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Anubhav Jain

Bio: Anubhav Jain is an academic researcher from Lawrence Berkeley National Laboratory. The author has contributed to research in topics: Thermoelectric materials & Ion exchange. The author has an hindex of 58, co-authored 266 publications receiving 21124 citations. Previous affiliations of Anubhav Jain include University of California, Berkeley & Management Development Institute.


Papers
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Journal ArticleDOI
TL;DR: The Materials Project (www.materialsproject.org) is a core program of the Materials Genome Initiative that uses high-throughput computing to uncover the properties of all known inorganic materials as discussed by the authors.
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.

6,566 citations

Journal ArticleDOI
TL;DR: The pymatgen library as mentioned in this paper is an open-source Python library for materials analysis that provides a well-tested set of structure and thermodynamic analyses relevant to many applications, and an open platform for researchers to collaboratively develop sophisticated analyses of materials data obtained both from first principles calculations and experiments.

2,364 citations

Journal ArticleDOI
TL;DR: In this paper, the difference between Na-ion and Li-ion based intercalation chemistries in terms of three key battery properties, voltage, phase stability and diffusion barriers was compared.
Abstract: To evaluate the potential of Na-ion batteries, we contrast in this work the difference between Na-ion and Li-ion based intercalation chemistries in terms of three key battery properties—voltage, phase stability and diffusion barriers. The compounds investigated comprise the layered AMO2 and AMS2 structures, the olivine and maricite AMPO4 structures, and the NASICON A3V2(PO4)3 structures. The calculated Na voltages for the compounds investigated are 0.18–0.57 V lower than that of the corresponding Li voltages, in agreement with previous experimental data. We believe the observed lower voltages for Na compounds are predominantly a cathodic effect related to the much smaller energy gain from inserting Na into the host structure compared to inserting Li. We also found a relatively strong dependence of battery properties on structural features. In general, the difference between the Na and Li voltage of the same structure, ΔVNa–Li, is less negative for the maricite structures preferred by Na, and more negative for the olivine structures preferred by Li. The layered compounds have the most negative ΔVNa–Li. In terms of phase stability, we found that open structures, such as the layered and NASICON structures, that are better able to accommodate the larger Na+ ion generally have both Na and Li versions of the same compound. For the close-packed AMPO4 structures, our results show that Na generally prefers the maricite structure, while Li prefers the olivine structure, in agreement with previous experimental work. We also found surprising evidence that the barriers for Na+ migration can potentially be lower than that for Li+ migration in the layered structures. Overall, our findings indicate that Na-ion systems can be competitive with Li-ion systems.

1,138 citations

01 Jan 2012
Abstract: To evaluate the potential of Na-ion batteries, we contrast in this work the difference between Na-ion and Li-ion based intercalation chemistries in terms of three key battery properties—voltage, phase stability and diffusion barriers. The compounds investigated comprise the layered AMO2 and AMS2 structures, the olivine and maricite AMPO4 structures, and the NASICON A3V2(PO4)3 structures. The calculated Na voltages for the compounds investigated are 0.18–0.57 V lower than that of the corresponding Li voltages, in agreement with previous experimental data. We believe the observed lower voltages for Na compounds are predominantly a cathodic effect related to the much smaller energy gain from inserting Na into the host structure compared to inserting Li. We also found a relatively strong dependence of battery properties on structural features. In general, the difference between the Na and Li voltage of the same structure, DVNa–Li, is less negative for the maricite structures preferred by Na, and more negative for the olivine structures preferred by Li. The layered compounds have the most negative DVNa–Li. In terms of phase stability, we found that open structures, such as the layered and NASICON structures, that are better able to accommodate the larger Na+ ion generally have both Na and Li versions of the same compound. For the close-packed AMPO4 structures, our results show that Na generally prefers the maricite structure, while Li prefers the olivine structure, in agreement with previous experimental work. We also found surprising evidence that the barriers for Na+ migration can potentially be lower than that for Li+ migration in the layered structures. Overall, our findings indicate that Na-ion systems can be competitive with Li-ion systems.

1,109 citations

Journal ArticleDOI
TL;DR: In this paper, the authors examined the shortcomings of the generalized gradient approximation (GGA) and GGA+U in accurately characterizing such difficult reactions and then outline a methodology that mixes GGA and GA+U total energies (using known binary formation data for calibration) to more accurately predict formation enthalpies.
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.

842 citations


Cited by
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[...]

08 Dec 2001-BMJ
TL;DR: There is, I think, something ethereal about i —the square root of minus one, which seems an odd beast at that time—an intruder hovering on the edge of reality.
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 …

33,785 citations

01 May 1993
TL;DR: 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.
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.

29,323 citations

Book
01 Jan 1995
TL;DR: In this article, Nonaka and Takeuchi argue that Japanese firms are successful precisely because they are innovative, because they create new knowledge and use it to produce successful products and technologies, and they reveal how Japanese companies translate tacit to explicit knowledge.
Abstract: How has Japan become a major economic power, a world leader in the automotive and electronics industries? What is the secret of their success? The consensus has been that, though the Japanese are not particularly innovative, they are exceptionally skilful at imitation, at improving products that already exist. But now two leading Japanese business experts, Ikujiro Nonaka and Hiro Takeuchi, turn this conventional wisdom on its head: Japanese firms are successful, they contend, precisely because they are innovative, because they create new knowledge and use it to produce successful products and technologies. Examining case studies drawn from such firms as Honda, Canon, Matsushita, NEC, 3M, GE, and the U.S. Marines, this book reveals how Japanese companies translate tacit to explicit knowledge and use it to produce new processes, products, and services.

7,448 citations

Journal ArticleDOI
TL;DR: The Materials Project (www.materialsproject.org) is a core program of the Materials Genome Initiative that uses high-throughput computing to uncover the properties of all known inorganic materials as discussed by the authors.
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.

6,566 citations