Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 1,228

The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.

Continuous, Highly Flexible, and Transparent Graphene Films by Chemical Vapor Deposition for Organic Photovoltaics

Gomez De Arco, Lewis, Zhang, Yi, Schlenker, Cody W., Ryu, Koungmin, Thompson, Mark E., Zhou, Chongwu·2010·ACS Nano

Abstract

We report the implementation of continuous, highly flexible, and transparent graphene films obtained by chemical vapor deposition (CVD) as transparent conductive electrodes (TCE) in organic photovoltaic cells. Graphene films were synthesized by CVD, transferred to transparent substrates, and evaluated in organic solar cell heterojunctions (TCE/poly-3,4-ethylenedioxythiophene:poly styrenesulfonate (PEDOT:PSS)/copper phthalocyanine/fullerene/bathocuproine/aluminum). Key to our success is the continuous nature of the CVD graphene films, which led to minimal surface roughness ( approximately 0.9 nm) and offered sheet resistance down to 230 Omega/sq (at 72% transparency), much lower than stacked graphene flakes at similar transparency. In addition, solar cells with CVD graphene and indium tin oxide (ITO) electrodes were fabricated side-by-side on flexible polyethylene terephthalate (PET) substrates and were confirmed to offer comparable performance, with power conversion efficiencies (eta) of 1.18 and 1.27%, respectively. Furthermore, CVD graphene solar cells demonstrated outstanding capability to operate under bending conditions up to 138 degrees , whereas the ITO-based devices displayed cracks and irreversible failure under bending of 60 degrees . Our work indicates the great potential of CVD graphene films for flexible photovoltaic applications.

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/nn901587x

Cites

4 of 4 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

Cited by

See all 1,228

Metadata

Authors
Gomez De Arco, L., Zhang, Y., Schlenker, C. W., Ryu, K., Thompson, M. E., & Zhou, C.
Venue
ACS Nano
Published
2010-04-15
Volume
4
Issue
5
Pages
2865-2873
ISSN
  • 1936-0851 (ISSN-L)
  • 1936-086X
OpenAlex
W2059203269
Cited by
1,228
References
4
FWCI
49.11
Type
journal article
Language
en
Open access
closed

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

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.