STM Imaging · foundry-ml
atomvison_atomistic_stm_images_2d_materials_unique_chemical_compositions_structure_v1-1
Simulated scanning tunnelling microscopy images of 2D materials for machine learning on atomic-scale imaging.
What atomvison_atomistic_stm_images_2d_materials_unique_chemical_compositions_structure_v1-1 is
AtomVision Atomistic STM Images 2D Materials Unique Chemical Compositions Structure v1-1 is a materials science and physics dataset published by foundry-ml. It contains simulated scanning tunnelling microscopy (STM) images representing two-dimensional materials with distinct chemical compositions.
The dataset provides structured visual data to support the development and evaluation of machine learning algorithms for atomic-resolution microscopy.
Key facts
- Publisher
- foundry-ml
- Category
- STM Imaging
- Fields
- Materials science, physics
- Content type
- Simulated scanning tunnelling microscopy (STM) images
What you can use it for
- Machine learning for atomic-resolution microscopy
- Training and validating computer vision and machine learning models on atomic-scale microscopy data.
- 2D material characterisation
- Studying simulated scanning tunnelling microscopy representations of two-dimensional materials.
- Compositional analysis
- Investigating image features associated with unique chemical compositions and structures.
Explore the data
No licence declared
The authors have not published a licence, which means no permission to redistribute the data has been granted to anyone. The rows are not served here; read them on the original dataset page.Strengths and limits
Good at
- Offers simulated scanning tunnelling microscopy data representing unique chemical compositions in 2D materials.
- Explicitly curated to support machine learning tasks on atomic-resolution imagery.
Watch out for
- Consists of simulated rather than experimental scanning tunnelling microscopy images.
- Specific image resolutions, formats, and simulation methods are not detailed in the dataset records.
Questions
Can I look inside atomvison_atomistic_stm_images_2d_materials_unique_chemical_compositions_structure_v1-1 without downloading it?
Not here: it declares no licence, so no permission to redistribute its rows has been granted. Its description and statistics are still shown.
What licence is atomvison_atomistic_stm_images_2d_materials_unique_chemical_compositions_structure_v1-1 under?
Its authors have not declared a licence, which means no permission to reuse or redistribute it has been granted.
What type of data does this dataset contain?
It contains simulated scanning tunnelling microscopy (STM) images corresponding to two-dimensional materials with unique chemical compositions.
What are the primary applications of the dataset?
It is developed to support machine learning workflows on atomic-resolution microscopy.
Are the microscopy images experimental?
No, the images are computationally simulated.
Written from atomvison_atomistic_stm_images_2d_materials_unique_chemical_compositions_structure_v1-1's own dataset card. Statements citing a figure that does not appear there are removed before publication. Licence and running details come from our registry.