Evidence map›Paper›PMID 32024184›Full record

ArticlePolymers2020

Synthesis of Modified Starch/Polyvinyl Alcohol Composite for Treating Textile Wastewater.

Kai Xia, Xin Liu, Weiwei Wang, Xizi Yang, Xiaodong Zhang

Open access · goldAbstract read
In one paragraph

Article in Polymers, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.1field-weighted citation impact, top 14% 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

6 citing papers in PubMed, 31 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

5 authors at 1 institution in 1 country.

Kai XiaCollege of Chemistry and Chemical Engineering, Qingdao University, Qingdao 266071, China.
Xin LiuCollege of Chemistry and Chemical Engineering, Qingdao University, Qingdao 266071, China.
Weiwei WangCollege of Chemistry and Chemical Engineering, Qingdao University, Qingdao 266071, China.
Xizi YangCollege of Chemistry and Chemical Engineering, Qingdao University, Qingdao 266071, China.
Xiaodong ZhangCollege of Chemistry and Chemical Engineering, Qingdao University, Qingdao 266071, China.
Qingdao University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this work, we demonstrated a strategy to design a modified starch/polyvinyl alcohol composite (CCSP), which was employed as a highly efficient and economical fixed-bed adsorbent for treating textile wastewater. Characterization revealed that most of the CCSP was shaped with the morphology of sphericity, and had some water swelling properties. The crystallinity of the CCSP was lower than that of native starch and polyvinyl alcohol, and its average particle size gradually increased with the dosage increase of cationic starch in the preparation. Adsorption experiments showed that the adsorption capacities of CCSP were more than 605 and 539 mg/g for Reactive Black 5 and Reactive Orange 131, respectively, which were over 10 times larger than that of commercial activated carbon (AC). The mixture adsorbent composed of CCSP and AC could remove starch, polyvinyl alcohol, and dyes from textile wastewater completely and simultaneously combined with the fixed-bed technique, and its adsorption capacity was conducted as a function of the bed height and flow rate. Most importantly, the disabled mixture adsorbent could be converted into regenerated AC through a chemical activation process, thereby avoiding the production of solid waste. This study will provide a new efficient green sustainable method for treating textile wastewater.

Indexed as

composite microspheresmodified polyvinyl alcoholmodified starchregenerated activated carbontextile wastewater

Identifiers

PMID32024184
PMCPMC7077426
OpenAlexW3003480998

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.