Computational Codes for Point Defect Dynamics in 2D Colloidal Crystals

Huang's repository contains Jupyter Notebook codes and data for analyzing Brownian motion of point defects in a 2D hexagonal colloidal crystal. The 32.8 MB ZIP archive includes a computational pipeline for extracting drift vectors, diffusion matrices, and reconstructing stochastic potentials from experimental trajectories. The dataset was last updated on 2026-05-09 and is shared under a CC-BY-4.0 license.

Use Cases

• Extract spatially resolved drift and diffusion tensors based on the conditional moments method described.
• Reconstruct a stochastic potential landscape for point defects based on Fourier series fitting of drift and diffusion data.
• Simulate defect trajectories using the reconstructed Stochastic Differential Equation (SDE) via the Euler–Maruyama method.
• Identify critical points like minima and saddle points in the potential to calculate energy barriers.
• Evaluate the goodness-of-fit for the Fourier expansion model based on the weighted coefficient of determination R².

Strengths

• Includes a complete, documented computational pipeline with 7 specific Jupyter Notebooks.
• Provides both raw experimental trajectory CSV files and intermediate/final NPZ outputs.
• The 32.8 MB size suggests a contained but non-trivial collection of code and data.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count for the experimental trajectory data is unknown, which may limit suitability assessment.
• The description is specific to the methodology but does not detail the scale or source of the underlying experimental data.

Provenance

Source

figshare, author Huang.

Collection Method

Codes implement analysis of experimental trajectories, likely from a laboratory study.

Freshness

Last updated 2026-05-09 10:19:50; freshness should be verified.