1000 open access electron microscopy images displaying nanoparticles and ordered patterns

Using this database, recognition of complex patterns of nanoparticles, analysis of ordering effects, and location of arrays of nanoparticles and individual nanoparticles can be carried out. Compatible with development of artificial intelligence projects and machine learning algorithms.

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We are happy to share with you a new database containing 1000 electron microscopy images of palladium nanoparticles attached to the carbon surface (Pd/C). Two distinct datasets were created - with and without ordering of nanoparticles on the carbon surface.

Have a look on marvelous traceries made by nature!

Highly valuable nanomaterials developed today are based on hierarchical structural organization, where individual nanoparticles are not arranged in a chaotic manner, but follow specific geometrical patterns. It is a cutting edge level of modern nanotechnologies to understand these geometrical patterns and develop new generation of materials and devices. This challenging task can hardly be solved without usage of appropriate computational algorithms for automated analysis of the nanoscale patterns (large number of nanoparticles has to be analyzed).

In this Scientific Data article we provide such a database for developing artificial intelligence and machine learning algorithms and applications.

Link to the published article: https://doi.org/10.1038/s41597...

Link to the Dataset 1 - ordered: https://doi.org/10.6084/m9.fig...

Link to the Dataset 2 -disordered: https://doi.org/10.6084/m9.fig...

Valentine Ananikov

Prof., Zelinsky Institute of Organic Chemistry, Russian Academy of Sciences

Research interests - molecular complexity and transformations. How do molecules live and chemical reactions run?