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Power Spectral Density Analysis of Solid-State Nanopore Signals: Application to Stability Estimation
Pratima Upretee1, Eric Beamish2, Wouter Botermans2
1IDLab, Department of Electronics and Information Systems, Ghent University - imec, Technologiepark Zwijnaarde 122, Ghent 9052, Belgium.
ACS Omega
|May 4, 2026
Summary
We developed a quantitative method using power spectral density (PSD) analysis to automatically assess nanopore stability and predict wettedness. This data-driven framework improves the reliability of solid-state nanopore sensing platforms.
Area of Science:
- Nanotechnology
- Biosensing
- Physical Chemistry
Background:
- Solid-state nanopore sensing demands stable, low-noise ionic current baselines for reliable measurements.
- Current methods for evaluating nanopore stability often rely on subjective visual inspection, limiting throughput and consistency.
Purpose of the Study:
- To establish a robust, quantitative framework for assessing nanopore wettedness and stability using power spectral density (PSD) analysis.
- To develop an automated method for predicting nanopore wettedness, moving beyond subjective evaluations.
Main Methods:
- Utilized power spectral density (PSD) analysis to characterize the noise floor of ionic current measurements.
- Compared multiple PSD fitting models and weighting strategies, identifying a five-component, five-parameter (5C5P) model with high-frequency, low-PSD (HFLS) weighting as optimal.
- Applied logistic regression using noise coefficients (1/f noise, white-noise, low-frequency noise) and applied voltage to predict nanopore wettedness.
Main Results:
- The optimized PSD analysis framework accurately characterized nanopore noise.
- A logistic regression classifier trained on noise features achieved a high median F1-score of 98% for wettedness prediction across varied voltages and pore dimensions.
- The classifier demonstrated reliable performance in segment-wise evaluations, mimicking real-time operation.
Conclusions:
- The proposed physics-informed, data-driven framework enables automated, quantitative wettedness prediction and stability assessment for solid-state nanopores.
- This approach offers a pathway toward reliable real-time quality control for high-throughput nanopore sensing platforms.
