Evidence map›Paper›PMID 36648821›Full record

ReviewBiomimetics (Basel, Switzerland)2023

Preparation of 2D Materials and Their Application in Oil-Water Separation.

Jie Li, Yushan Li, Yiyi Lu, Yuke Wang, Yunjie Guo, Wentian Shi

Open access · goldAbstract readReview
In one paragraph

Review in Biomimetics (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.9field-weighted citation impact, top 17% 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

3 citing papers in PubMed, 17 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
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

6 authors at 1 institution in 1 country.

Jie LiSchool of Artificial Intelligence, Beijing Technology and Business University, Beijing 100048, China.ORCID 0000-0002-3379-5183
Yushan LiSchool of Artificial Intelligence, Beijing Technology and Business University, Beijing 100048, China.
Yiyi LuSchool of Artificial Intelligence, Beijing Technology and Business University, Beijing 100048, China.
Yuke WangSchool of Artificial Intelligence, Beijing Technology and Business University, Beijing 100048, China.
Yunjie GuoSchool of Artificial Intelligence, Beijing Technology and Business University, Beijing 100048, China.
Wentian ShiSchool of Artificial Intelligence, Beijing Technology and Business University, Beijing 100048, China.ORCID 0000-0002-9320-4461
Beijing Technology and Business University · CN

Funding

National Key R&D Program of China 2022YFC2406004National Natural Science Foundation of China 51975006
6 · The paper itself

Abstract

The problems of environmental pollution are increasingly severe. Among them, industrial wastewater is one of the primary sources of pollution, so it is essential to deal with wastewater, especially oil and water mixtures. At present, biomimetic materials with special wettability have been proven to be effective in oil-water separation. Compared with three-dimensional (3D) materials, two-dimensional (2D) materials show unique advantages in the preparation of special wettable materials due to their high specific surface area, high porosity, controlled structure, and rich functional group rich on the surface. In this review, we first introduce oil-water mixtures and the common oil-water separation mechanism. Then, the research progress of 2D materials in oil-water separation is presented, including but not limited to their structure, types, preparation principles, and methods. In addition, it is still impossible to prepare 2D materials with large sizes because they are powder-like, which greatly limits the application in oil-water separation. Therefore, we provide here a review of several ways to transform 2D materials into 3D materials. In the end, the challenges encountered by 2D materials in separating oil-water are also clarified to promote future applications.

Indexed as

oil–water separationspecial wettabilitytwo-dimensional materials

Identifiers

PMID36648821
PMCPMC9844504
OpenAlexW4316466910

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.