Abstract
Higher manganese silicide(HMS)is a P-type medium temperature thermoelectric(TE)material,which has attracted widespread attention over the past few decades due to its remarkable mechanical prop-erties,excellent chemical and thermal stability,as well as the non-toxicity,abundance and competitive price.The peak power factor(PF)of HMS is as high as～1.50×10-3 W m-1 K-2 because of its intrinsic high electrical conductivity and Seebeck coefficient.However,the thermal conductivity of HMS is also high,resulting in relatively low zT values.Introducing nano-dispersion in the matrix is one of the most effective methods to enhance the TE properties via reducing the lattice thermal conductivity significantly without drastic changes on the other parameters.In this study,CsPbBr3 QDs with uniform size were syn-thesized and introduced into HMS bulks.The PF(at 823 K)was enhanced to 1.71×10-3 W m-1 K-2,which is improved 14.0％approximately compared with that of pure HMS owing to the combined effect of element doping and energy filtering.The lattice thermal conductivity(at 823 K)decreased from 2.56 W m-1 K-1 to 1.99 W m-1 K-1 synchronously(～22.0％)due to the intensive phonon scattering caused by Cs doping,and the embedding of Pb riched CsPbBr3 QDs and Pb QDs.A maximum zT value of 0.57(823 K)is achieved in CsPbBr3 QDs/HMS composites,which is 36.0％higher than that of pure HMS.Pre-dictably,for other TE materials,it is also feasible to improve the TE properties via introducing metastable quantum dots.
基金项目
National Science Foundation for Young Scientists of China(51802071)
Advanced Talent Incubation Program of Hebei University(521000981162)
Outstanding Youth Science Foundation project of Hebei Province(A2020201032)
Local Science and Tech-nology Development Fund Projects Guided by the Central Govern-ment(206Z4403G)
Local Science and Tech-nology Development Fund Projects Guided by the Central Govern-ment(042000520091)
国家自然科学基金(51372064)
Hebei Province High-level Talents Funding project(A201801003)
Microanalysis Center and the High-Performance Computing Center of Hebei University()
NETL
NSTL
万方数据