various deep learning techniques for applications in polymer, polymer composite chemistry, structures and processing

various deep learning techniques for applications in polymer, polymer composite chemistry, structures and processing

polymers and polymer composites possess a wide range of applications in chemical, material, and biomedical fields. although conventional techniques to the design and processing of these significant materials have been successful, they have faced critical problems. their synthesis is not only time-consuming, but it is also costly for polymer industries. in recent years, there has been a regenerated hype regarding deep learning, as an approach based on artificial neural networks.

due to the importance of both polymer chemistry and artificial intelligence systems in the academic research and industry, it is a requirement to present approaches combining these two promising fields. this paper aims to categorize various deep learning approaches used in the field of the polymer science. we expect that this can expand the polymer chemistry community engagement with artificial intelligence, especially deep learning and accelerate the improvement in the data-driven techniques for the synthesis and application of polymers.