Radius: Journal of Science and Technology
An International Bi-Annual Peer-Reviewed Refereed Journal
About the Journal
Radius: Journal of Science and Technology is an open-access international bi-annual peer-reviewed refereed journal that publishes high-quality research dedicated to advancing the frontiers of Science and Technology. It serves as a platform for the propagation and discussion of significant research findings, cutting-edge innovations, …
Why Choose This Journal
- High Standards: Rigorous peer review ensures academic excellence.
- Interdisciplinary: Publishes diverse and innovative research across science and technology.
- Global Reach: Broad international readership for maximum impact.
- Rapid Publication: Streamlined process for timely research dissemination.
- Author Support: Comprehensive guidance from submission to publication.
- Open Access: Reach a wider audience with accessible research.
Choose Radius: Journal of Science and Technology for a trusted platform that values innovation and excellence.
Important Links
Important Links
For Indian Authors: ₹ 3000
For others: US$ 100
Article Processing Charge
03 Days
Median time from submission to first editorial decision before peer review
15 Days
Median time from submission to first decision after peer review
25 Days
Median time from submission to final acceptance after peer review and any author revisions
Editor-in-Chief View Full Editorial Board
Editor-in-Chief
Prof. (Dr.) Ajay Singh Verma
Anand School of Engineering & Technology, Sharda University Agra, Uttar Pradesh, India
Articles
Study 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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