Project Overview
This project aims to integrate computer vision and artificial intelligence into materials science, utilizing deep learning and other AI methodologies to enable efficient and cost-effective digital characterization and reconstruction of heterogeneous materials. By advancing the application of emerging AI technologies, this research seeks to accelerate the development of materials informatics and enhance digital simulation, property prediction, and even the design of new materials.
Project Aims
- Ensure efficient, accurate, and explicit characterization of microscopic heterogeneous materials.
- Establish a quantitative relationship between the microstructure and properties of heterogeneous materials, facilitating the characterization of random microstructures.
- Enable comprehensive reconstruction of two-dimensional and three-dimensional images based on physical properties and morphological information.
Period: October 2023- September 2027
Impact: This study has advanced the digital characterization and reconstruction of microscopic heterogeneous materials by integrating computer vision and artificial intelligence. The artificial intelligence method accelerates the explicit characterization and accurate reconstruction of microscopic heterogeneous structures, greatly reducing the time and cost of obtaining material data sets. At the same time, a robust framework that links microstructures with material properties has been established, providing strong support for digital material simulation, performance prediction, and the design of new materials.
Project Team
Collaborators
Swansea University