Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 365

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

Enhanced Electronic Properties of SnO2 via Electron Transfer from Graphene Quantum Dots for Efficient Perovskite Solar Cells

Xie, Jiangsheng, Huang, Kun, Yu, Xuegong, Yang, Zhengrui, Xiao, Ke, Qiang, Yaping, Zhu, Xiaodong, Xu, Lingbo, Wang, Peng, Cui, Can, Yang, Deren·2017·ACS Nano

Abstract

Tin dioxide (SnO 2 ) has been demonstrated as an effective electron-transporting layer (ETL) for attaining high-performance perovskite solar cells (PSCs). However, the numerous trap states in low-temperature solution processed SnO 2 will reduce the PSCs performance and result in serious hysteresis. Here, we report a strategy to improve the electronic properties in SnO 2 through a facile treatment of the films with adding a small amount of graphene quantum dots (GQDs). We demonstrate that the photogenerated electrons in GQDs can transfer to the conduction band of SnO 2 . The transferred electrons from the GQDs will effectively fill the electron traps as well as improve the conductivity of SnO 2, which is beneficial for improving the electron extraction efficiency and reducing the recombination at the ETLs/perovskite interface. The device fabricated with SnO 2:GQDs could reach an average power conversion efficiency (PCE) of 19.2 ± 1.0% and a highest steady-state PCE of 20.23% with very little hysteresis. Our study provides an effective way to enhance the performance of perovskite solar cells through improving the electronic properties of SnO 2 .

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/acsnano.7b04070

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

Metadata

Authors
Xie, J., Huang, K., Yu, X., Yang, Z., Xiao, K., Qiang, Y., Zhu, X., Xu, L., Wang, P., Cui, C., & Yang, D.
Venue
ACS Nano
Published
2017-09-06
Volume
11
Issue
9
Pages
9176-9182
ISSN
  • 1936-0851 (ISSN-L)
  • 1936-086X
OpenAlex
W2753684966
Cited by
365
References
32
FWCI
17.68
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.