Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 359

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

Synthetic Graphene Oxide Leaf for Solar Desalination with Zero Liquid Discharge

Finnerty, Casey, Zhang, Lei, Sedlak, David L., Nelson, Kara L., Mi, Baoxia·2017·Environmental Science & Technology

Abstract

Water vapor generation through sunlight harvesting and heat localization by carbon-based porous thin film materials holds great promise for sustainable, energy-efficient desalination and water treatment. However, the applicability of such materials in a high-salinity environment emphasizing zero-liquid-discharge brine disposal has not been studied. This paper reports the characterization and evaporation performance of a nature-inspired synthetic leaf made of graphene oxide (GO) thin film material, which exhibited broadband light absorption and excellent stability in high-salinity water. Under 0.82-sun illumination (825 W/m 2 ), a GO leaf floating on water generated steam at a rate of 1.1 L per m 2 per hour (LMH) with a light-to-vapor energy conversion efficiency of 54%, while a GO leaf lifted above water in a tree-like configuration generated steam at a rate of 2.0 LMH with an energy efficiency of 78%. The evaporation rate increased with increasing light intensity and decreased with increasing salinity. During a long-term evaporation experiment with a 15 wt % NaCl solution, the GO leaf demonstrated stable performance despite gradual and eventually severe accumulation of salt crystals on the leaf surface. Furthermore, the GO leaf can be easily restored to its pristine condition by simply scraping off salt crystals from its surface and rinsing with water. Therefore, the robust high performance and relatively low fabrication cost of the synthetic GO leaf could potentially unlock a new generation of desalination technology that can be entirely solar-powered and achieve zero liquid discharge.

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/acs.est.7b03040

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

Metadata

Authors
Finnerty, C., Zhang, L., Sedlak, D. L., Nelson, K. L., & Mi, B.
Venue
Environmental Science & Technology
Published
2017-09-27
Volume
51
Issue
20
Pages
11701-11709
ISSN
  • 0013-936X (ISSN-L)
  • 1520-5851
OpenAlex
W2755939905
Cited by
359
References
34
FWCI
8.54
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.