The Office of Basic Energy Sciences in the U.S. Department of Energy’s Office of Science announced today two additional awards for research in Computational Materials Sciences in response to solicitations DE-FOA-0001528 and LAB 16-1528. The awards total $4 million per year for four years starting in FY 2016. The lead institutions for the awards are Oak Ridge National Laboratory and Lawrence Berkeley National Laboratory. The new grants—part of DOE’s Computational Materials Sciences (CMS) program begun in 2015 as part of the U.S. Materials Genome Initiative—reflect the enormous recent growth in computing power and the increasing capability of high-performance computers to model and simulate the behavior of matter at the atomic and molecular scales.
For Computational Materials Sciences awards, integrated, multidisciplinary teams were sought to perform research and develop validated community codes and databases for predictive design of functional materials. Applicants proposed new approaches to enhance the use of large data sets derived from advanced characterization of materials, materials synthesis, processing, properties assessments, and the data generated by large-scale computational efforts that model materials phenomena. Awards were selected from a large number of applications following rigorous peer review of their scientific and technical merit, proposed budget, competency of the team, and management plan.
The projects are expected to develop open-source, robust, validated, user-friendly software (and the associated experimental and computational databases) that captures the essential physics and chemistry of relevant systems and can be used by the broader research community and by industry to accelerate the design of new functional materials. The goal of this research activity is to leap beyond simple extensions of current theory and models of materials towards a paradigm shift in which specialized computational codes and software, coupled with innovative use of experimental and theoretical data, enable the design, discovery, and development of new materials, and in turn, creates new advanced, innovative technologies. Given the importance of materials to virtually all technologies, computational materials sciences is a critical area in which the United States needs to be competitive in the 21st century through global leadership in innovation.
The descriptions of the 2016 and 2015 Computational Materials Sciences Awards follow:
Center for Computational Study of Excited-State Phenomena in Energy Materials
Team: Steven Louie (Director), Jack Deslippe, Jeffrey Neaton, Eran Rabani, Feng Wang, Lin-Wang Wang, Chao Yang, Lawrence Berkeley National Laboratory. Partners: Daniel Neuhauser, University of California, Los Angeles; James Chelikowsky, University of Texas at Austin.
Goals: Methodological development of many-body theory software for single-particle and optical excitations as well as higher-order correlated processes in functional materials, with the objective to deliver state-of-the-art excited states calculations by advancing the GW-Bethe-Salpeter-Equation approach and beyond. The emphasis is on semiconducting, transition metal oxide, halide perovskite, graphene and two-dimensional transition metal dichalcogenide quantum materials. Excited-state phenomena, such as charge transport and optical response, are central to a variety of applications including electronics, photovoltaics, light-emitting diodes, information storage, energy storage, and electro- and photo-chemistry. Validation of materials-specific predictions includes experiments at the Advanced Light Source and the Molecular Foundry. Data management and computing will primarily use current petascale capabilities and future exascale capabilities at NERSC and the Leadership Computing Facilities. Access to the Materials Project and the emerging CAMERA center will be leveraged.
Center for Predictive Simulation of Functional Materials
Team: Paul Kent (Director), Panchapakesan Ganesh, Jaron Krogel, Ho Nyung Lee, Oak Ridge National Laboratory. Partners: Anand Bhattacharya, Anouar Benali, Olle Heinonen, Argonne National Laboratory; Miguel A. Morales Lawrence Livermore National Laboratory; Luke Shulenburger, Sandia National Laboratory; Lubos Mitas, North Carolina State University; Eric Neuscamman, University of California-Berkeley.
Goals: Methodological development of Quantum Monte Carlo software for functional materials, with the objective to deliver accurate and robust determination of electronic eigenstates, perform calculations beyond ground state properties, and improve valence Hamiltonians. The emphasis is on doped correlated oxides for electronic and spin-dependent functionalities, vacancy and strain control of metal-insulator transitions, and heterostructured transition metal oxides. Such quantum materials exhibit novel magnetism, optical properties, metal-insulator transitions, and exotic quantum phases that make them well-suited to energy applications. In many cases, small changes in composition, structure, doping, applied strain, or applied field yield substantially altered physical properties. Validation of materials specific predictions includes experiments at the Advanced Photon Source, Spallation Neutron Source, and the Nanoscale Science Research Centers. Data management and computing will primarily use current petascale and future exascale capabilities at the Argonne and Oak Ridge Leadership Computing Facilities, as well as NERSC.
Midwest Integrated Center for Computational Materials
Team: Giulia Galli (Director), Argonne National Laboratory. Partners: University of Chicago, University of Michigan, Northwestern University, University of Notre Dame, and University of California-Davis.
Goals: Development of interoperable quantum, classical and particle-continuum software, enabling the simulation and prediction of functional materials for energy conversion processes, with an emphasis on interfaces, the transport across them, and the manipulation of matter under conditions far from equilibrium. Validation of materials specific predictions includes experiments at the Advanced Photon Source and the Center for Nanoscale Materials. Data management and computing will primarily use capabilities at the Argonne Leadership Computing Facility.
Center for Computational Design of Functional Strongly Correlated Materials & Theoretical Spectroscopy
Team: Gabriel Kotliar (Director), Brookhaven National Laboratory. Partners: Rutgers University, University of Tennessee, and Ames Laboratory.
Goals: Development of next-generation methods and software to accurately describe electronic correlations in oxides and complex materials and a companion database to predict targeted properties with energy-related application to thermoelectric materials. Validation of materials specific predictions includes experiments at the National Synchrotron Light Source II. The project will use capabilities at the National Energy Research Scientific Computing Center (NERSC), and the Argonne and Oak Ridge Leadership Computing Facilities.
Computational Synthesis of Materials Software Project with Validation on Layered Low Dimensional Functional Materials and Ultra-Fast X-Ray Laser Experiments
Team: Priya Vashishta (Director), University of Southern California. Partners: California Institute of Technology, Lawrence Berkeley National Laboratory, University of Missouri, Rice University, and SLAC National Accelerator Laboratory.
Goals: Development of next-generation methods and software to predict and control materials processes at the level of electrons for synthesis, intercalation and exfoliation of stacked, twodimensional, functional layered materials with energy- related application to electronics and catalysis. Validation of materials specific predictions includes ultrafast free electron laser experiments at the Linac Coherent Light Source. Data management integrates the Materials Project at Lawrence Berkeley National Laboratory and uses computing capabilities at NERSC and the Argonne Leadership Computing Facility.