1. Computational design of new materials: magnetic nanostructures/nanocomposites
Experiment in '01: Si12W, Si12Rh , etc
Unknown physical and chemical properties
DARPA project enabled to compute and predict
electronic structure/stability of isolated systems
5 year challenge and goal: design complete
materials (eg, assemblies, composite solids)
cheaper and faster than experiment

2. Computational design of complex solid materials: ferroelectrics and spintronics
CaCu3Ti4O12
1/8 of the cell
Puzzle: huge
dielectric constant
5% La-doped CaB6
magnetic up to 900K
No d or f electrons!
Itinerant magnet ?
Impurities ?
Excitonic phase ?
DARPA project enabled to understand the basic properties:
electronic structure of undoped systems, band gaps, etc,
but lack of deeper understanding hampers applications
5 year goal and challenge: predict key quantities such as magnetic
and dielectric properties rapidly and guide experiments

3. Computational many-body methods
- new paradigm: many-body approaches doable and ultimately
more efficient
- produce both fundamental insights and accurate practical results
- robust stochastic algorithms use cheap cycles: heterogeneous
clusters and grid architectures
- complements and surpasses traditional one-particle methods
New age of many-body methods in computational materials research