ArticlePolymers2017
Combining Pickering Emulsion Polymerization with Molecular Imprinting to Prepare Polymer Microspheres for Selective Solid-Phase Extraction of Malachite Green.
Article in Polymers, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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.
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.
Who cites it
9 citing papers in PubMed, 22 citations in OpenAlex.
- Molecularly Imprinted Microspheres in Active Compound Separation from Natural Product.Molecules (Basel, Switzerland) · 2024Review
- Molecularly Imprinted Polymers Using Yeast as a Supporting Substrate.Molecules (Basel, Switzerland) · 2023Review
- Bovine Serum Albumin Molecularly Imprinted Electrochemical Sensors Modified by Carboxylated Multi-Walled Carbon Nanotubes/CaAlg Hydrogels.Gels (Basel, Switzerland) · 2023Article
- Microsphere Polymers in Molecular Imprinting: Current and Future Perspectives.Molecules (Basel, Switzerland) · 2020Review
- Trends inPolymers · 2019Article
- Biodegradable Polylactide/TiOPolymers · 2019Article
- Article
- Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Malachite green (MG) is currently posing a carcinogenic threat to the safety of human lives; therefore, it is highly desirable to develop an effective method for fast trace detection of MG. Herein, for the first time, this paper presents a systematic study on polymer microspheres, being prepared by combined Pickering emulsion polymerization and molecular imprinting, to detect and purify MG. The microspheres, molecularly imprinted with MG, show enhanced adsorption selectivity to MG, despite a somewhat lowered adsorption capacity, as compared to the counterpart without molecular imprinting. Structural features and adsorption performance of these microspheres are elucidated by different characterizations and kinetic and thermodynamic analyses. The surface of the molecularly imprinted polymer microspheres (M-PMs) exhibits regular pores of uniform pore size distribution, endowing M-PMs with impressive adsorption selectivity to MG. In contrast, the microspheres without molecular imprinting show a larger average particle diameter and an uneven porous surface (with roughness and a large pore size), causing a lower adsorption selectivity to MG despite a higher adsorption capacity. Various adsorption conditions are investigated, such as pH and initial concentration of the solution with MG, for optimizing the adsorption performance of M-PMs in selectively tackling MG. The adsorption kinetics and thermodynamics are deeply discussed and analyzed, so as to provide a full picture of the adsorption behaviors of the polymer microspheres with and without the molecular imprinting. Significantly, M-PMs show promising solid-phase extraction column applications for recovering MG in a continuous extraction manner.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.