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Journal of Polymer & Composites Cover

Journal of Polymer & Composites

E-ISSN: 2321-2810 | P-ISSN: 2321-8525 | Peer-Reviewed Journal (Refereed Journal) | Hybrid Open Access

About the Journal

Journal of Polymer & Composites is a peer-reviewed Hybrid Open Access journal launched in 2013, serving the fields of reinforced plastics and polymer composites, including research, production, processing, and applications. JOPC brings detailed developments in this rapidly expanding area long before they become commercial realities, offering a platform to discuss new issues in the area of polymers and composites, and advancing research quality through new methods and practices in Chemical Engineering.

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Journal Metrics

Key performance indicators showcasing our journal’s impact and reach

1407

Published Articles (2024)

44.69

Days Acceptance Time

40

Day Publication Time

Total Visits

Journal Information

Title: Journal of Polymer & Composites
Abbreviation: jopc
Issues Per Year: 6 Issues
P-ISSN: 2321-8525
E-ISSN: 2321-2810
Publisher: STM Journals, An imprint of Consortium e-Learning Network Pvt. Ltd.
DOI: 10.37591/JOPC
Starting Year: 2013
Subject: Chemical Engineering
Publication Format: Hybrid Open Access
Language: English
Copyright Policy: CC BY-NC-ND
Type: Peer-reviewed Journal (Refereed Journal)

Address:

STM Journals, An imprint of Consortium e-Learning Network Pvt. Ltd. A-118, 1st Floor, Sector-63, Noida, U.P. India, Pin - 201301

Editorial Board

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jopc maintains an Editorial Board of practicing researchers from around the world, to ensure manuscripts are handled by editors who are experts in the field of study.

Editor in Chief

Editor

Dr. Susarla Venkata Ananta Rama Sastry, Associate Dean

Harcourt Butler Technical University, Uttar Pradesh, India, 208001

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Latest Articles

Ahead of Print

Digital Twin Assisted Intelligent Prediction of Polymer Composite Degradation Under Environmental Exposure

Polymer matrix composites (PMCs) deployed in aerospace, marine, automotive, and renewable-energy structures are continuously subjected to coupled environmental stressors — ultraviolet (UV) radiation, moisture ingress, thermal cycling, and mechanical loading — that progressively degrade their mechanical performance. 

digital twin; polymer composite; degradation prediction; environmental exposure; physics-informed neural network; LSTM; structural health monitoring; accelerated ageing; hygrothermal ageing; predictive maintenance; degradation mechanisms; mechanical property retention; neural network prediction; IoT-based monitoring.

Artificial Intelligence for Polymer and Nanocomposite Materials: Performance Prediction, Manufacturing Optimization, and Future Perspectives

The exceptional mechanical properties, design flexibility, and lightweight nature of polymer composite and nanocomposite materials make them indispensable in a wide range of applications, including aerospace, automotive, construction, biomedical, and energy sectors.

Polymer nanocomposites, Performance Optimization, Mechanical Strength, Durability, Manufacturing Efficiency, Predictive Analytics, Material Engineering.

Machine Learning–Assisted Design of High-Performance Biomedical Polymer Composites

The high-performance biomedical polymer composite design needs to represent a trade-off between the strength, biocompatibility, and degradation that cannot be accomplished using conventional design methods.

Biomedical Polymer Composites, Machine Learning, Multi-Objective Optimization, ANN, Material Design

Artificial Intelligence-Based Optimization of Mechanical and Biocompatible Properties in Polymer Composite Implants

Artificial Intelligence (AI) has already become a ground-breaking tool of streamlining polymer composite implants to enhance both mechanical strength and biocompatibility simultaneously.

Artificial Intelligence, Polymer Composite Implants, Mechanical Properties, Biocompatibility, Multi-objective Optimization, Genetic Algorithms.

Smart Polymer Composite Scaffolds for Tissue Engineering with Integrated Machine Learning Feedback

Another potential solution to improving the results of tissue engineering is smart polymer composite scaffolds, which are capable of dynamic adaptation to changing biological factors, but typical scaffolds cannot change dynamically.

Smart Polymer Composite Scaffolds, Tissue Engineering, Machine Learning Feedback, Biodegradable Materials, Embedded Sensors, Real-Time Monitoring, Adaptive Control Systems, Predictive Modeling, Regenerative Medicine, Intelligent Biomaterials

Intelligent Failure Detection in Biomedical Composite Materials Using Machine Vision

The biomedical composite materials are intelligent failure-detecting, which is necessary to ensure the reliability, safety, and durability of the current healthcare equipment.

Biomedical Composite Materials, Machine Vision, Failure Detection, Deep Learning, Convolutional Neural Networks, Transformer Models, Ensemble Learning, Explainable AI, Edge–Cloud Computing, Predictive Maintenance.