ArticleACS omega2026
Power Spectral Density Analysis of Solid-State Nanopore Signals: Application to Stability Estimation.
Article in ACS omega, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Authors and funding
5 authors.
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Abstract
Reliable solid-state nanopore sensing requires stable, low-noise ionic current baselines. Existing stability evaluation methods often rely on subjective visual inspection. Here, we propose a robust quantitative framework that assesses nanopore wettedness and stability indicators through power spectral density (PSD) analysis of the noise floor in the measured ionic current and uses the resulting features to predict wettedness. A systematic comparison of multiple PSD fitting models and weighting strategies identified a five-component, five-parameter (5C5P) model coupled with high-frequency, low-PSD (HFLS) weighting as the most accurate and consistent approach for characterizing noise in the measured ionic current. Utilizing the noise coefficients from this optimized noise PSD fit, we applied logistic regression to predict nanopore wettedness. Among these coefficients, the 1/
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