Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 2,192

The DOI matches its Crossref record.

Light Trapping in Silicon Nanowire Solar Cells

Garnett, Erik, Yang, Peidong·2010·Nano Letters

Abstract

Thin-film structures can reduce the cost of solar power by using inexpensive substrates and a lower quantity and quality of semiconductor material. However, the resulting short optical path length and minority carrier diffusion length necessitates either a high absorption coefficient or excellent light trapping. Semiconducting nanowire arrays have already been shown to have low reflective losses compared to planar semiconductors, but their light-trapping properties have not been measured. Using optical transmission and photocurrent measurements on thin silicon films, we demonstrate that ordered arrays of silicon nanowires increase the path length of incident solar radiation by up to a factor of 73. This extraordinary light-trapping path length enhancement factor is above the randomized scattering (Lambertian) limit (2n(2) approximately 25 without a back reflector) and is superior to other light-trapping methods. By changing the silicon film thickness and nanowire length, we show that there is a competition between improved absorption and increased surface recombination; for nanowire arrays fabricated from 8 mum thick silicon films, the enhanced absorption can dominate over surface recombination, even without any surface passivation. These nanowire devices give efficiencies above 5%, with short-circuit photocurrents higher than planar control samples.

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/nl100161z

Cites

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

Cited by

See all 2,192

Metadata

Authors
Garnett, E., & Yang, P.
Venue
Nano Letters
Published
2010-01-28
Volume
10
Issue
3
Pages
1082-1087
ISSN
  • 1530-6984 (ISSN-L)
  • 1530-6992
OpenAlex
W1987211913
Cited by
2,192
References
0
FWCI
116.68
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

How to cite

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

This page
CoChat. (2026). Citation check: Light Trapping in Silicon Nanowire Solar Cells. https://app.cochat.ai/papers/10.1021/nl100161z
The paper
Garnett, E., & Yang, P. (2010). Light Trapping in Silicon Nanowire Solar Cells. Nano Letters. https://doi.org/10.1021/nl100161z

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.