Disentangled variational autoencoder (D-VAE) separates materials properties from the latent space by conditioning to make inverse materials design more efficient and transparent. It combines labeled ...

Researchers use large language models to streamline nanoscopic material design for advanced optical systems like camera ...

Rendered model showing a complex 3D structure made up of thousands of repeating microscopic patterns. By teaching an AI model to predict the behavior of these patterns, the Drexel team can design ...

Researchers developed a machine-learning framework that can predict a key property of heat dispersion in materials that is up to 1,000 times faster than other AI methods, and could enable scientists ...