ArticleMikrochimica acta2020
Rational integration of porous organic polymer and multiwall carbon nanotube for the microextraction of polycyclic aromatic hydrocarbons.
Article in Mikrochimica acta, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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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.
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.
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Who cites it
2 citing papers in PubMed.
- N-rich hypercrosslinked porous polymers for highly efficient preconcentration and sensitive detection of chlorophenols.Mikrochimica acta · 2023Article
- Porous Hexagonal Boron Nitride as Solid-Phase Microextraction Coating Material for Extraction and Preconcentration of Polycyclic Aromatic Hydrocarbons from Soil Sample.Nanomaterials (Basel, Switzerland) · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
By integration of benzene-constructed porous organic polymer (KBF) and multiwalled carbon nanotube (MWCNT), a MWCNT-KBF hybrid material was constructed through in situ knitting benzene with formaldehyde dimethyl acetal in the presence of MWCNTs to form a network. MWCNT-KBF was then adopted as a novel solid-phase microextraction (SPME) fiber coating. Coupled to gas chromatography-flame ionization detection, the MWCNT-KBF-assisted SPME method showed large enhancement factors (483-2066), low limits of detection (0.04-0.12 μg L
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Registered trials
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.