Thermoelectric figure of merit $zT$ vs carrier concentration $n$ for \ch{Bi2Te3} based on empirical data in ref.~\cite{rowe_alpha-sigma_1995}. Tuning $n$ for optimal $zT$ involves a compromise between thermal conductivity $\kappa$, Seebeck coefficient $S$ and electrical conductivity $\sigma$.
Increasing the electrical conductivity $\sigma$ not only produces an increase in the electronic thermal conductivity $\kappa_\text{el}$ but also usually decreases the Seebeck coefficient $S$. This makes optimal $\zT$ difficult to achieve. Plot scales are $\kappa/\si{\watt\per\meter\per\kelvin} \in [0,10]$, $S/\si{\micro\volt\per\kelvin} \in [0,500]$, $\sigma/\si{\per\ohm\per\centi\meter} \in [0,5000]$.
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% Thermoelectric figure of merit $zT$ vs carrier concentration $n$ for \ch{Bi2Te3} based on empirical data in ref.~\cite{rowe_alpha-sigma_1995}. Tuning $n$ for optimal $zT$ involves a compromise between thermal conductivity $\kappa$, Seebeck coefficient $S$ and electrical conductivity $\sigma$. Increasing the electrical conductivity $\sigma$ not only produces an increase in the electronic thermal conductivity $\kappa_\text{el}$ but also usually decreases the Seebeck coefficient $S$. This makes optimal $\zT$ difficult to achieve. Plot scales are $\kappa/\si{\watt\per\meter\per\kelvin} \in [0,10]$, $S/\si{\micro\volt\per\kelvin} \in [0,500]$, $\sigma/\si{\per\ohm\per\centi\meter} \in [0,5000]$.
\documentclass[tikz]{standalone}
\usepackage{pgfplots,siunitx}
\pgfplotsset{compat=newest}
\begin{document}
\begin{tikzpicture}
\begin{axis}[
xmode=log,
domain=1e17:1e21,
ymax=1,
enlargelimits=false,
ylabel=$zT$,
xlabel=Carrier concentration $n$ (\si{\per\centi\meter\cubed}),
grid=both,
width=12cm,
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\end{document}
Click to download: zt-vs-n.tex
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This file is available on tikz.netlify.app and on GitHub and is MIT licensed.
See more on the author page of Janosh Riebesell..
