Publications by authors named "Mona Nissen"

Accurate characterization of diffusing nanoscale species is increasingly important for revealing processes at the nanoscale, with fiber-assisted nanoparticle-tracking-analysis representing a new and promising approach in this field. In this work, we uncover the potential of this approach for the characterization of very small nanoparticles (<20 nm) through experimental studies, statistical analysis and the employment of a sophisticated fiber and chip design. The central results is the characterization of diffusing nanoparticles as small as 9 nm with record-high precision, corresponding to the smallest diameter yet determined for an individual nanoparticle with nanoparticle-tracking-analysis using elastic light scattering alone.

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Accurate determination of the size distribution of nanoparticle ensembles remains a challenge in nanotechnology-related applications due to the limitations of established methods. Here, a microstructured fiber-assisted nanoparticle tracking analysis (FaNTA) realization is introduced that breaks existing limitations through the recording of exceptionally long trajectories of rapidly diffusing polydisperse nanoparticles, resulting in excellent sizing precision and unprecedented separation capabilities of bimodal nanoparticle mixtures. An effective-single-mode antiresonant-element fiber allows to efficiently confine nanoparticles in a light-guiding microchannel and individually track them over more than 1000 frames, while aberration-free imaging is experimentally confirmed by cross-correlation analysis.

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Tracking and analyzing the individual diffusion of nanoscale objects such as proteins and viruses is an important methodology in life science. Here, we show a sensor that combines the efficiency of light line illumination with the advantages of fluidic confinement. Tracking of freely diffusing nano-objects inside water-filled hollow core fibers with core diameters of tens of micrometers using elastically scattered light from the core mode allows retrieving information about the Brownian motion and the size of each particle of the investigated ensemble individually using standard tracking algorithms and the mean squared displacement analysis.

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Due to a worldwide increased use of pharmaceuticals and, in particular, antibiotics, a growing number of these substance residues now contaminate natural water resources and drinking supplies. This triggers a considerable demand for low-cost, high-sensitivity methods for monitoring water quality. Since many biological substances exhibit strong and characteristic absorption features at wavelengths shorter than 300 nm, UV spectroscopy presents a suitable approach for the quantitative identification of such water-contaminating species.

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