Xia Research Group
Welcome
Welcome to Xia Research Group in the Department of Aerospace Engineering at Iowa State University! Our research focuses on understanding and designing advanced engineering materials through predictive multiscale modeling. We study how molecular- and nanoscale interactions govern the structure, mechanics, and functional performance of materials used in aerospace, structure, energy, and bioengineering applications.
Our group develops multiscale materials-by-design framework – by integrating theories (i.e., soft matter physics, mechanics, continuum theories), computational methods (i.e., molecular dynamics, coarse-grained modeling, and machine learning), and validating experiments. Together, these approaches enable the predictive design of high-performance multifunctional materials across scales.
Scaling up Materials Design with Computation
Modern materials often derive their unique properties from hierarchical structures & interfaces spanning multiple scales. Our group develops advanced scale-bridging computational techniques that connect molecular interactions with macroscopic material behavior.
These approaches allow us to investigate and design a wide range of systems, including:
- Polymer and soft materials
- Nanocomposites and hierarchical materials
- Two-dimensional and layered materials
- Bio-inspired and biological materials
By integrating physics-based modeling with advanced computational tools, our research provides mechanistic insight into material behavior and enables rational materials design.
Our work aligns closely with the goals of the Materials Genome Initiative (MGI) and contributes to accelerating the discovery and deployment of next-generation materials for engineering applications.
Research Highlights
Our group pioneered the Energy-Renormalization (ER) framework for coarse-graining polymers and soft materials, enabling accurate prediction of temperature-dependent behaviors by integrating polymer physics, glass transition theories, and mechanics.
Through multiscale modeling and simulation, our research has revealed how nanoscale structures and intermolecular interactions govern the complex behaviors of polymer thin films and soft materials under nanoconfinement.
More recently, we have integrated artificial intelligence and machine learning (AI/ML) with physics-based modeling to accelerate materials discovery and design. These efforts include predictive frameworks for the structure–property relationships of conjugated polymers, functional coatings, and network materials.
By combining physics-based theory, multiscale simulation, and data-driven approaches, our work advances the computational design of next-generation soft materials and multifunctional polymer systems.
Our Sponsors
