Nanopore-based single nanoparticle detection methods have found recently increasing importance in applications ranging from gaining a better understanding of biophysical processes to technology-driven solutions such as biomolecule sensing and nanoparticle characterization. The significant advantages of nanopores include label-free, high throughput, and low material requirement. However, challenges remain especially in terms of further improving sensitivity and specificity of such methods, which are the two most important factors to take into account for biomolecule/particle sensing.;This work aims to improve nanopore-based nanoparticle sensing. We first use nanopore resistive pulse sensing to detect translocation of nanobeads through low-aspect-ratio silicon nitride nanopores. Resistive-pulse sensing utilizes the principle that a single particle in a pore filled with conductive solution decreases the ionic conductance of the orifice. Transit of the particle through the pore is observed as a dip in the ionic current. We used this principle to detect 50 and 100 nm polystyrene particles modified with carboxyl group. Our result shows that the translocation current of these two nanoparticles are different, and the translocation frequency increases non-linearly with the nanoparticle concentration. We also found that often translocating particles become permanently stuck onto the nanopore surface, causing the experiment to end prematurely.;In the second half of this thesis, we present a new nanopore-based sensing method that does not only overcome the clogging limitation, but actually exploits the ionic current change and induced Brownian noise caused by the blockage to characterize the properties of single nanoparticles. The technique consists of electrokinetically trapping and de-trapping of particles near a nanopore, which happens when the diameter of the nanopore is smaller than that of the particles. We prove that trapping occurs due to a balance between two counteracting factors: electrophoretic and electroosmotic forces. The motion of the trapped nanoparticle can then be modeled as a damped harmonic oscillator. We use the new trapping phenomenon to characterize nanoparticles with different sizes and charges, each of which gives different blockage current and spring constant. We also study the dependence of applied voltage on the blockage current and spring constant, which shows the ability to tune the position of trapping and force exerted on the nanoparticle. This new technique may find applications in drug delivery, transport control, and biosensing.
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