Research

Everything Should Be Made as Simple as Possible, But Not Simpler --- Albert Einstein

The Wu research group is dedicated to advancing the understanding and design of complex materials, with a particular focus on macromolecules and polymers. By integrating cutting-edge computational techniques, we aim to push the boundary forward in the following key areas:

  1. Advanced Hierarchical Simulations: We are pioneering the development of advanced hierarchical simulation techniques. Using a combination of statistical mechanics and machine learning, we are creating predictive models that enable first-principle forecasts of material properties. Our simulations span from atomistic to coarse-grained levels, providing insights across multiple scales.
  2. Computational Design of Advanced Materials: We integrate machine learning and multiscale simulations into computational-driven materials design. This approach enables the autonomous discovery and design of functional materials with specific, targeted properties. By developing reliable machine-learning force-fields, we aim to accelerate the design of new materials, particularly polymeric materials with tailored topologies.
  3. Molecular Topology in Macromolecules: We seek to establish a fundamental understanding of the molecular topologies that naturally occur in macromolecular systems. These topological structures play a crucial role in determining the dynamics, rheology, mechanics, and transport properties of materials. By uncovering these principles, we aim to enable the rational control of these properties in both synthetic and biological systems.

Through our interdisciplinary research, we strive to push the boundaries of chemistry, polymer physics, and computational materials science, fostering innovation in the discovery and design of next-generation macromolecular materials. Join us in our mission to transform the way we understand and engineer functional macromolecular materials!

Research Infrastructure Our group currently owns workstations with GPUs: 4 \(\times\) 3090 and 3 \(\times\) 4090 and CPUs: > 100 cores; In addition, XJTLU has university-wide HPC center, which is continuously growing. Currently, there are more than 60 GPUs and 1000 CPU cores. Find more details on XJTLU HPC official website.