Lab profile: Kristin Persson, LBNL/UC Berkeley

Imagine if the properties of all known materials were freely available at the click of a mouse to the entire global scientific community. No small task, but this is the ultimate aim of the Materials Project, co-founded and led by Kristin Persson at the University of California Berkeley (UC Berkeley) and the Lawrence Berkeley National Laboratory (LBNL). The project is harnessing the power of supercomputing and state-of-the-art electronic structure methods to calculate data on known and predicted materials.

Easy web-based access to materials information with millions of computed properties, analysis algorithms, and computational materials should, she hopes, facilitate and accelerate the design and development of new materials, particularly for energy storage and generation applications urgently needed to meet society’s needs in a changing environment.

Prior to joining UC Berkeley and LBNL, Persson received a PhD from the Royal Institute of Technology in Stockholm in Sweden. She is the recipient of many awards including the 2018 US Department of Energy, Secretary of Energy’s Achievement Award, the 2017 TMS Faculty Early Career Award, the LBNL Director’s award for Exceptional Scientific Achievement in 2013 and she is a 2018 Kavli Fellow.

Kristin talked to Materials Today about her current research and future plans.

How long has your group been running?

The Persson Group started in 2008 when I joined LBNL and expanded in 2015 when I was appointed as a Professor in the Department of Materials Science and Engineering at UC Berkeley. In 2011, I co-founded the Materials Project and have been its Director since its inception. 

How many staff currently makes up your group?

In addition to me, the Persson Group houses four staff, 10 postdocs and 17 graduate students.

What are the major themes of research in your group?

Within the Persson group, we leverage the software and data infrastructure of the Materials Project, together with our expertise in materials informatics, to study the physics and chemistry of materials, particularly for energy production and storage applications.

Current areas of focus include the design of novel photocatalysts, multivalent battery electrode materials, Li-ion battery electrode materials, polar materials and liquid electrolytes for Li energy storage solutions and beyond.

As part of our mission in The Materials Project, we are endeavoring to compute the properties of all known materials and to provide this data, analysis algorithms, and computational materials applications free of charge to the global scientific community. The ultimate goal of the Materials Project is to reduce drastically the time needed to invent new materials to serve societal needs, in particular advancing clean energy solutions.

How and why did you come to work in these areas?

My graduate work in Sweden focused on electronic structure methods of metals and alloys, but my passion for data-driven materials design can be tracked to my years at Massachusetts Institute of Technology as a postdoctoral researcher. In particular, in 2005 I was working as part of a consulting team with a well-known company that manufactures alkaline batteries to try something that had never been done before: compute the properties of many thousands of materials using density functional theory to identify promising new materials for these batteries. As part of this work, we built the first database of tens of thousands of computed compounds and developed automated analysis algorithms. I brought my expertise in first-principles materials informatics to LBNL and was able to raise our first grant in 2010 that led to the birth of the Materials Project.  

What facilities and equipment does your lab have?

We utilize some of the world’s most powerful supercomputers for our work. These include machines at the National Energy Research Computing Center (NERSC), the Argonne Leadership Computing Facility (ALCF), and the NREL Computational Science Center. Our group uses hundreds of millions of CPU hours each year to perform atomistic simulations and compute the properties of materials. In addition to the high-performance computing hardware, our group houses and develops the majority of the software infrastructure that powers the Materials Project; including workflows, APIs, database builders and analyses.  

Do you have a favorite piece of kit or equipment?

This may be a little unconventional, but Pourbaix diagrams, which show the stability of compounds in aqueous systems, are one of my favorite tools for investigating materials systems. I developed the scheme whereby we can combine computed and experimental information in these diagrams, which has led to over 80,000 available diagrams on the Materials Project and one of our most used Applications.

What do you think has been your most influential work to date?

The Materials Project has had the largest impact by far. We have more than 90,000 active users from both industry and academia all over the world and that number is growing exponentially. Every day, over one million records are delivered through our API to our users. Feedback from our users and seeing the number of studies published that use Materials Project data or open-source tools has been extremely fulfilling for the whole team and we’re excited to continue to provide the materials research community with more data and materials design tools in the future. 
What is the key to running a successful group?

I think it is finding and retaining outstanding students, postdocs, and staff. All of our success is built on their creativity, passion, insight, and hard work.

How do you plan to develop your group in the future?

We are continuing to expand our expertise into areas such as machine learning and synthesis. Our group also enjoys several collaborations with other research groups, industry partners, and institutions, which is driving our diversification and growth. 

Key publications

1. A. Jain, S. P. Ong, G. Hautier, W. Chen, W. D. Richards, S. Dacek, S. Cholia, D. Gunter, D. Skinner, G. Ceder, K. A. Persson. Commentary: The Materials Project: A materials genome approach to accelerating materials innovation. Appl. Mat., 1 (2013), 011002. 
2. K. A. Persson, V. A. Sethuraman, L. J. Hardwick, Y. Hinuma, Y. S. Meng, A. van der Ven, V. Srinivasan, R. Kostecki, G. Ceder. Lithium diffusion in graphitic carbon. J. Phys. Chem. Lett., 1 (2010), 1176-1180. 
3. A. Jain, Y. Shin, K. A. Persson. Computational predictions of energy materials using density functional theory. Nature Reviews Materials, 1 (2016), 15004. 
4. M. Liu, Z. Rong, R. Malik, P. Canepa, A. Jain, G. Ceder, K. A. Persson. Spinel compounds as multivalent battery cathodes: a systematic evaluation based on ab initio calculations. Energy Environ. Sci., 8 (2015), 964-974.
5. N. N. Rajput, X. Qu, N. Sa, A. K. Burrell, K. A. Persson. Coupling between Stability and Ion Pair Formation in Magnesium Electrolytes from First-Principles Quantum Mechanics and Classical Molecular Dynamics. J. Am. Chem. Soc. 137 (2015) 3411-3420. 
6. S. P. Ong, S. Cholia, A. Jain, M. Brafman, D. Gunter, G. Ceder, K. A. Persson. The Materials Application Programming Interface (API): A simple, flexible and efficient API for materials data based on REpresentational State Transfer (REST) principles. Comp. Mater. Sci., 97 (2015) 209-215. 
7. S. P. Ong, W. D. Richards, A. Jain, G. Hautier, M. Kocher, S. Cholia, D. Gunter, V. L. Chevier, K. A. Persson, G. Ceder. Python Materials Genomics (pymatgen): A robust, open-source python library for materials analysis. Comp. Mate. Sci. 68 (2013) 314-319.
8. X. Qu, A. Jain, N. N. Rajput, L. Cheng, Y. Zhang, S. P. Ong, M. Brafman, E. Maginn, L. A. Curtiss, K. A. Persson. The Electrolyte Genome project: A big data approach in battery materials discovery. Comp. Mater. Sci. 103 (2015) 56-67. 
9. G. Ceder, K. A. Persson. How Supercomputers Will Yield a Golden Age of Materials Science. Sci. Am. 309 (2013), 36-40. [Originally published as The Stuff of Dreams.] 
10. M. Aykol, S. S. Dwaraknath, W. Sun, K. A. Persson. Thermodynamic limit for synthesis of metastable inorganic materials. Sci. Adv. 4 (2018) eaaq0148.