AI‐Driven Sustainable Polymers: A Pathway to Environmental Resilience

ABSTRACT Artificial intelligence (AI) is emerging as a disruptive material science technology, and the move toward sustainable materials is critical in mitigating environmental degradation. In offering a pathway toward greater environmental resilience, this research explores the potential of AI in designing and optimizing sustainable polymers. Accurate molecular design, improved recyclability, and reduced dependence on fossil fuels are facilitated by AI‐led innovation in polymer chemistry. AI integration increases predictive modeling, accelerating performance optimization and material discovery. The report critically assesses the recent innovations in AI technologies for polymer sustainability, including AI‐assisted polymer synthesis, machine learning algorithms for biodegradability prediction, and innovative recycling approaches. The research employs a mixed‐methods approach to assess the potential of AI in sustainable material development, combining data‐driven analysis and case studies from the real world. The research also covers issues of the day, such as the economic viability of AI‐enabled polymer innovation, AI‐material ethics, and scaling AI‐enabled solutions. Policy guidelines are made public to spur industry take‐up of sustainable AI‐enabled materials. Future studies are the central theme in more precise AI models, blockchain to enable supply chain transparency, and the exploration of quantum computing for polymer science innovations.

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Publication Details

Journal
Macromolecular Symposia
Published
2025-11-14
DOI
https://doi.org/10.1002/masy.70175
Primary Topic
Machine Learning in Materials Science
Type
article
Field-Weighted Citation Impact
0.00
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article

AI‐Driven Sustainable Polymers: A Pathway to Environmental Resilience

Abhishek Kumar Singh, SK Singh, Rashid Hashmi
Macromolecular Symposia
Machine Learning in Materials Science
article

AI‐Driven Sustainable Polymers: A Pathway to Environmental Resilience

Abhishek Kumar Singh, SK Singh, Rashid Hashmi
article en

Abstract

ABSTRACT Artificial intelligence (AI) is emerging as a disruptive material science technology, and the move toward sustainable materials is critical in mitigating environmental degradation. In offering a pathway toward greater environmental resilience, this research explores the potential of AI in designing and optimizing sustainable polymers. Accurate molecular design, improved recyclability, and reduced dependence on fossil fuels are facilitated by AI‐led innovation in polymer chemistry. AI integration increases predictive modeling, accelerating performance optimization and material discovery. The report critically assesses the recent innovations in AI technologies for polymer sustainability, including AI‐assisted polymer synthesis, machine learning algorithms for biodegradability prediction, and innovative recycling approaches. The research employs a mixed‐methods approach to assess the potential of AI in sustainable material development, combining data‐driven analysis and case studies from the real world. The research also covers issues of the day, such as the economic viability of AI‐enabled polymer innovation, AI‐material ethics, and scaling AI‐enabled solutions. Policy guidelines are made public to spur industry take‐up of sustainable AI‐enabled materials. Future studies are the central theme in more precise AI models, blockchain to enable supply chain transparency, and the exploration of quantum computing for polymer science innovations.

Macromolecular SymposiaVol. 415(1)
Tezpur University (IN), University of Petroleum and Energy Studies (IN), Sharda University (IN)
Openalex Percentile: Top 73%
Machine Learning in Materials Science
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