Kristin A. Persson

Bio: Kristin A. Persson is an academic researcher from Lawrence Berkeley National Laboratory. The author has contributed to research in topics: Electrolyte & Solvation. The author has an hindex of 77, co-authored 271 publications receiving 25201 citations. Previous affiliations of Kristin A. Persson include Pennsylvania State University & Argonne National Laboratory.

Commentary: The Materials Project: A materials genome approach to accelerating materials innovation

Abstract: Accelerating the discovery of advanced materials is essential for human welfare and sustainable, clean energy. In this paper, we introduce the Materials Project (www.materialsproject.org), a core program of the Materials Genome Initiative that uses high-throughput computing to uncover the properties of all known inorganic materials. This open dataset can be accessed through multiple channels for both interactive exploration and data mining. The Materials Project also seeks to create open-source platforms for developing robust, sophisticated materials analyses. Future efforts will enable users to perform ‘‘rapid-prototyping’’ of new materials in silico, and provide researchers with new avenues for cost-effective, data-driven materials design. © 2013 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution 3.0 Unported License.

Formation enthalpies by mixing GGA and GGA + U calculations

Abstract: Standard approximations to the density functional theory exchange-correlation functional have been extraordinary successful, but calculating formation enthalpies of reactions involving compounds with both localized and delocalized electronic states remains challenging. In this work we examine the shortcomings of the generalized gradient approximation (GGA) and GGA+U in accurately characterizing such difficult reactions. We then outline a methodology that mixes GGA and GGA+U total energies (using known binary formation data for calibration) to more accurately predict formation enthalpies. We demonstrate that for a test set of 49 ternary oxides, our methodology can reduce the mean absolute relative error in calculated formation enthalpies from approximately 7.7–21% in GGA+U to under 2%. As another example we show that neither GGA nor GGA+U alone accurately reproduces the Fe-P-O phase diagram; however, our mixed methodology successfully predicts all known phases as stable by naturally stitching together GGA and GGA+U results. As a final example we demonstrate how our technique can be applied to the calculation of the Li-conversion voltage of LiFeF3. Our results indicate that mixing energies of several functionals represents one avenue to improve the accuracy of total energy computations without affecting the cost of calculation.

Odyssey of Multivalent Cathode Materials: Open Questions and Future Challenges

Abstract: The rapidly expanding field of nonaqueous multivalent intercalation batteries offers a promising way to overcome safety, cost, and energy density limitations of state-of-the-art Li-ion battery technology. We present a critical and rigorous analysis of the increasing volume of multivalent battery research, focusing on a wide range of intercalation cathode materials and the mechanisms of multivalent ion insertion and migration within those frameworks. The present analysis covers a wide variety of material chemistries, including chalcogenides, oxides, and polyanions, highlighting merits and challenges of each class of materials as multivalent cathodes. The review underscores the overlap of experiments and theory, ranging from charting the design metrics useful for developing the next generation of MV-cathodes to targeted in-depth studies rationalizing complex experimental results. On the basis of our critical review of the literature, we provide suggestions for future multivalent cathode studies, including a...

I and i

Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

Fast parallel algorithms for short-range molecular dynamics

Abstract: Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

Commentary: The Materials Project: A materials genome approach to accelerating materials innovation

Abstract: Accelerating the discovery of advanced materials is essential for human welfare and sustainable, clean energy. In this paper, we introduce the Materials Project (www.materialsproject.org), a core program of the Materials Genome Initiative that uses high-throughput computing to uncover the properties of all known inorganic materials. This open dataset can be accessed through multiple channels for both interactive exploration and data mining. The Materials Project also seeks to create open-source platforms for developing robust, sophisticated materials analyses. Future efforts will enable users to perform ‘‘rapid-prototyping’’ of new materials in silico, and provide researchers with new avenues for cost-effective, data-driven materials design. © 2013 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution 3.0 Unported License.