Over the last five years, solid state nanopore technology advanced to rival biological pores as a platform for next generation DNA sequencing. Fabrication improvements led to a reduction in nanopore diameter and membrane thickness, offering high precision sensing. Custom electronics were developed concomitant with low capacitance membranes for low-noise, high-bandwidth measurements. These advances improved our ability to detect small differences between translocating molecules and to measure short molecules translocating at high speeds. This work focuses specifically on the challenge of maximizing the signal magnitude generated by the solid state nanopore. One way that this can be achieved is by thinning the membrane. We prove that it is possible to differentiate between DNA homopolymers by using nanopores with < 6 nm thickness and < 2 nm diameter. The results imply that solid state nanopores offer higher signal-to-noise than what is currently achieved with biological pores. Attempts to reduce membrane thickness further by making nanopores in 2D materials proved to be limited by wetting and noise considerations. Instead, we developed an electron-irradiation-based thinning technique to thin Si-based films to the limit of their stability in order to determine the intrinsic limit of their detection capabilities. At these small thicknesses, we discovered unexpected blocked current structure in the translocation events, which we hypothesize to be related to the DNA molecule blocking current flow before entering the nanopore. Then we outline an alternative technique for high signal-to-noise single-molecule measurement by using a nanopore to localize the molecule near a charge sensor. The design of such a device required the development of a technique to make nanopores without damaging the sensor. Results from measurements of these devices in solution are reported, along with discussion of methods for improving the sensitivity. In the last section we report on somewhat unrelated experiments that involve imaging charge flow through structured quantum dot films. We use a combination of AFM, EFM, and TEM to map the topography, charge flow, and structural features in high resolution. We show that charge flow patterns can be clearly correlated with structural details in the film.