Evidence map›Paper›PMID 38874326›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2024

Comprehensive Study of Artificial Light-Harvesting Systems with a Multi-Step Sequential Energy Transfer Mechanism.

Yong Wu, Yuqian Wang, Xu Yu, Qiao Song

Abstract read
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Yong WuShenzhen Grubbs Institute, Southern University of Science and Technology, Shenzhen, 518055, China.
Yuqian WangShenzhen Grubbs Institute, Southern University of Science and Technology, Shenzhen, 518055, China.
Xu YuInstitute of Innovation Materials and Energy, College of Chemistry and Chemical Engineering, Yangzhou University, Yangzhou, 225002, China.
Qiao SongShenzhen Grubbs Institute, Southern University of Science and Technology, Shenzhen, 518055, China.ORCID https://orcid.org/0000-0002-4286-0370

Funding

National Natural Science Foundation of China 22101124Natural Science Foundation of Guangdong Province of China 2022A1515011394Shenzhen Science and Technology Program 20220815163454004Shenzhen Science and Technology Program JCYJ20210324105009025
6 · The paper itself

Abstract

Artificial light-harvesting systems (LHSs) with a multi-step sequential energy transfer mechanism significantly enhance light energy utilization. Nonetheless, most of these systems exhibit an overall energy transfer efficiency below 80%. Moreover, due to challenges in molecularly aligning multiple donor/acceptor chromophores, systems featuring ≥3-step sequential energy transfer are rarely reported. Here, a series of artificial LHSs is introduced featuring up to 4-step energy transfer mechanism, constructed using a cyclic peptide-based supramolecular scaffold. These LHSs showed remarkably high energy transfer efficiencies (≥90%) and satisfactory fluorescence quantum yields (ranging from 17.6% to 58.4%). Furthermore, the structural robustness of the supramolecular scaffold enables a comprehensive study of these systems, elucidating the associated energy transfer pathways, and identifying additional energy transfer processes beyond the targeted sequential energy transfer. Overall, this comprehensive investigation not only enhances the understanding of these LHSs, but also underscores the versatility of cyclic peptide-based supramolecular scaffolds in advancing energy harvesting technologies.

Indexed as

artificial light‐harvesting systemscyclic peptidessequential energy transfersupramolecular scaffolds

Identifiers

PMID38874326
PMCPMC11336932

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.