Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 283

The DOI matches its Crossref record; 34 of the 34 references it cites were found in a registry or an index.

Giant valley splitting in monolayer WS2 by magnetic proximity effect

Open access
Norden, Tenzin, Zhao, Chuan, Zhang, Peiyao, Sabirianov, Renat, Petrou, Athos, Zeng, Hao·2019·Nature Communications

Abstract

Lifting the valley degeneracy of monolayer transition metal dichalcogenides (TMDs) would allow versatile control of the valley degree of freedom. We report a giant valley exciton splitting of 16 meV/T for monolayer WS 2, using the proximity effect from an EuS substrate, which is enhanced by nearly two orders of magnitude from that obtained by an external magnetic field. More interestingly, a sign reversal of the valley splitting is observed as compared to that of WSe 2 on EuS. Using first principles calculations, we investigate the complex behavior of exchange interactions between TMDs and EuS. The sign reversal is attributed to competing ferromagnetic (FM) and antiferromagnetic (AFM) exchange interactions for Eu- and S- terminated EuS surface sites. They act differently on the conduction and valence bands of WS 2 compared to WSe 2. Tuning the sign and magnitude of the valley exciton splitting offers opportunities for control of valley pseudospin for quantum information processing.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1038/s41467-019-11966-4

Cites

34 of 34 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 34 references

Cited by

See all 283

Metadata

Authors
Norden, T., Zhao, C., Zhang, P., Sabirianov, R., Petrou, A., & Zeng, H.
Venue
Nature Communications
Published
2019-09-13
Volume
10
Issue
1
Pages
4163-4163
ISSN
2041-1723 (ISSN-L)
OpenAlex
W2913250816
Cited by
283
References
34
FWCI
9.81
Type
journal article
Language
en
Open access
gold

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Giant valley splitting in monolayer WS2 by magnetic proximity effect. https://app.cochat.ai/papers/10.1038/s41467-019-11966-4
The paper
Norden, T., Zhao, C., Zhang, P., Sabirianov, R., Petrou, A., & Zeng, H. (2019). Giant valley splitting in monolayer WS2 by magnetic proximity effect. Nature Communications. https://doi.org/10.1038/s41467-019-11966-4

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.