2020
DOI: 10.1039/c9ra10087c
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HfS2/MoTe2 vdW heterostructure: bandstructure and strain engineering based on first-principles calculation

Abstract: In this study, a multilayered van der Waals (vdW) heterostructure, HfS2/MoTe2, was modeled and simulated using density functional theory (DFT).

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Cited by 29 publications
(10 citation statements)
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“…Under ambient conditions, the calculated bandgap energy was 0.92 eV, which is smaller than the previous result with a bandgap energy of 1.23 eV. 34 Density functional theory (DFT) calculations generally underestimate the bandgap energy of TMDs, and thus, a slight discrepancy in bandgap energy is tolerated. 35 From Fig.…”
Section: Resultscontrasting
confidence: 58%
“…Under ambient conditions, the calculated bandgap energy was 0.92 eV, which is smaller than the previous result with a bandgap energy of 1.23 eV. 34 Density functional theory (DFT) calculations generally underestimate the bandgap energy of TMDs, and thus, a slight discrepancy in bandgap energy is tolerated. 35 From Fig.…”
Section: Resultscontrasting
confidence: 58%
“…Some studies have suggested several candidate materials such as heterostructures, or monolayer systems. [27][28][29] For instance, the highly stable Hf 2 CO 2 is a semiconducting material with an energy gap of B1.70 eV. Narrowing its energy gap makes it suitable for infrared or thermoelectric applications, whereas opening the gap makes power electronics and optoelectronic functionality accessible.…”
Section: Introductionmentioning
confidence: 99%
“…Bandgap (in eV) comparison between the value calculated here using HSE06 and other HSE06 calculations found in the literature. [58][59][60] Discrepancies may result from different methodologies used in the approximation of the vdW potential and/or configuration of the supercells used. .72 1.39 [58] OTl 2 -GeI 2 1.83 1.45 [58] Br 2 Mg-Cl 2 Zn 5.50 5.49 [58] Cl 2 Zn-CdCl 2 5.10 5.29 [58] OTl 2 -O 2 Pt 0.62 0.86 [58] I 2 Yb-Br 2 Ge 1.30 1.04 [58] InSe/AsP 1.26 1.07 [59] HfS 2 /MoTe 2 0.59 0.35 [60] across the UMAC, the 2.2M structures predicted by the ML models lie within the domain of applicability for the model, so should be predicted with reasonable accuracy.…”
Section: Resultsmentioning
confidence: 99%