What is it about?
The combination of experiments and machine learning techniques to describe the properties of polymer composites incorporating carbon nanotubes. The results corroborate that even when the same prediction model is used, its performance varies depending on the physical property to be predicted.
Featured Image
Photo by Renders BR on Unsplash
Why is it important?
The development of accurate models for predicting nanocomposite properties would cheapen, simplify and systematize their design and production processes, resulting in improved final products and more efficient development procedures.
Perspectives
This research holds great potential for advancing the field of modelling the mechanical properties of polymeric nanocomposites and their practical applications in various industries such as food, pharmaceutical and biomedicine.
Ana Maria Diez Pascual
Universidad de Alcala de Henares
Read the Original
This page is a summary of: Machine learning algorithms to optimize the properties of bio-based poly(butylene succinate-co- butylene adipate) nanocomposites with carbon nanotubes, Industrial Crops and Products, November 2024, Elsevier,
DOI: 10.1016/j.indcrop.2024.119018.
You can read the full text:
Contributors
The following have contributed to this page
