1 publication

• Published Subscription Original Research 25 Jul 2026

  Hybrid Quantum–Machine Learning Framework for Nonlinear Rheological Modeling of Polymer and Composite Materials

  By Pijush Dutta, Pradip Deb, Pooja Nagpal, Shantanu Naskar, Anubrata Mondal, Tan Yi Fei, Chua Fang

  Abstract: In polymer and composite materials, a major challenge lies in predicting their nonlinear rheological response, owing to complex multiscale interactions that are not captured by traditional constitutive laws or conventional machine learning approaches. In this study, a hybrid Quantum Machine Learning (QML) model comprising Quantum Support Vector Machine (QSVM) and Quantum Neural Network (QNN) architectures is proposed for viscosity prediction without requiring any specific rheological equation. To train and test …

  Published in Journal of Polymer & Composites · Vol. 14, Issue 5, 2026 Read article →