Mg2Si1-xSnx合金热电性能的第一性原理计算预测

doi:10.11896/cldb.19120244

材料导报

2020, Vol. 34

Issue (18): 18098-18103 https://doi.org/10.11896/cldb.19120244

金属与金属基复合材料

Mg₂Si_1-xSn_x合金热电性能的第一性原理计算预测

李鑫, 谢辉, 魏鑫, 张亚龙

西安航空学院材料工程学院,西安 710077

Thermoelectric Properties Prediction of Mg₂Si_1-xSn_x Alloys by First Principle Calculation

LI Xin, XIE Hui, WEI Xin, ZHANG Yalong

School of Materials Engineering, Xi'an Aeronautical University, Xi'an 710077, China

摘要
参考文献
相关文章
推荐阅读
Metrics

下载:

全文 ( PDF ) ( 6650KB )
输出: BibTeX | EndNote (RIS)

摘要作为最具潜质的中温区热电材料之一,Mg₂Si_1-xSn_x基合金由于其低廉的成本和无毒无害等优点,在过去十几年受到广泛关注。Si和Sn原子间具有较大的质量差,有利于声子的合金化散射,使得晶格热导率极大降低(可达到1.8 W·m^-1·K^-1),解决了二元Mg₂Sn合金热导率较高的问题。大多数Mg₂Si_1-xSn_x合金通过降低晶粒尺寸来进一步降低晶格热导率,从而优化热电性能,然而,这类材料制备的热电器件在高温服役过程中容易出现由于晶粒长大导致的性能降低。因此,通过提高功率因子,如掺杂、能带工程等方法,来优化热电性能是更加可靠的路径。本工作采用第一性原理计算方法,对不同Sn成分的Mg₂Si_1-xSn_x(0.25≤x≤0.75)固溶体进行电子结构分析和热电性能预测。结果表明,在x=0.625时产生了能带收敛效应,可以在不影响电导率的前提下有效提高Seebeck系数值。计算预测的Seebeck系数在掺杂浓度为3×10²⁰ cm^-3时取得最大值-246 μV·K^-1,功率因子最高可达6.2 mW·m^-1·K^-2,不同温度下的Seebeck系数和电导率预测结果与高温度梯度定向凝固试样测试所得的结果拟合较好。根据测试所得的热导率结果,在T=700 K处计算预测的最大ZT值为1.3,而实验测试值为1.16,同时,在中温区550~800 K之间预测和实验测试的ZT值分别可以保持在1.0和0.9以上。因此,通过优化功率因子的方法可以有效提高Mg₂Si_1-xSn_x晶体的热电性能,为此类热电材料的性能优化提供了新的思路。

	服务
	把本文推荐给朋友
	加入引用管理器
	E-mail Alert
	RSS
	作者相关文章
	李鑫
	谢辉
	魏鑫
	张亚龙

关键词: 第一性原理计算 Mg₂Si_1-xSn_x 热电性能定向凝固

Abstract: As one of the most potential medium temperature thermoelectric materials, Mg₂Si_1-xSn_x -based alloy has received widely attention due to the advantage of low cost and non-toxic. Lattice thermal conductivity of ternary Mg₂Si_1-xSn_x alloys is reduced, because alloying scattering is enhanced by the large mass difference of elements. The minimum of thermal conductivity is 1.8 W·m^-1·K^-1, and it well resolves the disadvantage of high thermal conductivity for Mg₂Sn binary alloys. However, the main methods to optimize the thermoelectric properties of Mg₂Si_1-xSn_x alloys are decreasing the grain size to further reduce the thermal conductivity. But the performance of this kind of thermoelectric device is prone to degradation due to the grain growth in high temperature service. Therefore, improving the power factor by the method of doping and band engineering is a more reliable way to optimize the thermoelectric performance. In this paper, electronic structures analysis and thermoelectric properties prediction has been made to the Mg₂Si_1-xSn_x (0.25≤x≤0.75) compounds by first principle calculation method. The calculated band structures in Mg₂Si_1-xSn_x show the conduction band convergence directly. This convergence in energy at x=0.625 can enhance the Seebeck coefficient of the solid solution without influencing the electrical conductivity. The Seebeck coefficient and power factor of Mg₂Si_0.375Sn_0.625 could reach -246 μV·K^-1 and 6.2 mW·m^-1·K^-2, respectively, at the optimal doping density of 3×10²⁰ cm^-3. The predicted and tested results of ZT maximum are 1.3 and 1.16 at T=700 K, respectively. In the medium temperature range of 550—800 K, the predicted and tested ZT values can keep above 1.0 and 0.9, respectively. Therefore, power factor optimization is an effective way to improve the thermoelectric properties of Mg₂Si_1-xSn_x crystal.

