Evidence map›Paper›PMID 36275163›Full record

ReviewRSC advances2022

Mechanism and behavior of caffeine sorption: affecting factors.

Merve Fakioğlu, Yasemen Kalpaklı

Abstract readReview
In one paragraph

Review in RSC advances, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 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

2 authors.

Merve FakioğluDepartment of Chemical Engineering, Yildiz Technical University 34220 Davutpaşa Istanbul Turkey merve.fakioglu@std.yildiz.edu.tr kalpakli@yildiz.edu.tr.ORCID https://orcid.org/0000-0003-0929-2663
Yasemen KalpaklıDepartment of Chemical Engineering, Yildiz Technical University 34220 Davutpaşa Istanbul Turkey merve.fakioglu@std.yildiz.edu.tr kalpakli@yildiz.edu.tr.ORCID https://orcid.org/0000-0002-1300-2289

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Caffeine is one of the emerging pollutants with a diverse chemical composition. It is mixed with the hydrobiota as a result of its high consumption, and when certain dose intervals are exceeded, it re-enters the human body through indirect routes such as plants, animals, soil, water, and the food chain, causing health problems that are difficult or impossible to treat, and irreversible environmental problems. This situation raises concerns about the presence of pollutants emerging in water resources, igniting interest in water treatment processes and the development of alternative methods. Although there are several methods for removing caffeine from aqueous media, adsorption is the most popular because it is less expensive than other methods and has the highest removal efficiency. Furthermore, it has the benefit of selectively attaching the molecules in solution. In this article, studies on the caffeine adsorption process have been examined, and the caffeine adsorption efficiency of various adsorbents has been summarized by compiling information such as pH, contact time, temperature, and concentration of adsorbent and adsorbate, which are considered as optimum processing conditions. The binding mechanism was investigated, and it was clearly stated how caffeine adheres to the adsorbent surface. Among the equilibrium adsorption isotherms, the isotherm model with the best agreement with the experimental data was attempted to be determined. Many studies clearly show that the process of developing environmentally friendly and high-capacity adsorbents in sustainable processes and in harmony with the circular economy is increasing day by day.

Identifiers

PMID36275163
PMCPMC9479768

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.