Resources

Battery informatics is a rapidly evolving field that employs machine learning and data-driven approaches to predict battery life and performance. By analyzing large datasets generated from battery testing and operation, researchers can develop predictive models that can optimize battery design, performance, and maintenance. Machine learning algorithms can identify complex relationships between battery materials, manufacturing processes, and operating conditions, enabling the development of more reliable and efficient battery systems.

SLAC-Stanford Battery Center is located at the 2nd floor of Arrillaga Science Center. The Labs have access to multiple gloveboxes, Humehoods, in situ AFM, electrode and cell fabrication. The Labs also have capabilities for synthesis and scale-up of next generation battery materials.

SSRL (Stanford Synchrotron Radiation Lightsource) is a world-renowned research facility that provides cutting-edge synchrotron radiation and X-ray capabilities to scientists and engineers from around the world. Its state-of-the-art instruments and techniques have enabled groundbreaking research in many fields, including battery science, and have contributed to the development of new materials and technologies.

The Cryo-EM (cryogenic electron microscopy) facility at SLAC, built and operated in partnership with Stanford University, is equipped with multiple state-of-the-art instruments for cryo-EM, a groundbreaking technology whose rapid development over the past few years has given scientists unprecedented views of the inner workings of the cell.