Evidence map›Paper›PMID 33668604›Full record

ArticlePolymers2021

Solvent-Free Synthesis of Iron-Based Metal-Organic Frameworks (MOFs) as Slow-Release Fertilizers.

Yaxiao Du, Xuebin Xu, Fei Ma, Changwen Du

Abstract read
In one paragraph

Article in Polymers, 2021. 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
–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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
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

4 authors.

Yaxiao DuThe State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science Chinese Academy of Sciences, Nanjing 210008, China.
Xuebin XuThe State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science Chinese Academy of Sciences, Nanjing 210008, China.
Fei MaThe State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science Chinese Academy of Sciences, Nanjing 210008, China.
Changwen DuThe State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science Chinese Academy of Sciences, Nanjing 210008, China.ORCID 0000-0002-9064-3581

Funding

he National Key Research and Development Program of China 2017YFD0200704the "STS" Project from Chinese Academy of Sciences KFJ-STS-QYZX-046
6 · The paper itself

Abstract

Metal-organic frameworks (MOFs) were usually synthesized in hydrothermal conditions; in this study, a more energy-saving, easier to control, and solvent-free mechanochemical method was firstly applied to synthesize MOFs with varied reactants as slow release fertilizer, and the components and structures were characterized by X-ray diffraction (XRD), Fourier transform infrared total attenuated reflectance (FTIR-ATR), and laser-induced breakdown spectroscopy (LIBS). Results showed that three MOFs (compounds I, II, and III) were obtained, the MOFs were confirmed as oxalate phosphate oxalate frameworks (OPA-MOF), and ions were adsorbed between layers that contributed to the contents, while urea molecules mainly impacted the structure. The elemental compositions significantly varied among the three compounds; compound I showed the highest content of N (4.91%), P (15.71%), and Fe (18.60%), compound III indicated the highest content of C (6.52%) and K (12.59%), while the contents of C, K, P, and Fe in compound II were in the medium range. Similar release profiles of Fe and P were found among the three MOFs, and the release rates of nutrients were demonstrated as the order of N > K > P > Fe. The compositions and release profiles demonstrated potential application of MOFs as a novel slow-release fertilizer.

Indexed as

mechanochemical synthesismetal-organic frameworksslow release fertilizerurea

Identifiers

PMID33668604
PMCPMC7918741

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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.