DiffusionLab

DiffusionLab analyzes single-particle and single-molecule trajectories from super-resolution localization microscopy to extract motion-related parameters and characterize heterogeneous diffusion in systems such as inorganic porous hosts (e.g., zeolites).

Key Features:

• Trajectory Classification: Implements a two-step classification that groups trajectories into populations based on motion characteristics using machine learning or manual classification.
• Motion Analysis Tailoring: Applies motion analysis methods tailored to each classified population to account for distinct motion behaviors.
• Quantitative Mean Squared Displacement (MSD) Analysis: Performs quantitative MSD analyses on individual trajectories or trajectory populations.
• Diffusion Constant Calculation: Computes diffusion constants from individual long trajectories or as averages derived from multiple shorter trajectories.
• Handling Short and Heterogeneous Trajectories: Addresses challenges posed by short and heterogeneous trajectories commonly encountered in mass transport studies.
• Simulated Data Validation: Demonstrated on simulated datasets that mimic motion types observed in environments such as zeolites.

Scientific Applications:

• Single-Particle Tracking Analysis: Reveals heterogeneities in molecular or particle motion that are not detectable by ensemble methods.
• Mass Transport Characterization in Inorganic Porous Hosts: Characterizes diffusive behavior and mass transport phenomena in inorganic porous hosts, including zeolites.

Methodology:

Classify trajectories into motion-based populations (machine learning or manual), perform tailored motion analyses including MSD calculation, and compute diffusion constants per trajectory or as averages from multiple short trajectories; validation demonstrated on simulated datasets.