Preparation of porous polymers based on high internal phase emulsion for enrichment of estrogens in urine
| Autor: | Guihua Ruan, Yan Zhang, Zhengyi Chen, Fuyou Du, Xiangqiong Jiang, Wenjuan Zhang |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Glycidyl methacrylate
Polymers Surface Properties Emulsion polymerization Filtration and Separation 02 engineering and technology 01 natural sciences Analytical Chemistry chemistry.chemical_compound Humans Sample preparation Particle Size Monolith chemistry.chemical_classification Acrylate geography geography.geographical_feature_category Molecular Structure 010401 analytical chemistry Estrogens Polymer 021001 nanoscience & nanotechnology Divinylbenzene Healthy Volunteers 0104 chemical sciences chemistry Chemical engineering Emulsion Emulsions Female Graphite Adsorption 0210 nano-technology Porosity |
| Zdroj: | Journal of Separation Science. 44:1140-1147 |
| ISSN: | 1615-9314 1615-9306 |
| DOI: | 10.1002/jssc.202000566 |
| Popis: | In this work, graphene oxide-hybridized high internal emulsion polymers with crosslinking and open-cell structure was prepared and applied for separation and enrichment of estrogens. The prepared graphene oxide-hybridized high internal emulsion polymer monoliths had hydrophobicity, porosity and stability, which were just obtained by one step in-situ emulsion polymerization of 2-ethylhexyl acrylate, glycidyl methacrylate, and divinylbenzene after doping with graphene oxide. Benefit from the advantages of its unique character, the graphene oxide-hybridized high internal emulsion polymers monolith with low background pressure (85 kPa) and high mechanical strength could be applied for efficient separation for trace estrogens in urine. Under the optimized condition, trace estrogens, including estrone, estradiol, and diethylstilbestrol in urine, were detected by high-performance liquid chromatography, all the sample preparation process were carried out in 15 min, the recovery rate was ranged from 85.0 to 106.0% and the relative standard deviation was less than 4. |
| Databáze: | OpenAIRE |
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