Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 969

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Molecule Self-Assembly Synthesis of Porous Few-Layer Carbon Nitride for Highly Efficient Photoredox Catalysis

Xiao, Yuting, Tian, Guohui, Li, Wei, Xie, Ying, Jiang, Baojiang, Tian, Chungui, Zhao, Dongyuan, Fu, Honggang·2019·Journal of the American Chemical Society

Abstract

Polymeric carbon nitride (C 3 N 4 ) has emerged as the most promising candidate for metal-free photocatalysts but is plagued by low activity due to the poor quantum efficiency and low specific surface area. Exfoliation of bulk crystals into ultrathin nanosheets has proven to be an effective and widely used strategy for enabling high photocatalytic performances; however, this process is complicated, time-consuming, and costly. Here, we report a simple bottom-up method to synthesize porous few-layer C 3 N 4, which involves molecule self-assembly into layered precursors, alcohol molecules intercalation, and subsequent thermal-induced exfoliation and polycondensation. The as-prepared few-layer C 3 N 4 expose more active sites and greatly enhance the separation of charge carriers, thus exhibiting a 26-fold higher hydrogen evolution activity than bulk counterpart. Furthermore, we find that both the high activity and selectivity for the oxidative coupling of amines to imines can be obtained under visible light that surpass those of other metal-free photocatalysts so far.

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/jacs.8b12428

Cites

2 of 2 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 969

Metadata

Authors
Xiao, Y., Tian, G., Li, W., Xie, Y., Jiang, B., Tian, C., Zhao, D., & Fu, H.
Venue
Journal of the American Chemical Society
Published
2019-01-17
Volume
141
Issue
6
Pages
2508-2515
ISSN
  • 0002-7863 (ISSN-L)
  • 1520-5126
OpenAlex
W2910397134
Cited by
969
References
2
FWCI
25.92
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.