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金属学报  2017, Vol. 53 Issue (8): 1018-1024    DOI: 10.11900/0412.1961.2017.00053
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深过冷液态金属Cu的热物理性质和原子分布
朱姜蕾, 王庆, 王海鹏()
西北工业大学应用物理系 西安 710072
Thermophysical Properties and Atomic Distribution of Undercooled Liquid Cu
Jianglei ZHU, Qing WANG, Haipeng WANG()
Department of Applied Physics, Northwestern Polytechnical University, Xi'an 710072, China
引用本文:

朱姜蕾, 王庆, 王海鹏. 深过冷液态金属Cu的热物理性质和原子分布[J]. 金属学报, 2017, 53(8): 1018-1024.
Jianglei ZHU, Qing WANG, Haipeng WANG. Thermophysical Properties and Atomic Distribution of Undercooled Liquid Cu[J]. Acta Metall Sin, 2017, 53(8): 1018-1024.

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摘要: 

针对液态金属Cu在深过冷亚稳条件下的热物理性质和液态结构数据缺乏的问题,采用分子动力学方法结合修正嵌入原子势,研究了常规液态和亚稳液态金属Cu的热物理性质(熔点、密度、比热容和自扩散系数)和原子分布规律,体系温度范围为800~2400 K,最大过冷度达到556 K。通过构建晶体-液体-晶体结构,探索了金属Cu的熔化过程,获得最优的熔点计算温度为1341 K,与实验值误差1.11%。获得了宽广温度范围内液态金属Cu的密度随温度的变化规律,采用Mishin势函数计算的熔点处密度模拟值为7.86 g/cm3,与文献报道的实验结果的误差小于2%。液态金属Cu的焓在800~2400 K范围内随温度呈线性关系变化,即比热容几乎不随过冷度变化而变化,而自扩散系数则随温度呈指数关系变化。根据不同温度原子的位置变化,获得了相应的双体分布函数,发现液态体系始终处于短程有序、长程无序的状态,且原子短程有序度随温度升高而降低,短程有序结构仅保持在3~4个原子间距范围内,且随间距增大而展现出典型的无序特征。

关键词 深过冷液态金属热物理性质双体分布函数    
Abstract

Cu is commonly used in the field of electricity and electronics because of its high ductility, and electrical and thermal conductivity. The thermophysical properties and the atomic structure of liquid Cu, especially for undercooled state, are of practical significance in both application and fundamental researches. The major approaches to obtain thermophysical properties of undercooled metals are containerless techniques based on electrostatic levitation, electromagnetic levitation and ultrasonic levitation et al. However, the strong volatility of liquid Cu results in great difficulties to measure the thermophysical properties. Accordingly, computational prediction is becoming an expected method to obtain the thermophysical data of liquid Cu. The molecular dynamics (MD) simulation, in combination with a resonable potential model, has been extensively employed in studying the physical properties of several metals as a powerful approach. In this work, the atomic distribution and thermophysical properties including melting temperature, density, specific heat and self-diffusion coefficient of liquid Cu were studied by molecular dynamics simulation. Mishin's and Zhou's embedded-atom method potentials, and the modified embedded-atom method potential proposed by Baskes were used over the temperature range of 800~2400 K, reaching the maximum undercooling of 556 K. The simulated results are in good agreement with the reported experimental results. The crystal-liquid-crystal sandwich structure has been used to calculate the melting point. The melting point calculated by Baskes' potential model is 1341 K, just a difference of 1.11% from the experimental value. The density at the melting point calculated by Mishin's potential is 7.86 g/cm3, with a difference less than 2% compared with the reported data. It is found that the enthalpy of liquid Cu increases linearly with the increase of temperature. The specific heat is obtained to be 31.89 J/(molK) by Mishin's potential, which is constant in the corresponding temperature range. The self-diffusion coefficient is exponentially dependent on the temperature. The maximum error between the reported value and the present value of the self-diffusion coefficient calculated by Mishin's potential is only 4.93%. The pair distribution function was applied to investigate the atomic structure of liquid Cu, which suggests that the simulated system is still ordered in short range and disordered in long range for both normal liquid and undercooled state. It is found that the atomic ordered degree is weakened with the increase of temperature, and it is kept within 3~4 atom neighbor distance.

Key wordsundercooling    liquid metal    thermophysical property    pair distribution function
收稿日期: 2017-02-20     
ZTFLH:  O469  
基金资助:国家自然科学基金项目Nos.51474175和51522102及陕西省工业科技攻关项目No.2015GY138
作者简介:

作者简介 朱姜蕾,女,1992年生,硕士生

图1  晶体-液体-晶体结构法计算Cu内能随温度的变化
图2  不同设定温度时体系相变过程
图3  液态Cu密度随温度的变化
图4  液态Cu的焓随温度的变化
图5  液态Cu自扩散系数随温度的变化
图6  液态Cu在900~2300 K温度范围内双体分布函数
图7  液态Cu双体分布函数的第一近邻和第二近邻峰值随温度变化关系
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