Effects of substrate temperature and precursor separation on the morphology of ReS 2 nanoflakes prepared by chemical vapor deposition
Source abstract
Abstract
Abstract Rhenium disulfide (ReS 2 ) is a 2-dimensional transitional metal dichalcogenides that exhibits unique properties such as a direct band gap irrespective of thickness, weak interlayer coupling, and exceptional anisotropic properties, making it a promising material for optoelectronics applications. In this work, we synthesized ReS 2 nanoflakes on SiO 2 /Si substrates using chemical vapor deposition (CVD). The effects of Re precursor-substrate distance ( d ) and growth temperature on flakes morphology were systematically investigated. Field-effect scanning electron microscopy images revealed that shorter Re precursor-substrate distance ( d = 8 cm) favored the formation of high density and vertical flakes due to the high concentration of Re vapor. However, samples grown with the largest separation distance ( d = 11 cm) and higher substrate temperature (850 °C) demonstrated a low density of planar flakes. Raman spectroscopy measurements showed the E g , A g , and C p vibrational modes which belong to ReS 2 . The full-width-at-half-maximum of the E g mode at 212 cm −1 is 6.7 cm −1 , comparable to the mechanically exfoliated ReS 2 reference. The thicknesses of the flakes range from bilayer to multilayer and the measured band gap energy is ∼1.57 eV. The XPS data verified that the atomic ratio between Re and S is 1.9, which confirms the stoichiometry of the ReS 2 flakes. Finally, the TEM images and diffraction pattern confirmed that the ReS 2 flake is a single-crystal with distorted 1 T-phase. This work emphasizes the influence of CVD parameters on the morphology of ReS 2 flakes, which is vital for developing high performance ReS 2 based optoelectronics devices.
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Research context
OpenAlex topics: 2D Materials and Applications · Chalcogenide Semiconductor Thin Films · MXene and MAX Phase Materials
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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