Jialin's recent paper "Atomistic simulation of the formation and fracture of oxide bifilms in cast aluminum" Acta Materialia, volume 164 (2019) page 673-682 was picked and featured by 
for the field of Materials Engineering.
This work was in collabration with Dr. Qigui Wang at General Motors. In this paper, we applied reactive molecular dynamics (MD) simulations to understand the atomistic details of the formation and fracture of aluminum oxide bifilms, which are inevitable to form and harmful to the mechanical properties of cast aluminum parts, such as the engines. Unfortunately, neither the formation process nor fracture mechanism is fully understood due to the difficulty of in-situ observation on nano-scale aluminum oxide thin film.
This work was the first study to quantify the fracture properties of oxide bifilms at different aging stage and/or different chemical environments. Moreover, these predictions can serve as inputs to a multiscale modeling framework to simulate the oxides distributions in the casting process and the fracture of the casted components during operation.
Jialin finished his PhD in 2019 spring and joined 3M Corporate Research System Lab as a research scientist. Currently, he is working on implementing machine learning and deep learning tools in atomic modeling techniques for more accurate prediction and high-throughput new material designing.