The BES SciDAC Partnership portfolio focuses on the development of new algorithms and computational approaches which could dramatically accelerate the discovery of new materials and processes as well as provide fundamental understanding and improvement of current materials and processes. Implementing these new algorithms on current and next generation massively parallel computers requires a team approach which includes materials and chemical scientists, applied mathematicians and computer scientists.

The following priority research directions form the basis for BES SciDAC Partnership projects:

• Capturing Solar Energy
• Chemical Reactions
• Magnetism and Superconductivity
• Materials Under Extreme Environments
• Separations
• Energy Storage

Current Projects

Advanced Modeling of Ions in Solutions, on Surfaces, and in Biological Environments
This projects aims to advance the state of ab initio molecular dynamics (AIMD) simulation in handling hydrated ions in situations relevant for future research applications dealing with energy and the environment.

Lead Investigator: Roberto Car (rcar@princeton.edu)
Princeton University

Charge Transfer and Charge Transport in Photoactivated Systems: Developing Electron-Correlated Methods for Excited State Structure and Dynamics in the NWChem Software Suite
This project aims to develop and implement a suite of new theoretical methods in the NWChem computational chemistry software suite in order to provide improved capabilities for excited-state dynamics in the gas phase and to add the capability to perform electronically excited-state dynamics in solution.

Lead Investigator: Christopher J. Cramer (cramer@umn.edu)
University of Minnesota

Discontinuous Methods for Accurate, Massively Parallel Quantum Molecular Dynamics: Lithium Ion Interface Dynamics From First Principles
This project aims to develop and implement a new Discontinuous Galerkin electronic structure method and to apply it to address fundamental questions on the formation and evolution of the solid-electrolyte interphase layer in Li-ion cells.

Lead Investigator: John E. Pask (pask1@llnl.gov)
Lawrence Livermore National Laboratory

OSCon -- Optimizing SuperConductor Transport Properties Through Large-Scale Simulation
This project aims to develop and apply novel methods for optimizing superconductors for energy applications using large-scale computational algorithms and tools.

Lead Investigator: Andreas Glatz (glatz@anl.gov)
Argonne National Laboratory

Scalable Computational Tools for Discovery and Design – Excited State Phenomena in Energy Materials
This project aims to develop and implement new methods and theories to predict electronic excited state phenomena in energy related materials, e.g., materials for photovoltaics, photocatalysis, and electrical energy storage by using advanced algorithms and many-body perturbation theory.

Lead Investigator: James R. Chelikowsky (jrc@ices.utexas.edu)
University of Texas at Austin

Simulating The Generation, Evolution and Fate of Electronic Excitations in Molecular and Nanoscale Materials With First Principles Methods
This project aims to make meaningful progress by coupling new and improved models for bound and metastable excited states from physical scientists with advances on underlying methodological challenges in applied mathematics, and practical realization via high performance computing.

Lead Investigator: Martin Head-Gordon (mhg@chemistry.berkeley.edu)
Lawrence Berkeley National Laboratory

Predictive Computing for Condensed Matter
This project aims to develop a suite of programs that can predict the properties of materials with unique and highly correlated electronic structure.

Lead Investigator: So Hirata (sohirata@illinois.edu)
University of Illinois at Urbana-Champaign