PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
February 11, 2024Langmuir4 citations

Anisotropic Magnetic Polymeric Particles with a Controllable Structure via Seeded Emulsion Polymerization

View Full Paper
QXQianrui XuYNYingrui NieDWDiyan Wu

Key Points

Key points are not available for this paper at this time.

Abstract

Magnetic polymer composites have been widely utilized in potential applications in material science, such as reduction of dyes, immunodiagnostics, biomedicals, and magnetically controllable photonic crystals owing to large surface areas, fast separation, and recyclable performance. In this work, anisotropic magnetic particles were prepared by seeded emulsion polymerization, with morphologies of "Fe3O4-shell", "hemisphere-like", "raspberry-like", "multiple lobes-like", and "sandwich-like". Poly(styrene/divinylbenzene/mono-2-(methacryloxy)ethyl succinate)@ Fe3O4 (P(St/DVB/MMES)@Fe3O4) were the seed microspheres, and P(St/DVB/MMES)@Fe3O4@polymer particles are achieved by seeded emulsion polymerizations. The morphology of the particles depends on polymerization conditions (monomer ratios and surfactant), particle properties, and so on. Then, the minimum surface free energy change principles were used to predict the equilibrium morphologies of the magnetic polymer composites. Through theory, the model gives the correct tendency and good agreement with the equilibrium morphology which was in tandem with TEM results. Lastly, after in situ surface deposition of Ag nanoparticles, magnetic composite particles with sandwich-like morphology were applied for the catalytic degradation of 4-nitrophenol (4-NP) reacting with NaBH4. The apparent rate coefficient is 0.0069 s–1, and it can keep mainly about 80% efficiency in catalysis after five cycles.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Xu et al. (2024) studied this question.

synapsesocial.com/papers/68e7997bb6db64358770a1f4https://doi.org/10.1021/acs.langmuir.3c03379
Ask AI
Helpful
Bookmark
Share
View Full Paper