Coarse-Grained Molecular Dynamics(CGMD)法的精髓在於能以較少的節點數來取代多數的原子做運算，對於多重尺度(Multi-scale)的模擬，在能保持與分子動力學(Molecular Dynamics, MD)具有相似的模擬結果前提下，靈活地對系統做模擬尺度的變換，有效的降低模擬時間。本文將CGMD法應用於奈米壓痕(Nanoindentation)上，探討在不同效應下微觀結構的力學行為，並將其結果與MD相比較。 此法簡化粒子數的方式，是源於有限元素法(FEM)的權重函數(Weighting function)概念，而運動方程式的推導是由分子動力學經統計力學(Statistical mechanics)處理所求得，模擬不同尺度時則對其勢能函數做修正，因此不同尺度下，其理論基礎仍相同，然而在跨尺度模擬介面時所產生的不連續問題，也有其應對方法。 本研究探討CGMD法在不同溫度、速度、尺寸及材料效應下，透過奈米壓痕的(1)3D結構圖、(2)力量與深度關係圖、(3)基板材料之硬度與楊氏模數值、(4)缺陷結構圖的分析比較後，可發現CGMD模擬結果與MD會有相當接近的趨勢。模擬中並透過時間的監控，得到CGMD模擬時間約為MD的1/3，當模擬的尺寸越大時，兩者間時間的差異將會越來越明顯。

The significance of Coarse-Grained Molecular Dynamics (CGMD) is mainly established on its flexibility to perform the numerical computation with fewer nodes instead of all atoms. In multi-scale simulation, CGMD method can not only vary its scale to describe the system more flexible but also effectively save more computational cost than Molecular Dynamics (MD) on the promise that the simulation result can maintain as accurate as MD. This study applies CGMD to investigate the mechanical behavior of material in micro-scale under nanoindentation. Moreover, the results of CGMD are compared with MD. The concept of CGMD is to utilize the weighting function of Finite Element Method (FEM) to reduce the nodes. The equations of motion are also derived from Molecular Dynamics through statistical mechanics. Moreover, we modify and obtain the potential functions suitable for different scales. Therefore, the simulated systems are based on the same theories and the problems of seamless coupling between different scales can be easily solved. This work applies CGMD to nanoindentation process and investigates the effects of the temperature, the velocity, the size, and the material upon the results of (1) 3-D deformation configuration, (2) force-displacement curve, (3) substrate material’s hardness and Young’s modulus, as well as (4) the defects of structure. It can be concluded that CGMD can obtain the results as accurate as MD does. The computational time of CGMD takes only one-third as long as MD. Moreover, the larger the simulation system, the higher the efficiency of CGMD .

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