.5% vs. 2–3%). These differences help explain the softer texture and lower melting behaviour of Rambutan seed fat. Overall, the findings suggest that it could serve as a viable alternative fat, although further studies on stability and application are needed. Read more
View PDFStudy of the Wear & Tear Behavior of Resin-based Composites Reinforced with Al2O3 Ultrafine nanoparticles and Metal Wires applying DOE Techniques
Open Access | Original Article | 30 March 2026 | Article Number: 261001
Abstract
The scientists investigate the mechanical characteristics of an epoxy-based biodegradable composite material reinforced with Al2O3 ultrafine particles and metal wires, and uses design of experiments (DOE) and simulation techniques to optimize its attributes. The Al2O3 nano powder was characterized by SEM and used in weight percentage of 0-5% to create composites with 50-100 nm nanoparticles. ANN models were trained on the resulting data to estimate the tensile strength and moisture absorbing behavior of the composite under different conditions, with mean absolute errors of 5% and 10% for the training and test sets respectively. The data demonstrate the effectiveness of computational learning in predicting the material properties of natural/jute composite materials and optimizing their design. Overall, this research paper provides valuable observation into the use of Al2O3 ultrafine nanoparticles and metal wire reinforcement for enhancing the overall material properties of biodegradable epoxy-based composites. Read more
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