Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 447

The DOI matches its Crossref record; 68 of the 68 references it cites were found in a registry or an index.

Development of bioinspired artificial photosynthetic systems

Fukuzumi, Shunichi·2008·Physical Chemistry Chemical Physics

Abstract

The specific objective of this review is to describe recent development of bioinspired artificial photosynthetic systems and their applications. First, multi-step electron-transfer systems composed of electron donor-acceptor ensembles are presented, mimicking functions of the photosynthetic reaction center. However, a significant amount of energy is lost during the multi-step electron-transfer processes. Then, as an alternative to conventional charge-separation functional molecular models based on multi-step long-range electron transfer within redox cascades, simple electron donor-acceptor dyads linked by covalent or non-covalent bonding have been developed to attain a long-lived and high-energy charge-separated state without significant loss of excitation energy. Such simple molecular dyads, capable of fast charge separation but extremely slow charge recombination, have significant advantages with regard to synthetic feasibility, providing a variety of applications including construction of organic solar cells and development of efficient photocatalytic systems for the solar energy conversion.

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/b801198m

Cites

68 of 68 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 68 references

Cited by

See all 447

Metadata

Authors
Fukuzumi, S.
Venue
Physical Chemistry Chemical Physics
Published
2008
Volume
10
Issue
17
Pages
2283
ISSN
  • 1463-9076 (ISSN-L)
  • 1463-9084
OpenAlex
W1976870657
Cited by
447
References
68
FWCI
23.96
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: Development of bioinspired artificial photosynthetic systems. https://app.cochat.ai/papers/10.1039/b801198m
The paper
Fukuzumi, S. (2008). Development of bioinspired artificial photosynthetic systems. Physical Chemistry Chemical Physics. https://doi.org/10.1039/b801198m

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.