High gradient magnetic separation of upconverting lanthanide nanophosphors based on their intrinsic paramagnetism
Source abstract
Abstract
Photon upconverting nanophosphors (UCNPs) have the unique luminescent property of converting low-energy infrared light into visible emission which can be widely utilized in nanoreporter and imaging applications. For the use as reporters in these applications, the UCNPs must undergo a series of surface modification and bioconjugation reactions. Efficient purification methods are required to remove the excess reagents and biomolecules from the nanophosphor solution after each step to yield highly responsive reporters for sensitive bioanalytical assays. However, as the particle size of the UCNPs approaches the size of biomolecules, the handling of these reporters becomes cumbersome with traditional purification methods such as centrifugation. Here we introduce a novel approach for purification of bioconjugated 32-nm NaYF4: Yb3+, Er3+-nanophosphors from excess unbound biomolecules utilizing high gradient magnetic separation (HGMS)-system constructed from permanent super magnets which produce magnetic gradients in a magnetizable steel wool matrix amplifying the magnetic field. The non-magnetic biomolecules flowed straight through the magnetized HGMS-column while the UCNPs were eluted only after the magnetic field was removed. In the UCNPs the luminescent centers, i.e., lanthanide-ion dopants are responsible for the strong upconversion luminescence, but in addition they are also paramagnetic. In this study we have shown that the presence of these weakly paramagnetic luminescent lanthanides actually also enables the use of HGMS to capture the UCNPs without incorporating additional optically inactive magnetic core into them.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Luminescence Properties of Advanced Materials · Quantum Dots Synthesis And Properties · Gas Sensing Nanomaterials and Sensors
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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