All programming languages and levels of experience are welcome! How We Are Different. There are dozens of local meetup groups that teach people how to code. We are building a local community of friendly, creative, highly-motivated programmers in the Berkeley area.

Now that I lead a research group, I am rarely able to conduct research myself anymore. Instead, one my of main roles is to guide the others members of my group.

Harnessing the power of supercomputing and state of the art electronic structure methods, the Materials Project provides open web-based access to computed information on known and predicted materials as well as powerful analysis tools to inspire and design novel materials. Search for materials information by chemistry, composition, or property. Find candidate materials for lithium batteries. Get voltage profiles and oxygen evolution data.

We are proud to be part of a collaborative publication with the Laboratory of Energy Storage and Conversion. Ensemble learning of X-ray Absorption Spectra. Providing an important new public resource for the analysis of XAS to all materials researchers. Finally, the ELSIE algorithm itself has been made available as part of Veidt. An open source machine learning library for materials science.

This picture is all the system of this web site. Available data associated with Materials Project IDs. Crystal structures obtained from the Materials Project. The contents of this web site are licensed under a Creative Commons Attribution 4. Unless another license is specially mentioned in each web page.

How to read this manual. Cloning of ATK Python objects. Note on Spin in low level interface functions. Built-in parameter sets in ATK-SE. Introduction to Atomistix ToolKit and Virtual NanoLab.

An Exploration of the Surfaces and Wulff shapes of the Elements. Click on any element to start. A collaboration between the Materials Virtual Lab. Ong, Surface Energies of Elemental Crystals.