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Welcome to CederGroupHub 👋

The Computational and Experimental Design of Emerging materials Research group (CEDER) is a part of the Department of Materials Science and Engineering at UC Berkeley and the Materials Sciences Division at Lawrence Berkeley National Laboratory.

Our goal is to better design high quality functional materials by mapping the relationship between materials structures and their physical and chemical properties through a combined theoretical and experimental approach. Our group integrates all the aspects of materials research from developing the fundamental understanding to the design, synthesis and testing of new bulk and nano materials. We combine computational approaches in quantum mechanics, solid state physics and statistical mechanics, with selected experiments into a complimentary research strategy to investigate materials in the energy field. We are one of the premier groups in high-throughput computing and the Materials Genome and contribute extensively to the Materials Project.

Applied areas of interest are in energy storage based on Li, Na, and multi-valent ion intercalation, thermoelectrics, and other functional materials. On the fundamental side, the group develops expertise in electronic structure, ab-initio thermodynamics of bulk and nano systems, diffusion, electron transport, structure prediction, and data mining. We are also integrating these methods with newly developed tools for autonomous experimentation and AI-enabled data interpretation. Over the last decade, we have successfully performed many research projects supported by various companies and governments.

Pinned

  1. chgnet chgnet Public

    Pretrained universal neural network potential for charge-informed atomistic modeling https://chgnet.lbl.gov

    Python 196 48

  2. text-mined-synthesis_public text-mined-synthesis_public Public

    Codes for text-mined solid-state reactions dataset

    Python 57 18

  3. smol smol Public

    Statistical Mechanics on Lattices

    Python 57 14

  4. sparse-lm sparse-lm Public

    Sparse Linear Regression Models

    Python 15 7

  5. LimeSoup LimeSoup Public

    LimeSoup is a package to parse HTML or XML papers from different publishers.

    Python 19 7

  6. text-mined-solution-synthesis_public text-mined-solution-synthesis_public Public

    Jupyter Notebook 11 3

Repositories

Showing 10 of 30 repositories