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What does Big mean in the realm of materials science data?
Big data has ushered in a new wave of predictive power using machine learning models. In this work, we assess what big means in the context of typical materials-science... -
Rapid detection of rare events from in situ X-ray diffraction data using mach...
High-energy X-ray diffraction methods can non-destructively map the 3D microstructure and associated attributes of metallic polycrystalline engineering materials in their bulk... -
Predicted perovskites dataset
A dataset of 10,790 predicted perovskites, along with their 5 most similar experimental materials, used to test the effectiveness of the VAE model. -
Experimental materials dataset
A dataset of 2104 experimental materials, including their crystal structure information, used to train a Variational Autoencoder (VAE) model. -
Porous Organic Cages
The dataset used for machine learning accelerated discovery of porous organic cages. -
Metal-Organic Frameworks
The dataset used for machine learning accelerated discovery of metal-organic frameworks. -
Transition-metal complexes
The dataset used for machine learning accelerated discovery of transition-metal complexes. -
Test dataset
A dataset of 200 samples with 1283 resolution, generated using VGrain software with a regularity of 0.73 and uniform random orientation
