Self-healing of cracks in brittle ceramics and glasses can dramatically increase the reliability and lifetime of structural components and reduce the maintenance costs in a broad range of energy technologies. The goal of this project is to achieve a detailed atomistic understanding of self-healing processes to determine the optimal size and spatial distribution of nanoparticles for self-healing of structural ceramics in energy applications at high service temperatures.

Researchers will perform petascale quantum molecular dynamics (QMD), reactive molecular dynamics (RMD), and mesoscale reactive dissipative particle dynamics (RDPD) simulations to study the self-healing capabilities of anticorrosion coatings for metals and ceramic nanocomposites. They also will perform RMD simulations to determine the mechanical properties of self-healing materials, like aluminum sponges.

Based on benchmarks and previous production runs on Mira, researchers have significantly improved the scalability, time-to-solution, and floating-point performance of QMD and RMD simulation codes. Time-to-solution was 60-times less than the previous state-of-the-art code.

Simulation results have revealed a novel nanostructural design for on-demand hydrogen production from water, advancing renewable energy technologies. And the team’s largest QMD simulation has shown that orders-of-magnitude faster reactions with higher yields can be achieved by alloying aluminum (Al) particles with lithium (Li). During this investigation, researchers discovered a surprising autocatalytic behavior of the oxygens that bridge Li and Al, suggesting that Li-O-Al plays an active role in oxidation. This atomistic understanding of metal corrosion advances the proposed study of anticorrosion coatings for metals.

Novel self-healing materials will play vital roles in the design of components for high-temperature turbines, wind and solar energy, lighting applications, and medical implants.