Illuminating the Electronic Properties of WS2 Polytypism with Electron Microscopy

Sabrya E. van Heijst, Masaki Mukai, Eiji Okunishi, Hiroki Hashiguchi, Laurien I. Roest, Louis Maduro, Juan Rojo, Sonia Conesa-Boj

Research output: Contribution to journalArticleScientificpeer-review

1 Citation (Scopus)
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Abstract

Tailoring the specific stacking sequence (polytypes) of layered materials represents a powerful strategy to identify and design novel physical properties. While nanostructures built upon transition-metal dichalcogenides (TMDs) with either the 2H or 3R crystalline phases have been routinely studied, knowledge of TMD nanomaterials based on mixed 2H/3R polytypes is far more limited. In this work, mixed 2H/3R free-standing WS2 nanostructures displaying a flower-like configuration are fingerprinted by means of state-of-the-art transmission electron microscopy. Their rich variety of shape-morphology configurations is correlated with relevant local electronic properties such as edge, surface, and bulk plasmons. Machine learning is deployed to establish that the 2H/3R polytype displays an indirect band gap of (Formula presented.). Further, high resolution electron energy-loss spectroscopy reveals energy-gain peaks exhibiting a gain-to-loss ratio greater than unity, a property that can be exploited for cooling strategies of atomically-thin TMD nanostructures and devices built upon them. The findings of this work represent a stepping stone towards an improved understanding of TMD nanomaterials based on mixed crystalline phases.

Original languageEnglish
Article number2000499
JournalAnnalen der Physik
Volume533
Issue number3
DOIs
Publication statusPublished - 2021

Keywords

  • machine learning methods
  • polytypes
  • transition metal dichalcogenides

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