Bi2Te3热电器件的制备以及界面优化
Preparation of Bi2Te3 thermoelectric devices and interface optimization
王奕蘅 1卢嘉祺 1孙凯星 1薛天宇 1王博文 1夏聪 1夏明岗1
作者信息
- 1. 西安交通大学物理学院,陕西西安 710049
- 折叠
摘要
基于温差发电技术,利用仿真模拟和实验研究了Bi2Te3热电器件的制备以及界面的优化处理.通过计算机模拟建立热电器件模型,构建71对粒子组成的热电器件,模拟结果表明:在冷热端温差为150 ℃条件下产生的电动势约为4.37 V.采用氢等离子体清洗Bi2Te3粒子表面,利用X光电子能谱检测处理前后粒子的元素,发现氢等离子体清洗处理工艺可有效去除热电材料的氧化层.利用Sn膏将Bi2Te3半导体材料和Cu片无Pb焊接,制备热电器件,测试其发电效率,绘制效率随温差电阻变化图像.利用四点法测试氢等离子体处理前后的粒子电阻,发现接触电阻减小,说明界面氧化物含量减少,表面的缺陷程度降低.
Abstract
Based on thermoelectric generation technology,the preparation of Bi2Te3 thermoelectric devices and the interface optimization to improve their thermoelectric properties were studied using simulation and experiment.Firstly,the thermoelectric device model was established by computer sim-ulation.By constructing a thermoelectric device composed of 71 pairs of particles,the simulation re-sults showed that the electromotive force generated was about 4.37 V under the temperature differ-ence of 150℃ between the hot and cold ends.In the experiment,the surface of Bi2Te3 particles was deoxidated by hydrogen plasma cleaning,and the elements before and after the treatment were detec-ted by X-ray photoelectron spectroscopy.It was found that the hydrogen plasma cleaning process could effectively remove the oxide layer of thermoelectric materials.Then,lead-free soldering of Bi2Te3 semiconductor material and copper sheet with solder paste was used to prepare thermoelectric devices.The power generation efficiency of thermoelectric devices was tested by using the built test device,and the image of efficiency changing with temperature difference resistance was drawn.Final-ly,the four-point method was used to test the particle resistance before and after hydrogen plasma cleaning,and it was found that the contact resistance decreased,indicating that the interface oxide content was reduced and the degree of surface defects was decreased.
关键词
Bi2Te3热电器件/氢等离子清洗/界面优化/表征元素分析Key words
Bi2Te3 thermoelectric devices/hydrogen plasma cleaning/interface optimization/characterization element analysis引用本文复制引用
出版年
2024
NETL
NSTL
万方数据