Epitaxial formation of core–shell heterostructured Bi2Te3@Sb2Te3 hexagonal nanoplates
Source abstract
Abstract
The core–shell heterostructured Bi2Te3@Sb2Te3 hexagonal nanoplates with a thickness range of 22–26 nm were fabricated by a ligand auxiliary solution process. After complete ligand removal by a facile NH3-based procedure, the platelets are spark plasma-sintered to a good p-type nanostructured bulk material with crystal grain sizes preserved. Resultant crystal structures and microstructures were characterized by means of X-ray diffraction, scanning electron microscopy, transmission electron microscopy, high-resolution TEM, energy dispersed X-ray spectroscopy, selected area electron diffraction, and atomic force microscopy measurements. The influences of solvent ratios of H2O/ethylene glycol, molar concentration of source materials, and PVP on the formation of the core–shell structures were studied in detail. Based on the time-dependent experiment, a possible formation mechanism related to epitaxial attachment was presented for the growth of the core–shell heterostructured Bi2Te3@Sb2Te3 nanoplates. The thermoelectric Seebeck coefficient, S, is in the range of 133–171 μV K−1 and the electric conductivity for the Bi2Te3@Sb2Te3 is in the range of 48,400–79,200 S m−1. The final power factor is in the range of 0.97–2.04 mW m−1 K−2, which is close to those of physical method synthesized bulk pellets. Furthermore, this result is about several to tens of times higher than those of the recent reported works on chemically synthesized nanocrystalline pnictogen chalcogenide materials. These unique features of our core–shell nanoplates make them attractive for the manufacture of high-performance 3D-embedded matrixthermoelectric materials.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Advanced Thermoelectric Materials and Devices · Chalcogenide Semiconductor Thin Films · Thermal Radiation and Cooling Technologies
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (20)
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