Layer-modulated two-photon absorption in MoS<sub>2</sub>: probing the shift of the excitonic dark state and band-edge

Xie, Yafeng; Zhang, Saifeng; Dong, Ningning; Zhang, Xiaoyan; Wang, Lei; Liu, Weimin; Kislyakov, I. M.; Nunzi, Jean‐Michel; Hu, Qi; Zhang, Long; Wang, Jun

doi:10.1364/prj.7.000762

Cited by 30 publications

(21 citation statements)

References 57 publications

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“…As shown in Figure 1c, two Raman-active modes, E 1 2g and A 1g , exhibit significant differences, and the Raman frequency difference of the monolayer sample is~17.9 cm −1 , while that of the bilayer sample is~21.1 cm −1 . This is consistent with previous results for mechanical exfoliation (ME)-prepared and CVD-prepared samples, implying this difference is universal between samples obtained from different preparation methods [35][36][37]. The cracks nucleated at sulfur vacancies propagate along the energy-favored zigzag directions upon the relatively fast temperature-drop-induced thermal strain, which results in an orientation-specific fracture behavior [38].…”

Section: Resultssupporting

confidence: 90%

Machine Learning Analysis of Raman Spectra of MoS2

et al. 2020

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Defects introduced during the growth process greatly affect the device performance of two-dimensional (2D) materials. Here we demonstrate the applicability of employing machine-learning-based analysis to distinguish the monolayer continuous film and defect areas of molybdenum disulfide (MoS2) using position-dependent information extracted from its Raman spectra. The random forest method can analyze multiple Raman features to identify samples, making up for the problem of not being able to effectively identify by using just one certain variable with high recognition accuracy. Even some dispersed nucleation site defects can be predicted, which would commonly be ignored under an optical microscope because of the lower optical contrast. The successful application for classification and analysis highlights the potential for implementing machine learning to tap the depth of classical methods in 2D materials research.

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Section: Resultssupporting

confidence: 90%

Machine Learning Analysis of Raman Spectra of MoS2

et al. 2020

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“…From the spectral positions, we estimate exciton BE of 0.1 ± 0.007 eV of A,1s excitons [28,29]. Recent reports on bulk and multi-layered TMDC [30,31] estimate similar values.…”

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confidence: 63%

Observation of Dynamic Screening in the Excited Exciton States in Multi-layered MoS$_2$

Karmakar,

Bhattacharya,

Mukherjee

et al. 2021

Preprint

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Excitonic resonance and binding energies can be altered by controlling the environmental screening of the attractive Coulomb potential. Although this screening response is often assumed to be static, the time evolution of the excitonic quasiparticles manifests a frequency-dependence in its Coulomb screening efficacy. In this letter, we investigate a ground (1s) and first excited exciton state (2s) in a multi-layered transition metal dichalcogenide (MoS2) upon ultrafast photo-excitation. We explore the dynamic screening effects on the latter and show its resonance frequency is the relevant frequency at which screening from the smaller-sized 1s counterparts is effective. Our finding sheds light on new avenues of external tuning on excitonic properties.

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“…In addition, it was found that the TPA coefficient of PdSe 2 gradually decreased with the increasing of layers. Such a phenomenon was mainly attributed to the fact that the bandgap decreased with the increase of the number of layers, and there was a certain detuning between the formative exciton and the two-photon energy 53 .…”

Section: Resultsmentioning

confidence: 99%

Giant nonlinear optical activity in two-dimensional palladium diselenide

Kuang

et al. 2021

Nat Commun

105

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Nonlinear optical effects in layered two-dimensional transition metal chalcogenides have been extensively explored recently because of the promising prospect of the nonlinear optical effects for various optoelectronic applications. However, these materials possess sizable bandgaps ranging from visible to ultraviolet region, so the investigation of narrow-bandgap materials remains deficient. Here, we report our comprehensive study on the nonlinear optical processes in palladium diselenide (PdSe2) that has a near-infrared bandgap. Interestingly, this material exhibits a unique thickness-dependent second harmonic generation feature, which is in contrast to other transition metal chalcogenides. Furthermore, the two-photon absorption coefficients of 1–3 layer PdSe2 (β ~ 4.16 × 105, 2.58 × 105, and 1.51 × 105 cm GW−1) are larger by two and three orders of magnitude than that of the conventional two-dimensional materials, and giant modulation depths (αs ~ 32%, 27%, and 24%) were obtained in 1–3 layer PdSe2. Such unique nonlinear optical characteristics make PdSe2 a potential candidate for technological innovations in nonlinear optoelectronic devices.

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Layer-modulated two-photon absorption in MoS₂: probing the shift of the excitonic dark state and band-edge

Cited by 30 publications

References 57 publications

Machine Learning Analysis of Raman Spectra of MoS2

Machine Learning Analysis of Raman Spectra of MoS2

Observation of Dynamic Screening in the Excited Exciton States in Multi-layered MoS$_2$

Giant nonlinear optical activity in two-dimensional palladium diselenide

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Layer-modulated two-photon absorption in MoS2: probing the shift of the excitonic dark state and band-edge

Cited by 30 publications

References 57 publications

Machine Learning Analysis of Raman Spectra of MoS2

Machine Learning Analysis of Raman Spectra of MoS2

Observation of Dynamic Screening in the Excited Exciton States in Multi-layered MoS$_2$

Giant nonlinear optical activity in two-dimensional palladium diselenide

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Layer-modulated two-photon absorption in MoS₂: probing the shift of the excitonic dark state and band-edge