Efficiency at maximum power of thermoelectric heat engines with the symmetric semiconductor superlattice

TL;DR

This paper investigates the efficiency at maximum power (EMP) of thermoelectric heat engines using symmetric semiconductor superlattices, demonstrating near-theoretical limits through resonant tunneling and machine learning optimization.

Contribution

It introduces a superlattice-based approach to achieve high EMP close to theoretical limits, utilizing resonant tunneling and machine learning for optimization.

Findings

Over 95% of theoretical EMP can be achieved under optimal conditions.

Symmetric modes and Fabry-Pérot resonances enhance electron transmission.

Optimization of bias voltage and layer thickness improves power and efficiency.

Abstract

Efficiency at maximum power (EMP) is a very important specification for a heat engine to evaluate the capacity of outputting adequate power with high efficiency. It has been proved theoretically that the limit EMP of thermoelectric heat engine can be achieved with the hypothetical boxcar-shaped electron transmission, which is realized here by the resonant tunneling in the one-dimensional symmetric InP/InSe superlattice. It is found with the transfer matrix method that a symmetric mode is robust that regardless of the periodicity, and the obtained boxcar-like electron transmission stems from the strong coupling between symmetric mode and Fabry-P\'erot modes inside the allowed band. High uniformity of the boxcar-like transmission and the sharp drop of the transmission edge are both beneficial to the maximum power and the EMP, which are optimized by the bias voltage and the thicknesses of barrier and well. The maximum power and EMP are extracted with the help of machine learning technique, and more than 95% of their theoretical limits can both be achieved for smaller temperature difference, smaller barrier width and larger well width. We hope the obtain results could provide some basic guidance for the future designs of high EMP thermoelectric heat engines.