Dataset Overview and Structure

This folder contains all the data and analysis resources associated with our study, including raw and processed datasets, computational notebooks, and summary files. A Python notebook is also provided to highlight key components of the analysis pipeline and to demonstrate how the data was processed.

1. Fluorescence Center of Mass Tracking

As described in the Supplementary Information of the manuscript, the data analysis pipeline for extracting fluorescence center of mass from raw microscopy data consists of the following steps:

• Microscopy Acquisition: Time-lapse imaging of a region approximately 100 μm×100 μm100μm×100μm using wide-field fluorescence microscopy.

• Region of Interest Selection: Manual or automated identification of regions where DNA molecules are trapped in nanocavities or nanochannels.

• Noise Subtraction: Application of a background subtraction protocol based on the approach from Capaldi et al.[Ref. \cite{capaldi2018probing}], implemented via an ImageJ Macro tailored for high-throughput processing.

• Center of Mass Calculation: Frame-by-frame extraction of the fluorescence centroid for each tracked molecule, yielding time-resolved position trajectories.

The results of this pipeline are provided in the folder fluorescence_center_of_mass/, and match the tracking data presented in the main manuscript.

2. Frequency-Dependent Confinement

This section contains .csv files derived from the center of mass analysis across a range of driving frequencies and for multiple cavity diameters. These datasets were used to quantify the extent of confinement as a function of frequency, as shown in the main text. Data are organized within the folder frequency_dependence/.

3. Voltage-Dependent Confinement

Similar to the frequency analysis, this section includes .csv files containing center of mass data for experiments performed at different applied voltages. These measurements were used to investigate how confinement strength varies with voltage, and are stored in the folder voltage_dependence/.

4. Tension Measurements

We measure mechanical tension in DNA molecules confined across two adjacent nanocavities by tracking fluctuations in their relative positions. The fluctuations are fitted with a parabolic profile, and the resulting curvature is translated into force via the Marko–Siggia worm-like chain model. The corresponding datasets and plots are provided in the folder tension_measurements/.

5. Current Measurements and Polymer Partitioning

This section includes:

• Raw and processed current measurements, used to characterize electrokinetic behavior across trap geometries and signal configurations.

• Analysis of polymer partitioning, which quantifies the distribution of DNA molecules between cavity and channel regions.

These data are located in the folders current_measurements/ and partitioning/, respectively. Additional scripts used for analysis are provided where applicable.