Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 291

The DOI matches its Crossref record; 37 of the 37 references it cites were found in a registry or an index.

High power density microbial fuel cell with flexible 3D graphene–nickel foam as anode

Wang, Hanyu, Wang, Gongming, Ling, Yichuan, Qian, Fang, Song, Yang, Lu, Xihong, Chen, Shaowei, Tong, Yexiang, Li, Yat·2013·Nanoscale

Abstract

The structure and electrical conductivity of anode play a significant role in the power generation of microbial fuel cells (MFCs). In this study, we developed a three-dimensional (3D) reduced graphene oxide-nickel (denoted as rGO-Ni) foam as an anode for MFC through controlled deposition of rGO sheets onto the nickel foam substrate. The loading amount of rGO sheets and electrode surface area can be controlled by the number of rGO loading cycles. 3D rGO-Ni foam anode provides not only a large accessible surface area for microbial colonization and electron mediators, but also a uniform macro-porous scaffold for effective mass diffusion of the culture medium. Significantly, at a steady state of the power generation, the MFC device with flexible rGO-Ni electrodes produced an optimal volumetric power density of 661 W m(-3) calculated based on the volume of anode material, or 27 W m(-3) based on the volume of the anode chamber. These values are substantially higher than that of plain nickel foam, and other conventional carbon based electrodes (e.g., carbon cloth, carbon felt, and carbon paper) measured in the same conditions. To our knowledge, this is the highest volumetric power density reported for mL-scale MFC device with a pure strain of Shewanella oneidensis MR-1. We also demonstrated that the MFC device can be operated effectively in a batch-mode at least for a week. These new 3D rGO-Ni electrodes show great promise for improving the power generation of MFC devices.

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 · 10.1039/c3nr03487a

Cites

37 of 37 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 291

Metadata

Authors
Wang, H., Wang, G., Ling, Y., Qian, F., Song, Y., Lu, X., Chen, S., Tong, Y., & Li, Y.
Venue
Nanoscale
Published
2013
Volume
5
Issue
21
Pages
10283
ISSN
  • 2040-3364 (ISSN-L)
  • 2040-3372
OpenAlex
W1982633143
Cited by
291
References
37
FWCI
23.17
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.