Optimization of Thermal Conductance at Interfaces Using Machine Learning Algorithms.

Optimization of thermal transport across the interface of two different materials is critical to micro-/nanoscale electronic, photonic, and phononic devices. Although several examples of compositional intermixing at the interfaces having a positive effect on interfacial thermal conductance (ITC) have been reported, an optimum arrangement has not yet been determined because of the large number of potential atomic configurations and the significant computational cost of evaluation. On the other hand, computation-driven materials design efforts are rising in popularity and importance. Yet, the scalability and transferability of machine learning models remain as challenges in creating a complete pipeline for the simulation and analysis of large molecular systems. In this work we present a scalable Bayesian optimization framework, which leverages dynamic spawning of jobs through the Message Passing Interface (MPI) to run multiple parallel molecular dynamics simulations within a parent MPI job to optimize heat transfer at the silicon and aluminum (Si/Al) interface. We found a maximum of 50% increase in the ITC when introducing a two-layer intermixed region that consists of a higher percentage of Si. Because of the random nature of the intermixing, the magnitude of increase in the ITC varies. We observed that both homogeneity/heterogeneity of the intermixing and the intrinsic stochastic nature of molecular dynamics simulations account for the variance in ITC.

Effect of graphitic anode surface functionalization on the structure and dynamics of electrolytes at the interface.

Surface termination on a graphitic surface and the type of electrolytes in lithium-ion batteries (LIBs) play an important part in determining the structure, composition, and thus, the quality of the emergent solid electrolyte interphase. In this paper, we analyze the structure and dynamics of electrolyte molecules in multi-component electrolyte with varying species compositions combinatorially paired with four different graphitic surfaces terminated with hydrogen, hydroxyl, carbonyl, and carboxyl to explore the interplay between surface chemistry and electrolyte dynamics at electrode/electrolyte interfaces. Addition of dimethyl carbonate and fluoroethylene carbonate brought substantial changes in the ethylene carbonate (EC) and LiPF6 surface population density for hydroxyl and carbonyl surfaces. Strong density oscillation and drastic slowing of the dynamics of the electrolyte molecules at the interface are reported for all the systems. While these observations are universal, carboxyl surfaces have the strongest local and long-range effects. Characterization of the average dipole direction at the interface shows strong orientational preferences of ethylene carbonate molecules. EC molecules are preferred to be oriented either almost parallel or perpendicular to the hydroxyl surface, are tilted between parallel and perpendicular with a higher angle of incidence of the dipole vs surface normal on the carbonyl surface than on the hydroxyl surface, and are oriented perpendicularly against the carboxyl surface. These differences highlight the significant effect of graphite surface termination on the dynamics of the electrolytes and provide insight into the complex interplays between electrolyte species and graphite anode in LIBs.