Ab Initio Driven Exploration on the Thermal Properties of Al–Li Alloy

Abstract

Al–Li alloys are feasible and promising additives in advanced energy and propellant systems due to the significantly enhanced heat release and increased specific impulse. The thermal properties of Al–Li alloys directly determine the manufacturing, storage safety, and ignition delay of propellants. In this study, a neural network potential (NNP) is developed to investigate the thermal behaviors of Al–Li alloys from an atomistic perspective. The novel NNP demonstrates an excellent predictive ability for energy, atomic force, mechanical behaviors, phonon vibrations, and dynamic evolutions. A series of NNP-based molecular dynamics simulations are performed to investigate the effect of Li doping on the thermal properties of Al–Li alloys. All calculated results for Al–Li alloys are consistent with experimental values for Al, ensuring their validity in predicting Al–Li interactions. The simulation results suggest that a minor increment in the Li content results in a slight change in the melting point, thermal expansion, and radical distribution functions. These three properties are associated with the lattice characteristics; nonetheless, it causes a substantial reduction in thermal conductivity, which is related to the physical properties of the elements. The lower thermal conductivity allows heat accumulation on the particle surface, thereby speeding up the surface premelt and ignition. This provides an alternative atomic explanation for the improved combustion performance of Al–Li alloys. These findings integrate insights from the field of alloy material science into crucial combustion applications, serving as an atomistic guide for developing manufacturing techniques.