THE ANNUAL 2012 DEIXIS DEPARTMENT OF ENERGY COMPUTATIONAL SCIENCE GRADUATE FELLOWSHIP SCIENCE GRADUATE OF ENERGY COMPUTATIONAL DEPARTMENT COMPUTATION SHINES IN PHOTOVOLTAICS SEARCH Anubhav Jain’s Practicum Predicts New Energy-Capturing Materials PAGE 5 THE ANNUAL TABLE OF CONTENTS DEIXIS DEIXIS, The DOE CSGF Annual is published by the Krell Institute. Krell administers the Department of Energy Computational Science 13 Graduate Fellowship (DOE CSGF) program for the DOE under contract DE-FG02-97ER25308. 9 For additional information about the DOE CSGF program, the Krell Institute or topics covered 20 22 in this publication, please contact: 26 Editor, DEIXIS Krell Institute 1609 Golden Aspen Drive, Suite 101 Ames, IA 50010 (515) 956-3696 www.krellinst.org/csgf PRIMED TO MEET PRIORITIES 4 20 26 Copyright 2012 Krell Institute. Practicum Profiles Alumni Profiles Winning Essays All rights reserved. The Department of Energy Computational Science Graduate Not Your Usual Summer Internship Alumni Span the Globe Encouraging Communication Fellowship was established to train scientists who can apply the United States’ growing computational power to important national needs, 5 Anubhav Jain 20 Jeffrey Hittinger 26 Kenley Pelzer, DEIXIS (ΔΕΙΞΙΣ — pronounced da¯ksis) transliterated including those of the DOE. This issue of DEIXIS provides examples Research Could Illuminate Livermore Alumnus Winner from classical Greek into the Roman alphabet, means a display, mode or process of proof; the process of of how fellows and alumni do just that. Promising Photovoltaics Fields Hard Problems A Place in the Sun showing, proving or demonstrating. DEIXIS can For example, the department emphasizes the rapid development and Hockey Pucks also refer to the workings of an individual’s keen intellect, or to the means by which such individuals, of innovative materials for clean energy production and conservation. 9 Brian Lockwood 28 Paul M. Sutter, e.g. DOE CSGF fellows, are identified. Fellow Anubhav Jain, profiled in this issue, helps drive that research with Fellow Probes Probability in 22 Richard Katz Honorable Mention the Materials Project, a database of calculated compound properties. Quantification Quest Delving into the Deep Earth A New View on Old Light DEIXIS is an annual publication of the Department of Energy Computational Science Graduate Fellowship The DOE CSGF also addresses the rising demand for scientists program that highlights the work of fellows and alumni. capable of implementing and using exascale computers – machines 13 Eric Chi 24 Jimena Davis capable of a million trillion (1018) calculations per second – expected to Movie Challenge Sparks Tackling Uncertainty in The DOE CSGF is funded by the Office of Science and the National Nuclear Security Administration’s Office come on line later in this decade. Fellows Brian Lockwood and Hayes Practicum – and a Sequel Chemical Vulnerability 30 of Defense Programs. Stripling research uncertainty quantification, a key tool for maximizing Howes Scholars exascale potential. 17 Hayes Stripling IV Saluted for Research and Service The fellowship meets these goals with a unique program that Sampling Surrogates Cover art and images on pages 5 and 9 appear courtesy creates well-rounded students and exposes them to avenues outside to Weigh Uncertainty of the U.S. Department of Energy’s National Renewable Energy Laboratory. their immediate field. This cross-pollination often results in surprising insights and lasting collaborations, as in the partnership of statistician 32 Eric Chi and applied mathematician Tamara Kolda. Directory Editor Publication These are just a few examples of DOE CSGF fellows and alumni Shelly Olsan Coordinator working to attack the issues facing us in the years ahead. 32 Fellows Lisa Frerichs Senior Science Writer Design 36 Alumni Thomas R. O’Donnell julsdesign, inc. Copy Editor Ron Winther 28 P2 DEIXIS 12 DOE CSGF ANNUAL DEIXIS 12 DOE CSGF ANNUAL P3 practicum profiles NOT YOUR USUAL SUMMER INTERNSHIP LAB PRACTICUMS BRING FELLOWS PERSONAL AND PROFESSIONAL BENEFITS The Department of RESEARCH COULD ILLUMINATE Energy Computational PROMISING PHOTOVOLTAICS Science Graduate Fellowship supports the ANUBHAV JAIN nation’s brightest science Massachusetts Institute of Technology and engineering students, Lawrence Berkeley National Laboratory allowing them to concentrate on learning WITH HIS FUTURE WIFE on the other side of the country during his summer and research. The work 2010 practicum at Lawrence Berkeley National Laboratory (LBNL), Anubhav Jain had enough spare time to pick up a hobby. of more than 250 DOE The Department of Energy Computational Science Graduate Fellowship (DOE CSGF) CSGF alumni has helped recipient bought a few books and dove into photography, testing his