Predictive Modeling
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Advanced Material Design and Fabrication Efficiency Using Cloud Computing: A Scalable Computational Framework for Polymer Nanocomposites
Abstract: The design of the material, the prediction of the properties and the fabrication techniques should be enhanced to efficiently use the high performance polymer nanocomposites. However, the traditional computational methods are often restricted by issues of scaling, computing cost, data integration, and processing time in assessing the complex combinations of polymers, nanofillers, processing factors and material characteristics. This work presents a scalable cloud-computing framework for the efficient design and fabrication …
Published in Journal of Polymer & Composites · Vol. 14, Issue 5, 2026 Read article
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Machine Learning-Based Optimization of Additive Manufacturing with Improved Mechanical Performance: Development of Sustainable Thermoplastic Composites
Abstract: Additive manufacturing has successfully manufactured lightweight, programmable and geometrically complicated components. However, reliable mechanical performance and efficient use of resources remain hard. This paper presents a machine learning (ML) based approach to optimize additive fabrication of sustainable thermoplastic composites with enhanced mechanical characteristics. The suggested approach combines material composition, printing settings and process circumstances to forecast and optimize tensile strength, flexural strength, impact resistance and dimensional stability. The aim is …
Published in Journal of Polymer & Composites · Vol. 14, Issue 5, 2026 Read article