Coupling modification of Fermi level, band flattening and lattice defects to approach outstanding thermoelectric performance of ZnO films via tuning In and Ga incorporation
Source abstract
Abstract
Band structure modification is found one of the state-of-the-art strategies to control electrical, thermal transport properties, and optimize performance of thermoelectric (TE) materials. Despite being a high-temperature n -type TE material, low-dimensional ZnO structures, specifically thin films normally possess a poor performance due to instability, low electrical, and high thermal conductivities. Herein, it is found that the trade-offs between TE parameters of ZnO films can be simultaneously abated by co-doping In and Ga. The dual incorporation of In and Ga enhances crystallinity, thermal stability, and TE properties up to 573 K. Tuning In and Ga contents not only optimizes carrier concentration associating with Fermi level modification, but also engineers lattice defects contributing to scattering transport mechanisms. Furthermore, the In 3+ compensation at substitutional sites, specifically at high temperature, significantly increases density-of-state effective mass due to conduction band flattening. As a result, the coupling modification of Fermi level, band flattening, and lattice defects leads to maintaining electrical conductivity at a medium degree, increasing Seebeck coefficient, and decreasing thermal conductivity, respectively. The TE dimensionless figure of merit ( ZT) and power factor ( PF) of the films deposited from the In 0.01Ga 0.04Zn 99.95O compound significantly boost to 0.2 and 745.2 µW/mK 2 at 573 K, respectively. These values are 1328 and 536% higher than pristine ZnO film; 400 and 258% greater than Ga single-doped ZnO film, respectively. It proposes that our ZnO-based thin films approach the high ZT region ( ZT ≥ 0.2) of advanced nanostructured ZnO-based bulks.
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Research context
OpenAlex topics: Advanced Thermoelectric Materials and Devices · ZnO doping and properties · Perovskite Materials and Applications
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (100+)
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