Multifunctional microfluidic chips for the single particle inductively coupled plasma mass spectrometry analysis of inorganic nanoparticles.
Gyula KajnerAlbert KériÁdám BéltekiSándor ValkaiAndrás DérZsolt GeretovszkyGábor GalbácsPublished in: Lab on a chip (2022)
This study aimed at exploiting the so far unexploited potential of carrying out on-line sample pretreatment steps on microfluidic chips for single particle inductively coupled plasma mass spectrometry (spICP-MS) measurements, and demonstrating their ability to practically facilitate most of the simpler tasks involved in the spICP-MS analysis of nanoparticles. For this purpose, polydimethylsiloxane microfluidic chips, capable of high-range dilution and sample injection were made by casting, using high-precision, 3D-printed molds. Optimization of their geometry and functions was done by running several hydrodynamic simulations and by gravimetric, fluorescence enhanced microscope imaging and solution-based ICP-MS experiments. On the optimized microfluidic chips, several experiments were done, demonstrating the benefits of the approach and these devices, such as the determination of nanoparticle concentration using only a few tens of microliters of sample, elimination of solute interferences by dilution, solution-based size calibration and characterisation of binary nanoparticles. Due to the unique design of the chips, they can be linked together to extend the dilution range of the system by more than a magnitude per chip. This feature was also demonstrated in applications requiring multiple-magnitude dilution rates, when two chips were sequentially coupled.
Keyphrases
- mass spectrometry
- liquid chromatography
- gas chromatography
- circulating tumor cells
- high throughput
- high performance liquid chromatography
- capillary electrophoresis
- single cell
- liquid chromatography tandem mass spectrometry
- high resolution
- tandem mass spectrometry
- solid phase extraction
- ms ms
- simultaneous determination
- multiple sclerosis
- label free
- drug delivery
- molecular dynamics
- deep learning
- ionic liquid
- walled carbon nanotubes
- working memory
- ultrasound guided
- high intensity