abilities with inexpensive digital cameras. The results are on his website, anubhavjain.net. the United States remain “I like composition a lot – how you can frame your shot so that things are at places your eye competitive in a will be drawn to and how you can lead the viewer to certain things,” says Jain, who earned his doctoral degree from the Massachusetts Institute of Technology (MIT) in August 2011. global economy. WComposition of a different type dominates Jain’s working hours. He uses high-performance computers to calculate the properties of inorganic compounds of both untested and previously ~~~~~ known compositions. The assessments portray a material’s stability, energy-storing capacity and other qualities. Like a good photo, the calculations draw scientists’ eyes to the most promising materials for synthesis and testing. The goal: Get new energy-saving and energy-producing materials to market faster. Jain helped MIT Materials Science and Engineering Professor Gerbrand Ceder develop the Left to right: IN THE CLASSIC CARICATURE of a summer internship, college students Materials Genome Project, a computational encyclopedia of properties for inorganic materials. Brian Lockwood, Hayes slave away at “gofer” duties and other tedious tasks. They combined powerful parallel-processing computers and density functional theory (DFT) Stripling IV, Anubhav Jain Not so for Department of Energy Computational Science Graduate Fellowship recipients’ algorithms to simultaneously portray the characteristics of tens of thousands of materials. DFT, and Eric Chi summer practicums. Fellows are dispatched to national laboratories and tasked with hard a quantum mechanical modeling method, calculates the arrangement and interactions of problems – research subjects outside the bounds of the projects they carry out at their home electrons in atoms and molecules, breaking materials into geometrically arranged repeating universities. They work with leaders in subject matters of national importance and often cells to more easily capture the material’s bulk properties. The problem, however, becomes more employ some of the world’s most powerful computers. The experience exposes fellows to difficult as the number of electrons in each cell increases. the unique blend of resources and collaboration found at national laboratories. The Materials Genome has been used to predict material structures and screen for The summer subject may be tangential to their doctoral project – like the materials compounds suitable for purposes like absorbing mercury from coal gasification. With Ceder’s research Anubhav Jain pursued or the uncertainty quantification projects Brian Lockwood group, Jain helped use its methods to computationally combine lithium with other elements in and Hayes Stripling IV tackled. Or the summer may be a branch out into an interesting area search of compounds for lighter, longer-lasting batteries. As a Luis W. Alvarez Fellow in outside their usual realm, as with Eric Chi’s foray into tensor factorization. Either way, fellows Computational Science at LBNL, Jain now helps move the Materials Genome into its next return to campus with new perspectives and tools, both professional and personal. iteration: the Materials Project. P4 DEIXIS 12 DOE CSGF ANNUAL DEIXIS 12 DOE CSGF ANNUAL P5 practicum profiles Jain’s job was to find the simplest approximate approach that would make reasonable predictions about band gap and absorption spectrum. ~~~~~ SWITCHING TO array of atoms comprising it. Most photons was to calculate those quantities for would be to scale up to rapidly assess in the fundamental quantity but then when SOLAR MATERIALS in sunlight are in a tight range at relatively untested compounds, Jain says. “If hundreds of compounds. you went up to the practical quantity they As with his MIT research, Jain’s low photon energies – the visible spectrum. we could do that, we could evaluate Jain and Neaton compared two DFT were OK,” Jain says. summer 2010 project goal was to devise An ideal solar PV material has a band gap those materials’ potential for use as methods that calculate how a material’s In the final analysis, some of the errors high-throughput methods for computing small enough to absorb those photons, but next-generation solar PV materials.” energy changes as the electron charge apparently cancelled: When Jain ranked 11 the properties of thousands of new materials. not so small that the electrons carry too density changes. The first, the generalized of the materials for solar cell suitability based This time he focused on identifying inorganic little energy to do meaningful work. “What KEEPING IT SIMPLE gradient approximation (GGA), is a standard on band gap and absorption spectrum, the photovoltaic (PV) solids for solar power we