Improved Thermoelectric Properties of Hot‐Extruded Bi–Te–Se Bulk Materials with Cu Doping and Property Predictions via Machine Learning

2019 ◽  
Vol 5 (6) ◽  
pp. 1900079 ◽  
Author(s):  
Zhi‐Lei Wang ◽  
Yuuki Yokoyama ◽  
Tetsuhiko Onda ◽  
Yoshitaka Adachi ◽  
Zhong‐Chun Chen
Author(s):  
Nattharika Theekhasuk ◽  
Rachsak Sakdanuphab ◽  
Pilaipon Nuthongkum ◽  
Prayoonsak Pluengphon ◽  
Adul Harnwunggmoung ◽  
...  

2013 ◽  
Vol 06 (05) ◽  
pp. 1340008 ◽  
Author(s):  
DALE HITCHCOCK ◽  
YEN-LIANG LIU ◽  
YUFEI LIU ◽  
TERRY M. TRITT ◽  
JIAN HE ◽  
...  

Over the past decade the widely used p-type ( Bi 2-x Sb x) Te 3 bulk thermoelectric materials have been subject to various nanostructuring processes for higher thermoelectric performance. However, these nanostructuring processing were conducted on compositions optimized for bulk materials (x ~ 1.52–1.55). This leads to the question of whether the optimal composition for bulk materials is the same for their nanoscale counterparts. In this work we hydrothermally grew Bi 2-x Sb x Te 3 nanopowders (nominally, x = 1.46, 1.48, 1.52 and 1.55) and measured their thermoelectric properties on cold-pressed vacuum-sintered pellets (74–78% of the theoretical density) below 300 K. The measurements were conducted 18 months apart to probe the aging phenomena, with the samples stored in ambient conditions. We have found that (i) the peak of thermopower shifts to lower temperatures upon nanostructuring but it shifts back to higher temperatures upon aging; (ii) the electrical conductivity degrades by a factor of 1.5–2.3 upon aging while the temperature dependence is largely retained; and (iii) the ZT of freshly made samples is sensitive to the x value, a maximum ZT ~ 1.25(~ 0.62) at ~ 270 K (~ 255 K) was attained in the freshly made sample x = 1.55(x = 1.46), respectively; while the ZT of aged samples is significantly lowered by a factor of 2–4 but lesser x-dependent. These observations have been discussed in the context of charge buildup and compensation at grain boundaries.


Author(s):  
Yong Hwan Kim ◽  
Yurian Kim ◽  
Hyun‐Sik Kim ◽  
Soon‐Mok Choi ◽  
Sang‐il Kim ◽  
...  

2020 ◽  
Vol 22 (28) ◽  
pp. 16165-16173
Author(s):  
Hangbo Zhou ◽  
Gang Zhang ◽  
Yong-Wei Zhang

We perform quantum master equation calculations and machine learning to investigate the thermoelectric properties of multiple interacting quantum dots, including electrical conductance, Seebeck coefficient, thermal conductance and ZT.


2017 ◽  
Vol 136 ◽  
pp. 111-114 ◽  
Author(s):  
Zhi-Lei Wang ◽  
Takahiro Akao ◽  
Tetsuhiko Onda ◽  
Zhong-Chun Chen

2017 ◽  
Vol 43 (8) ◽  
pp. 5920-5924 ◽  
Author(s):  
Jianping Zheng ◽  
Song Chen ◽  
Kefeng Cai ◽  
Junlin Yin ◽  
Shirley Shen

2010 ◽  
Vol 405 (24) ◽  
pp. 4931-4936 ◽  
Author(s):  
Weili Ren ◽  
Chunxia Cheng ◽  
Zhongming Ren ◽  
Yunbo Zhong

2006 ◽  
Vol 89 (5) ◽  
pp. 052111 ◽  
Author(s):  
P. C. Zhai ◽  
W. Y. Zhao ◽  
Y. Li ◽  
L. S. Liu ◽  
X. F. Tang ◽  
...  

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