Computational Prediction to Two-Dimensional SnAs
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Abstract
By means of the particle-swarm optimization method and density functional theory calculations, the lowest-energy structure of SnAs is determined to be a bilayer stacking system and the atoms on top of each other are of the same types. Using the hybrid functional of Heyd–Scuseria–Ernzerhof, SnAs is calculated to be a semiconductor with an indirect band gap of 1.71 eV, which decreases to 1.42 eV with the increase of the bi-axial tensile stress up to 2%, corresponding to the ideal value of 1.40 eV for potential photovoltaic applications. Based on the deformation potential theory, the two-dimensional (2D) SnAs has high electron motilities along x and y directions (1.63\times10^3 cm^2V^-1s^-1). Our calculated results suggest that SnAs can be viewed as a new type of 2D materials for applications in optoelectronics and nanoelectronic devices.
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Dawei Zhou, Yangbing Zheng, Chunying Pu, Zhuo Wang, Xin Tang. Computational Prediction to Two-Dimensional SnAs[J]. Chin. Phys. Lett., 2018, 35(10): 107101. DOI: 10.1088/0256-307X/35/10/107101
Dawei Zhou, Yangbing Zheng, Chunying Pu, Zhuo Wang, Xin Tang. Computational Prediction to Two-Dimensional SnAs[J]. Chin. Phys. Lett., 2018, 35(10): 107101. DOI: 10.1088/0256-307X/35/10/107101
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Dawei Zhou, Yangbing Zheng, Chunying Pu, Zhuo Wang, Xin Tang. Computational Prediction to Two-Dimensional SnAs[J]. Chin. Phys. Lett., 2018, 35(10): 107101. DOI: 10.1088/0256-307X/35/10/107101
Dawei Zhou, Yangbing Zheng, Chunying Pu, Zhuo Wang, Xin Tang. Computational Prediction to Two-Dimensional SnAs[J]. Chin. Phys. Lett., 2018, 35(10): 107101. DOI: 10.1088/0256-307X/35/10/107101
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