Researchers used machine learning and life cycle assessment to evaluate the carbon emissions of magnesium silicate hydrate ...

Finally, the team constructed a model able to predict the cycle lives of lithium-metal batteries by applying machine learning methods to the charge/discharge data. The model proved able to make ...

Explaining the life cycle with technical terms about model ... and departments within an organization to ensure that machine learning models are deployed and maintained effectively.” ...

X Engineered Materials demonstrates how AI offers a path toward more resilient, sustainable, and future-ready manufacturing.

NIMS and SoftBank Corp. have jointly developed a model capable of predicting the cycle lives of high-energy-density lithium-metal batteries by applying machine learning methods to battery ...

Ocean color remote sensing (OCRS) provides crucial insights into marine ecosystems, detecting phytoplankton blooms, measuring ...

Large language models have captured the news cycle, but there are many other kinds of machine learning and deep learning with many different use cases. Amid all the hype and hysteria about ChatGPT ...

Superhydrides are materials that can store significantly more hydrogen than conventional hydrides and present a highly ...

Molecular machine learning (ML) underpins critical workflows in drug discovery, material science, and catalyst optimization by rapidly predicting molecular interactions and properties. For instance, ...