Literature DB >> 32400768

Evolution of high-frequency Raman modes and their doping dependence in twisted bilayer MoS2.

Rahul Debnath1, Indrajit Maity1, Rabindra Biswas2, Varun Raghunathan2, Manish Jain1, Arindam Ghosh3.   

Abstract

Twisted van der Waals heterostructures provide a new platform for studying strongly correlated quantum phases. The interlayer coupling in these heterostructures is sensitive to the twist angle (θ) and key to controllably tuning several interesting properties. Here, we demonstrate the systematic evolution of the interlayer coupling strength with twist angle in bilayer MoS2 using a combination of Raman spectroscopy and classical simulations. At zero doping, we observe a monotonic increase in the separation between the A1g and E2g1 mode frequencies as θ decreases from 10° → 1°, and the separation approaches that of a bilayer at small twist angles. Furthermore, using doping dependent Raman spectroscopy, we reveal the θ dependent softening and broadening of the A1g mode, whereas the E2g1 mode remains unaffected. Using first principles based simulations, we demonstrate large (weak) electron-phonon coupling for the A1g (E2g1) mode, which explains the experimentally observed trends. Our study provides a non-destructive way to characterize the twist angle and the interlayer coupling and establishes the manipulation of phonons in twisted bilayer MoS2 (twistnonics).

Year:  2020        PMID: 32400768     DOI: 10.1039/c9nr09897f

Source DB:  PubMed          Journal:  Nanoscale        ISSN: 2040-3364            Impact factor:   7.790


  2 in total

1.  Temperature induced modulation of resonant Raman scattering in bilayer 2H-MoS2.

Authors:  Mukul Bhatnagar; Tomasz Woźniak; Łucja Kipczak; Natalia Zawadzka; Katarzyna Olkowska-Pucko; Magdalena Grzeszczyk; Jan Pawłowski; Kenji Watanabe; Takashi Taniguchi; Adam Babiński; Maciej R Molas
Journal:  Sci Rep       Date:  2022-08-19       Impact factor: 4.996

2.  Toward automated classification of monolayer versus few-layer nanomaterials using texture analysis and neural networks.

Authors:  Shrouq H Aleithan; Doaa Mahmoud-Ghoneim
Journal:  Sci Rep       Date:  2020-11-26       Impact factor: 4.379

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.