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Software and tools

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Scott Lab GitHub
Public code, notebooks, and data repositories from the Scott Lab.

Simulated nanostructures generated with Construction Zone

Construction Zone
An open-source Python package for building nanoscale atomic models for simulation workflows.

Image adapted from Rangel DaCosta et al. (2024), CC BY 4.0.

Public datasets

HRTEM segmentation and defect identification

Gold and cadmium selenide nanoparticle micrographs with segmentation maps for neural network training. Paper: Machine Learning Pipeline for Segmentation and Defect Identification from HRTEM Data.

Receptive field and network complexity

TEM images of gold nanoparticles of different sizes on ultrathin carbon substrates, with segmentation labels. Paper: Understanding the Influence of Receptive Field and Network Complexity in Neural-Network-Guided TEM Image Analysis.

Examples of tellurium nanoparticles and mirror-image handedness labeling

Chiral nanoparticle handedness

Images of individual tellurium nanoparticles and handedness labels for classifier training. Paper: npj Computational Materials (2022).

Figure 1 from Groschner et al. (2022), CC BY 4.0.

Construction Zone synthetic HRTEM datasets

Generated atomic structures, simulated images, and example trained models for synthetic-data studies. Paper: npj Computational Materials (2024).

HRTEM generalization across experimental parameters

407 raw nanoparticle images with segmentation maps and 13 curated datasets spanning imaging and material parameters. Paper: Microscopy and Microanalysis (2024).

Cobalt oxide nanoparticle images and segmentation

Example TEM images, model-predicted segmentation results, and hand-labeled training images for statistical analysis of cobalt oxide nanoparticles. Paper: ACS Nano (2024).

Tutorials

Transfer learning for HRTEM analysis

A tutorial with case studies on when and how transfer learning works for neural network analysis of HRTEM images, using simulated datasets. Paper: Strategies for effective transfer learning for HRTEM analysis with neural networks, Elemental Microscopy (2026).

Fused multi-modal electron microscopy

A beginner’s guide, with guided computation tutorials for fusing EELS or X-EDS maps with HAADF images to improve chemical resolution (collaboration with Prof. Hovden, U Mich). Paper: Fused Multi-Modal Electron Microscopy: A beginner’s guide, Elemental Microscopy (2024).

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