藉超快形狀辨識技術及瞬間正則模分析探討金屬叢集熔化行為

Abstract

我們探討八種不同原子數目的金屬鋅叢集的熔化行為，分別是 〖Zn〗_n (n=6, 13, 29, 33, 39, 42, 49, 53)。利用Brownian-type isothermal的分子動力模擬搭配Gupta-type位能產生金屬鋅叢集從低溫至高溫的組態。這八種不同原子數目的鋅叢集的比熱和Lindemann-like參數隨溫度的變化呈現不尋常的轉變；這不尋常的轉變在物理上是有趣的，所以在本論文中加以探索。在本論文中有兩種分析方法，分別為超快形狀辨識技術及瞬間正則模分析。這兩種方法都能夠有效的運用在分析金屬鋅叢集的結構。超快形狀辨識技術的概念著重於，將在一溫度的叢集結構與最低能量狀態的叢集結構做比較。瞬間正則模分析著重於，對在一溫度下所有叢集組態平均，而得到叢集的瞬間震動頻譜。計算的結果顯示，超快形狀辨識技術及瞬間正則模分析皆能夠更進一步指示鋅叢集的結構相變，並能解釋鋅叢集比熱隨溫度的變化。

We investigated the melting behaviors of Zn metallic clusters with eight different atom numbers n =6, 13, 29, 33, 39, 42, 49 and 53. The Zn cluster configurations at low and high temperatures were generated by the Brownian-type isothermal molecular dynamic (MD) simulations with the empirical Gupta-type potential. The temperature variations in the specific heat C_v (T) and the Lindemann-like parameter δ(T) both exhibit unusual transitions of Zn cluster of each size. These unusual transitions are interesting things and explored in this thesis, in order to understand the phase transition of Zn clusters. The ultrafast shape recognition technique (USRT) and the instantaneous normal mode (INM) analysis were used to analyze the structures of Zn clusters. The USRT emphasizes on comparing the similarity between cluster structures at a given temperature and the structure at the lowest energy state; the INM analysis lays an emphasis on the vibrational INM spectrum, which is an ensemble average over cluster configurations at this temperature. According to the results in this thesis, both the USRT and the INM analysis provide insights into the phase transitions of Zn clusters with eight different atom numbers for understanding their respective specific heat.