Micro scale rarefied gas transport attracts great research interests recently due to the special phenomena arising from small spatial scales, as well as its extensive applications in microelectromechanical systems. Due to the large surface-to-volume ratio at small scale, gas-surface interaction plays an important role in micro scale rarefied gas transport, which is currently described through empirical models and incorporated in various numerical methods for rarefied gas flow simulations. The validity of the empirical gas-surface interaction models needs systematic evaluation and the accommodation coefficients which are the adjustable parameters in the empirical models require to be determined through a feasible approach. These challenges of the existing empirical models form the two o...[ Read more ]

Micro scale rarefied gas transport attracts great research interests recently due to the special phenomena arising from small spatial scales, as well as its extensive applications in microelectromechanical systems. Due to the large surface-to-volume ratio at small scale, gas-surface interaction plays an important role in micro scale rarefied gas transport, which is currently described through empirical models and incorporated in various numerical methods for rarefied gas flow simulations. The validity of the empirical gas-surface interaction models needs systematic evaluation and the accommodation coefficients which are the adjustable parameters in the empirical models require to be determined through a feasible approach. These challenges of the existing empirical models form the two objectives of this thesis: 1) to validate the empirical gas-surface interaction models in typical micro scale rarefied gas transport problems based on the resolved macroscopic flow quantities; 2) to develop simple model for estimating accommodation coefficients.

First, an efficient hybrid DSMC-MD scheme is developed for the simulation of micro scale gas flows with accurate gas-surface interaction boundary condition. It applies molecular dynamics (MD) method in the thin gas-surface interaction layer and the direct simulation Monte Carlo (DSMC) method in the remaining portion of flow field. The coupling between the two methods is realized by matching the molecular velocity distribution function at the DSMC/MD interface. Further improvement in efficiency is achieved by taking advantage of gas rarefaction inside the gas-surface interaction layer and by employing the “smart-wall model”. The developed hybrid algorithm resolves the accurate macroscopic flow field and measures the accommodation coefficients at the same time. It provides the evaluation criterion for the performance of empirical gas-surface interaction models.

Secondly, a systematic study on the performance of two widely-used empirical gas-surface interaction models, the Maxwell model and the Cercignani-Lampis (CL) model, in the entire Knudsen range is conducted by examining the accuracy of key macroscopic quantities in typical rarefied gas transport problems commonly encountered in micro/nano systems. Maxwell model predicts qualitatively wrong trend of pressure profile and Knudsen force orientation due to the sole accommodation coefficient and scattering correlation it employs for all the velocity components. CL model performs better owning to its independent accommodation coefficients for different velocity components, but the over-constrained relation between the tangential momentum accommodation coefficient and tangential energy accommodation coefficient inherent in the model still leads the inaccurate thermal transpiration coefficient. Directions for further improvement of gas-surface interaction models are suggested.

Finally, a modified washboard model is developed as an efficient tool for estimating the tangential momentum accommodation coefficient (TMAC) of monotonic gas molecules scattering on atomically smooth surfaces. Reasonable approaches are proposed to determine the input parameters in washboard model, including the virtual surface which captures the turning point locations of gas molecules’ trajectories, the attractive potential well that governs the mean collision number of gas molecules with the surface and the effective solid cube mass which reflects the collective response of the solid atoms involved in the collision process. Two new physical processes, the soft collision and the non-uniform attractive potential well, are considered in the new model which significantly improve the accuracy of the model for estimating TMAC. Overall, by comparing with the molecular dynamics simulations, the modified washboard model is able to estimate TMAC on atomically smooth surface with relative error of 10% (absolute error of 0.02).