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Updated: May 6, 2026

Monitoring Protein Adsorption with Solid-state Nanopores
Published on: December 2, 2011
Comparative Benchmarking of Glass and Silicon Nitride Nanopores for Single-Molecule Detection
Fei Zheng1,2, Zhan Wang3, An Bai4
1School of Nanoscience and Nanotechnology, University of Chinese Academy of Sciences, Beijing 101408, China.
Abstract:
In the rapidly evolving field of single-molecule sensing, solid-state nanopores have emerged as transformative tools for the label-free detection of biomolecules, ranging from DNA polymers to proteins. Yet, with two dominant platforms─glass nanopores and silicon nitride (SiNx) nanopores─researchers face a pivotal choice: which architecture best unlocks superior performance? Here, we deliver a head-to-head experimental comparison under comparable experimental conditions, benchmarking noise characteristics, signal-to-noise ratios (SNRs), and translocation dynamics for DNA and protein analytes across matched nanopore sizes. Our findings reveal compelling trade-offs: glass nanopores excel in DNA sensing, achieving record SNR values of >80 in 5 nm nanopores (4 M LiCl, 50 kHz filter cutoff) due to their conical geometry that focuses electric fields. In contrast, SiNx nanopores dominate protein detection with SNR values of >120, leveraging thin membranes for enhanced current blockade from volume exclusion. Comprehensive performance metrics─including unfolded DNA fraction, backward-to-forward translocation time ratio, translocation frequency, and perturbed events─also show distinct translocation behaviors of biomolecules in the two nanopore platforms. These insights, supported by finite-element simulations, establish a mechanistic framework for nanopore selection, favoring conical glass nanopores for polymeric analytes and SiNx membrane nanopores for compact biomolecules. This work not only sets benchmarks for nanopore sensitivity but also enables the development of tailored sensors in diagnostics, sequencing, and beyond, advancing nanotechnology for high-resolution biomolecular analyses.

