Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 732

The DOI matches its Crossref record; 32 of the 32 references it cites were found in a registry or an index.

Ultrafast All-Optical Graphene Modulator

Open access
Li, Wei, Chen, Bigeng, Meng, Chao, Fang, Wei, Xiao, Yao, Li, Xiyuan, Hu, Zhifang, Xu, Yingxin, Tong, Limin, Wang, Hongqing, Liu, Weitao, Bao, Jiming, Shen, Y. Ron·2014·Nano Letters

Abstract

Graphene is an optical material of unusual characteristics because of its linearly dispersive conduction and valence bands and the strong interband transitions. It allows broadband light-matter interactions with ultrafast responses and can be readily pasted to surfaces of functional structures for photonic and optoelectronic applications. Recently, graphene-based optical modulators have been demonstrated with electrical tuning of the Fermi level of graphene. Their operation bandwidth, however, was limited to about 1 GHz by the response of the driving electrical circuit. Clearly, this can be improved by an all-optical approach. Here, we show that a graphene-clad microfiber all-optical modulator can achieve a modulation depth of 38% and a response time of ∼ 2.2 ps, limited only by the intrinsic carrier relaxation time of graphene. This modulator is compatible with current high-speed fiber-optic communication networks and may open the door to meet future demand of ultrafast optical signal 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 · 10.1021/nl404356t

Cites

32 of 32 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 32 references

Metadata

Authors
Li, W., Chen, B., Meng, C., Fang, W., Xiao, Y., Li, X., Hu, Z., Xu, Y., Tong, L., Wang, H., Liu, W., Bao, J., & Shen, Y. R.
Venue
Nano Letters
Published
2014-01-13
Volume
14
Issue
2
Pages
955-959
ISSN
  • 1530-6984 (ISSN-L)
  • 1530-6992
OpenAlex
W2312266205
Cited by
732
References
32
FWCI
30.08
Type
journal article
Language
en
Open access
hybrid

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: Ultrafast All-Optical Graphene Modulator. https://app.cochat.ai/papers/10.1021/nl404356t
The paper
Li, W., Chen, B., Meng, C., Fang, W., Xiao, Y., Li, X., Hu, Z., Xu, Y., Tong, L., Wang, H., Liu, W., Bao, J., & Shen, Y. R. (2014). Ultrafast All-Optical Graphene Modulator. Nano Letters. https://doi.org/10.1021/nl404356t

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.