Atomistic Probing of Defect-Engineered 2H-MoTe2 Monolayers

  • Odongo Francis Ngome Okello
  • , Dong Hwan Yang
  • , Seung Young Seo
  • , Jewook Park
  • , Gunho Moon
  • , Dongwon Shin
  • , Yu Seong Chu
  • , Sejung Yang
  • , Teruyasu Mizoguchi
  • , Moon Ho Jo
  • , Si Young Choi

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

Point defects dictate various physical, chemical, and optoelectronic properties of two-dimensional (2D) materials, and therefore, a rudimentary understanding of the formation and spatial distribution of point defects is a key to advancement in 2D material-based nanotechnology. In this work, we performed the demonstration to directly probe the point defects in 2H-MoTe2 monolayers that are tactically exposed to (i) 200 °C-vacuum-annealing and (ii) 532 nm-laser-illumination; and accordingly, we utilize a deep learning algorithm to classify and quantify the generated point defects. We discovered that tellurium-related defects are mainly generated in both 2H-MoTe2 samples; but interestingly, 200 °C-vacuum-annealing and 532 nm-laser-illumination modulate a strong n-type and strong p-type 2H-MoTe2, respectively. While 200 °C-vacuum-annealing generates tellurium vacancies or tellurium adatoms, 532 nm-laser-illumination prompts oxygen atoms to be adsorbed/chemisorbed at tellurium vacancies, giving rise to the p-type characteristic. This work significantly advances the current understanding of point defect engineering in 2H-MoTe2 monolayers and other 2D materials, which is critical for developing nanoscale devices with desired functionality.

Original languageEnglish
Pages (from-to)6927-6935
Number of pages9
JournalACS Nano
Volume18
Issue number9
DOIs
StatePublished - Mar 5 2024

Funding

This work was supported by the Institute for Basic Science (IBS-R034-D1) as well as the Korea Basic Science Institute (National Research and Equipment Center) grant funded by the Ministry of Education (2020R1A6C101A202 and 2021R1A6C103B434). S.Y. acknowledges the support of a National Research Foundation of Korea grant provided by the Korean government (Ministry of Science and ICT) (NRF-2022R1A2C2091160).

Keywords

  • 2H-MoTe
  • deep learning
  • laser-illumination
  • point defect
  • scanning transmission electron microscopy
  • vacuum-annealing

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