A new AI tool has identified five promising metal oxide structures which could be used to replace lithium-ion batteries. The ...

To overcome these hurdles, the NJIT team developed a novel dual-AI approach: a Crystal Diffusion Variational Autoencoder (CDVAE) and a finely tuned Large Language Model (LLM). Together, these AI tools ...

Specifically, the team used generative AI to discover new porous materials that could make multivalent-ion batteries a viable replacement for lithium-based systems. These next-generation batteries ...

A gradual fine-tuning strategy was employed, progressively unfreezing the last 6 layers of ESM-2 encoder and applying discriminative learning rates with the AdamW optimizer. The model was trained ...

The trained neural autoencoder is subjected to a sanity check by computing the MSE for the 40-item validation dataset. The MSE is 0.0017 which is very close to the MSE of the dataset being reduced, ...