A computational modeling suite for toxicity estimation of PFAS ​“forever chemicals”

Argonne’s 3D X-ray microscope employs computer vision to detect features of interest and capture and visualize data.

Argonne’s self-driving chemist platform executes an autonomous method for chemical discovery to improve chemical reactions and create new materials.

An important component of self-driving laboratories, dexterous, free-roaming robots — basically, robotic scientists – will free up researchers for more complex tasks.

Argonne is leading a collaboration of DOE laboratories and the National Cancer Institute to address cancer research challenges.

Argonne has been applying machine and deep learning techniques to build predictive models for diagnosis of traumatic brain injury symptoms.

Argonne combines advances in AI with extreme and edge computing to unlock new opportunities in astrophysics.

The ultimate goal of the project is to enable design of peptides with predictable functions. The capabilities we develop will be critical in advancing scientific discoveries in biology and other fields.