Key words: first principle calculation Mg₂Si_1-xSn_x thermoelectric properties directional solidification

发布日期: 2020-09-12

ZTFLH:

TG146.2+2

基金资助: 国家自然科学基金委青年项目(51904219);西安航空学院校级科研基金项目(2019KY0203)

通讯作者: lixin005@xaau.edu.cn

作者简介: 李鑫,2018年6月毕业于西北工业大学材料学院,获得工学博士学位。现为西安航空学院材料工程学院讲师。目前主要研究领域为定向凝固、热电材料和第一性原理计算。

引用本文:

李鑫, 谢辉, 魏鑫, 张亚龙. Mg₂Si_1-xSn_x合金热电性能的第一性原理计算预测[J]. 材料导报, 2020, 34(18): 18098-18103.
LI Xin, XIE Hui, WEI Xin, ZHANG Yalong. Thermoelectric Properties Prediction of Mg₂Si_1-xSn_x Alloys by First Principle Calculation. Materials Reports, 2020, 34(18): 18098-18103.

链接本文:

http://www.mater-rep.com/CN/10.11896/cldb.19120244 或 http://www.mater-rep.com/CN/Y2020/V34/I18/18098

1 Fan W B, Chen S P, Zeng B, et al. ACS Applied Materials & Interfaces, 2017, 34(9), 28635.
2 Deng R G, Su X L, Hao S Q, et al. Energy & Environmental Science, 2018, 11(6), 1520.
3 Yin K, Su X L, Yan Y G, et al. Scripta Materials, 2017, 126, 1.
4 Snyder G J, Toberer E S. Nature Materials, 2008, 7(2), 105.
5 Chang C, Wu M H, He D S, et al. Science, 2018, 360, 778.
6 Chen X X, Wu H J, Cui J, et al. Nano Energy, 2018, 52, 246.
7 Shi X, Chen L D. Nature Materials, 2016, 15(7), 691.
8 Zhao L D, Tan G J, Hao S Q, et al. Science, 2016, 351(6269), 141.
9 Li X, Li S M, Feng S K. Intermetallics, 2017, 81, 26.
10 Zhang Q, Zhao X B, Yin H, et al. Rare Metal Materials and Engineering, 2009, 38(z1), 165(in Chinese).
张倩, 赵新兵, 殷浩, 等. 稀有金属科学与工程, 2009, 38(z1):165.
11 Bahk J, Bian Z X, Shakouri A. Physics Review B, 2014, 89(7), 75204.
12 Liu W, Tang X F, Li H, et al. Chemistry of Materials, 2011, 23(23), 5256.
13 Gao P, Lu X, Burken I, et al. Applied Physics letters, 2014, 105, 202104.
14 Zhang Q, Zheng Y, Su X L, et al. Scripta Materials, 2015, 96, 1.
15 Bellanger P, Gorsse S, Bernard-Granger G, et al. Acta Materialia, 2015, 95, 102.
16 Liu W S, Kim H S, Jie Q, et al. Scripta Materials, 2016, 111, 3.
17 Feng S K, Li S M, Fu H Z. Chinese Physics B, 2014, 23(8), 086301.
18 Zhao L D, Tan G, Hao S, et al. Science, 2016, 351(6269), 141.
19 Liu Y, Hu W C, Li D J, et al. Physica Scripta, 2013,88(4), 045302.
20 Petrova L I, Abrikosov N K, Dudkin L D, et al. Inorganic Materials, 1990, 26(6), 1023.
21 Marlo M, Milman V. Physics Review B, 2000, 62(4), 2899.
22 Vanderbilt D. Physics Review B, 1990, 41(11), 7892.
23 Schwarz K, Blaha P. Computational Materials Science, 2003, 28(2), 259.
24 Scheidemantel T J, Ambrosch-Draxl C, Thonhauser T, et al. Physical Review B, 2003, 68(12), 125210.
25 Madsen G K H, Singh D J. Computer Physics Communications, 2006, 175(1), 67.
26 Li X, Li S M, Feng S K, et al. Journal of Electronic Materials, 2016, 45(6), 2895.
27 Pei Y Z, Shi X, LaLonde A, et al. Nature, 2011, 473(7345), 66.
28 Zhang Q, He J, Zhu T J, et al. Applied Physics Letters, 2008, 93(10), 102109.

