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Published Subscription Original Research
Thermo-Structural Machine Learning Framework for Malicious Sample Detection and Validation in Polymer Composite MaterialsBy Mahesh T. Dhande, Nilesh V. Ingale, Pankaj Deshmukh, Ritesh S. Fegade, Ashwini L. Patil, Bhausaheb Varpe, Vithoba Tale, Rupendra Nehete
Abstract: The increased use of polymer composites in aerospace, automotive, biomedical and industrial applications has increased the urgency of developing dependable methods to detect malicious samples with counterfeited resins, unauthorized additives, recycled components, hidden flaws, or purposefully degraded physical properties. Most current machine learning techniques have focused either on isolated spectral analysis or detecting flaws in materials; as such, they are unable to perform joint verification of both chemical authenticity and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article →