Evidence map›Paper›PMID 33825458›Full record

ReviewACS sensors2021

Covalent Organic Polymers and Frameworks for Fluorescence-Based Sensors.

Tina Skorjanc, Dinesh Shetty, Matjaz Valant

Abstract readReview
In one paragraph

Review in ACS sensors, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers.

0numbers the graph read from it
0cells of the map it votes in
50citing 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

50 citing papers in PubMed.

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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

3 authors.

Tina SkorjancMaterials Research Laboratory, University of Nova Gorica, Vipavska 11c, 5270 Ajdovscina, Slovenia.
Dinesh ShettyDepartment of Chemistry & Center for Catalysis and Separations (CeCaS), Khalifa University of Science and Technology, P.O. Box 127788, Abu Dhabi, United Arab Emirates.
Matjaz ValantMaterials Research Laboratory, University of Nova Gorica, Vipavska 11c, 5270 Ajdovscina, Slovenia.ORCID 0000-0003-4842-5676

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Following the advancements and diversification in synthetic strategies for porous covalent materials in the literature, the materials science community started to investigate the performance of covalent organic polymers (COPs) and covalent organic frameworks (COFs) in applications that require large surface areas for interaction with other molecules, chemical stability, and insolubility. Sensorics is an area where COPs and COFs have demonstrated immense potential and achieved high levels of sensitivity and selectivity on account of their tunable structures. In this review, we focus on those covalent polymeric systems that use fluorescence spectroscopy as a method of detection. After briefly reviewing the physical basis of fluorescence-based sensors, we delve into various kinds of analytes that have been explored with COPs and COFs, namely, heavy metal ions, explosives, biological molecules, amines, pH, volatile organic compounds and solvents, iodine, enantiomers, gases, and anions. Throughout this work, we discuss the mechanisms involved in each sensing application and aim to quantify the potency of the discussed sensors by providing limits of detection and quenching constants when available. This review concludes with a summary of the surveyed literature and raises a few concerns that should be addressed in the future development of COP and COF fluorescence-based sensors.

Indexed as

Explosive AgentsMetal-Organic FrameworksGasesPolymersPorosityExplosive AgentsGasesMetal-Organic FrameworksPolymersaminesbiological moleculescovalent organic frameworkscovalent organic polymersenantiomersexplosivesfluorescenceionsquenchingsensors

Identifiers

PMID33825458
PMCPMC8155660

What OpenQuestion holds

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Registered trials

None linked

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.