[1]	李鑫, 谢辉, 杨宾, 李双明. Mg₂(Si,Sn)基热电材料研究进展[J]. 材料导报, 2020, 34(Z1): 43-47.
[2]	申兰先, 陈家莉, 李德聪, 刘文婷, 葛文, 邓书康. Yb掺杂Ⅷ型Yb_xBa_8-xGa₁₆Sn₃₀笼合物的制备及热电性能[J]. 材料导报, 2020, 34(8): 8136-8140.
[3]	徐彪, 付上朝, 赵仕俊, 贺新福. 高熵合金辐照性能的计算机模拟进展[J]. 材料导报, 2020, 34(17): 17031-17040.
[4]	马文彬, 郭京京, 骆红云, 唐君, 杨晓光. 低塑性加工对定向凝固镍基合金DZ125高温氧化性能的影响[J]. 材料导报, 2020, 34(10): 10093-10097.
[5]	杨金祥, 石爽, 姜大川, 李旭, 李鹏廷, 谭毅, 姚玉杰, 池明, 张润德, 张建帅. 多晶硅定向凝固过程中温度对凝固速率的影响[J]. 材料导报, 2019, 33(z1): 28-32.
[6]	龙亮, 刘炳刚, 罗昊, 鲜亚疆. 碳化硼的研究进展[J]. 材料导报, 2019, 33(z1): 184-190.
[7]	王怡心, 马勤, 贾建刚, 高昌琦, 张瑄瑄. Half-Heusler热电材料性能优化策略及研究进展[J]. 材料导报, 2019, 33(z1): 403-407.
[8]	卢百平, 崔春娟, 田露露, 问亚岗, 王佩. 布里奇曼定向凝固Ni-12%Si过共晶的弹性模量与断裂韧性[J]. 材料导报, 2019, 33(8): 1383-1388.
[9]	王晓娟, 刘林, 赵新宝, 黄太文, 杨文超, 张军, 傅恒志. 添加碳和硼改善第三代镍基定向凝固高温合金的显微组织和偏析行为[J]. 材料导报, 2019, 33(20): 3452-3459.
[10]	莫晓华, 蒋卫卿. Fe、Co和Ni掺杂LiBH₄放氢性能的第一性原理研究[J]. 材料导报, 2019, 33(2): 225-229.
[11]	朱靖, 李勇, 王莹, 李焕, 赵亚茹. 不同定向凝固速率下Cu-2.5%Cr合金中带状组织的形成机理[J]. 材料导报, 2019, 33(2): 309-313.
[12]	李佳琪, 刘光华, 吴晓明, 贺刚, 杨增朝, 李江涛. 混料方式对燃烧合成Cu₂Se的热电性能的影响[J]. 材料导报, 2019, 33(18): 3147-3151.
[13]	魏岑,李向明. 一种不稳定的共晶生长方式:倾斜共晶生长的研究进展[J]. 材料导报, 2019, 33(15): 2532-2537.
[14]	李怀明, 孙秋, 宋英. W掺杂对Zn_0.98Al_0.02O陶瓷热电性能的影响[J]. 材料导报, 2019, 33(12): 1959-1962.
[15]	袁大超, 郭双, 郝建军, 马跃进, 王淑芳. 脉冲激光沉积c轴取向BiCuSeO外延薄膜及其热电性能[J]. 材料导报, 2019, 33(1): 152-155.

[1]	Wei ZHOU, Xixi WANG, Yinlong ZHU, Jie DAI, Yanping ZHU, Zongping SHAO. A Complete Review of Cobalt-based Electrocatalysts Applying to Metal-Air Batteries and Intermediate-Low Temperature Solid Oxide Fuel Cells[J]. Materials Reports, 2018, 32(3): 337 -356 .
[2]	Yanzhen WANG, Mingming CHEN, Chengyang WANG. Preparation and Electrochemical Properties Characterization of High-rate SiO₂/C Composite Materials[J]. Materials Reports, 2018, 32(3): 357 -361 .
[3]	Yimeng XIA, Shuai WU, Feng TAN, Wei LI, Qingmao WEI, Chungang MIN, Xikun YANG. Effect of Anionic Groups of Cobalt Salt on the Electrocatalytic Activity of Co-N-C Catalysts[J]. Materials Reports, 2018, 32(3): 362 -367 .
[4]	Dongyong SI, Guangxu HUANG, Chuanxiang ZHANG, Baolin XING, Zehua CHEN, Liwei CHEN, Haoran ZHANG. Preparation and Electrochemical Performance of Humic Acid-based Graphitized Materials[J]. Materials Reports, 2018, 32(3): 368 -372 .
[5]	Huanchun WU, Fei XUE, Chengtao LI, Kewei FANG, Bin YANG, Xiping SONG. Fatigue Crack Initiation Behaviors of Nuclear Power Plant Main Pipe Stainless Steel in Water with High Temperature and High Pressure[J]. Materials Reports, 2018, 32(3): 373 -377 .
[6]	Miaomiao ZHANG,Xuyan LIU,Wei QIAN. Research Development of Polypyrrole Electrode Materials in Supercapacitors[J]. Materials Reports, 2018, 32(3): 378 -383 .
[7]	Qingshun GUAN,Jian LI,Ruyuan SONG,Zhaoyang XU,Weibing WU,Yi JING,Hongqi DAI,Guigan FANG. A Survey on Preparation and Application of Aerogels Based on Nanomaterials[J]. Materials Reports, 2018, 32(3): 384 -390 .
[8]	Yunzi LIU,Wei ZHANG,Zhanyong SONG. Technological Advances in Preparation and Posterior Treatment of Metal Nanoparticles-based Conductive Inks[J]. Materials Reports, 2018, 32(3): 391 -397 .
[9]	Bingwei LUO,Dabo LIU,Fei LUO,Ye TIAN,Dongsheng CHEN,Haitao ZHOU. Research on the Two Typical Infrared Detection Materials Serving at Low Temperatures: a Review[J]. Materials Reports, 2018, 32(3): 398 -404 .
[10]	Lanyan LIU,Jun SONG,Bowen CHENG,Wenchi XUE,Yunbo ZHENG. Research Progress in Preparation of Lignin-based Carbon Fiber[J]. Materials Reports, 2018, 32(3): 405 -411 .

Viewed

Full text

Abstract

Cited

Shared

Discussed