Enhancing Mechanical Properties of Polymer Nanocomposites through Artificial Intelligence and Machine Learning.

EasyChair Preprint 14500

Abstract

The advancement of polymer nanocomposites has revolutionized material science, offering enhanced mechanical properties that are crucial for various industrial applications. However, optimizing these properties remains a significant challenge due to the complex interplay between the polymer matrix and nanoscale fillers. This study explores the integration of Artificial Intelligence (AI) and Machine Learning (ML) techniques to enhance the mechanical properties of polymer nanocomposites. By leveraging AI-driven models, we can predict and optimize key factors such as filler dispersion, interfacial adhesion, and material composition. ML algorithms are employed to analyze large datasets, identify patterns, and propose novel formulations with superior mechanical performance. This approach not only accelerates the material design process but also reduces the reliance on trial-and-error methods, leading to more efficient and sustainable material development. The findings suggest that AI and ML hold significant potential in advancing the field of polymer nanocomposites, paving the way for the creation of materials with tailored properties for specific applications.

Keyphrases: Artificial Intelligence, Modulus, Toughness, machine learning, mechanical properties, polymer nanocomposites, tensile strength

@booklet{EasyChair:14500,
  author    = {Abi Cit},
  title     = {Enhancing Mechanical Properties of Polymer Nanocomposites through Artificial Intelligence and Machine Learning.},
  howpublished = {EasyChair Preprint 14500},
  year      = {EasyChair, 2024}}