2 publications

• Published Subscription Original Research 23 Jul 2026

  Prediction of Mechanical Properties for Advanced Engineering Applications utilizing Polymer Composite Materials by Machine Learning

  By R. Indhu, S. Palpandi, W.V. Sherlin Sherly, M. Indirani, M.D. Boomija, S. Suruthi, R. Balasubramaniyan

  Abstract: Polymer composites show great promise as engineering materials because of their mechanical performance, resistance to corrosion, lightweight nature, and adaptability in design. Aerospace, automotive, biomedical, maritime, and civil engineers all rely on mechanical property prediction to cut down on trial expenses, expedite product development, and optimize material selection. Speedy design optimization is not possible using traditional numerical and experimental methods due to the high costs associated with material characterisation, computational …

  Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 Read article →

• Published Subscription Original Research 6 Jul 2026

  Develop the Design of Sustainable Polymer Materials: Applying Reinforcement Learning, IoT-Enabled Monitoring, and Data-Driven Manufacturing Approaches

  By C. Selvarathi, M. Parthiban, D. Pavunraj, D. Shobana, V. Parimala, R. Dhivya, S. Palpandi

  Abstract: Sustainable polymer materials development is a must due to resource constraints, environmental concerns, and the demand for designed materials with high performance. When it comes to material optimization, energy utilization, process unpredictability, and lifecycle sustainability, traditional polymer production methods have their challenges. Reinforcement Learning (RL), Internet of Things (IoT) monitoring, and data-driven production are utilized in the design and manufacturing of sustainable polymer materials. It is recommended to use Internet …

  Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 Read article →