Extreme Composites (NSF)

Prof. Jae-Hwang Lee is the principal investigator for UMass Amherst on a three-year, $700,000 project, funded by the National Science Foundation (NSF), to develop pioneering high-performance materials required by many of the world’s most significant industries. Lee is collaborating on the NSF project with Rutgers University principal investigator Professor Jonathan Singer and co-principal investigator Assimina Pelegri.

The Rutgers team will produce hierarchical composite materials and will perform near static mechanical characterization. UMass team will perform the micro-ballistic characterization (laser-induced projectile impact testing or LIPIT) to understand the composite materials’ mechanical properties under extreme deformation.”

In addition to the existing dynamic mechanical analysis, the energy loss spectra from the proposed micro-ballistic method being performed by his UMass team will open a new path to discovering high-strain-rate rheological properties of various viscoelastic materials that have complex phases.

As the NSF research abstract states, “This collaborative proposal employs self-limiting electrospray deposition (SLED) to create controlled libraries of porous microfilms, enabling rapid screening of their characteristic material and architecture parameters while facilitating customized property tunability.” The researchers say they will undertake mechanical analysis covering testing conditions from quasi-static to ballistic impact at room or elevated temperatures, thus allowing probing of the materials’ mechanical response to thermomechanical stimulus.

For ballistic analysis, according to Lee, his team will employ LIPIT testing, an innovative method of using laser-propelled microparticles to create controlled micro-ballistic impact.

The project team consists of experts in SLED fabrication, nanomechanical testing and modeling, and micro-ballistic analysis. Meanwhile, each stage of these studies will be supported by multiscale computational simulations to create predictive models to guide both the course of the experiments to be conducted and the design of future materials.