Evidence map›Paper›PMID 35155902›Full record

ArticleACS omega2022

Optimization of the Urea Removal in a Wearable Dialysis Device Using Nitrogen-Doped and Phosphorus-Doped Graphene.

Keyvan Karimi, Mansour Rahsepar

Open access · goldAbstract read
In one paragraph

Article in ACS omega, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.2field-weighted citation impact, top 25% of its field
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

4 citing papers in PubMed, 19 citations in OpenAlex.

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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 at 1 institution in 1 country.

Keyvan KarimiDepartment of Materials Science and Engineering, School of Engineering, Shiraz University, Zand Boulevard, Shiraz 7134851154, Iran.
Mansour RahseparDepartment of Materials Science and Engineering, School of Engineering, Shiraz University, Zand Boulevard, Shiraz 7134851154, Iran.ORCID https://orcid.org/0000-0001-5254-9319
Shiraz University · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Dialysis has been recognized as an essential treatment for end-stage renal disease (ESRD). This therapy, however, suffers from several limitations leading to numerous complications in the patients. As dialysis cannot completely substitute healthy kidney functions, the health condition of an ESRD patient is ultimately affected. Wearable artificial kidney (WAK) can resolve the restrictions of blood purification by the dialysis method. However, absorbing large amounts of urea produced in the body is one of the main challenges of these WAK and overcoming this is necessary to improve both functionality and footprint of the device. This study investigates the adsorption capabilities of N- and P-doped graphene nanosorbents for the first time by using molecular dynamic simulation. Urea removal on carbon nanosheets was simulated with different percentages of phosphorus and nitrogen dopants along with the pristine graphene. Specifically, the effects of interaction energy, adsorption percentage, gyration radius, hydrogen bonding, and other molecular dynamic analyses on urea removal were also investigated. The results from this study match well with the existing research, demonstrating the accuracy of the model. The results further suggest that graphene nanosheets doped by 10% nitrogen are likely the most effective in removing urea given that it is associated with the maximum radial distribution function (RDF), the maximum reduction in gyration radius, a high number of hydrogen bonds, and the most negative adsorption energy. This molecular study offers attractive suggestions for the novel adsorbents of artificial kidney devices and paves the way for the development of novel and enhanced urea adsorbents.

Identifiers

PMID35155902
PMCPMC8829914
OpenAlexW4206930823

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.