Categories: AI/ML News

Machine-learning models help discover a material for film capacitors with record-breaking performance

The Department of Energy’s Lawrence Berkeley National Laboratory (Berkeley Lab) and several collaborating institutions have successfully demonstrated a machine-learning technique to accelerate the discovery of materials for film capacitors—crucial components in electrification and renewable energy technologies. The technique was used to screen a library of nearly 50,000 chemical structures to identify a compound with record-breaking performance.
AI Generated Robotic Content

Share
Published by
AI Generated Robotic Content

Recent Posts

Chroma Radiance, Mid training but the most aesthetic model already imo

submitted by /u/Different_Fix_2217 [link] [comments]

7 hours ago

From human clicks to machine intent: Preparing the web for agentic AI

For three decades, the web has been designed with one audience in mind: People. Pages…

8 hours ago

Best GoPro Camera (2025): Compact, Budget, Accessories

You’re an action hero, and you need a camera to match. We guide you through…

8 hours ago

What tools would you use to make morphing videos like this?

submitted by /u/nikitagent [link] [comments]

1 day ago

Bias after Prompting: Persistent Discrimination in Large Language Models

A dangerous assumption that can be made from prior work on the bias transfer hypothesis…

1 day ago

Post-Training Generative Recommenders with Advantage-Weighted Supervised Finetuning

Author: Keertana Chidambaram, Qiuling Xu, Ko-Jen Hsiao, Moumita Bhattacharya(*The work was done when Keertana interned…

1 day ago