## Research Activity: Theoretical Condensed Matter Physics

Division: Materials Sciences and Engineering

Primary Contact(s): Dale Koelling (<Dale.Koelling@science.doe.gov> ,
301-903-2187)

Team Leader: William Oosterhuis

Division Director: Patricia Dehmer, Acting

**Portfolio Description:**

The Theoretical Condensed Matter Physics activity provides theoretical
support for all parts of the Materials Science and Engineering Division.
Research areas include quantum dots, nanotubes and their properties,
tribology at the atomic level, superconductivity, magnetism, and optics.
A significant effort within the portfolio is the development of advanced
computer algorithms and fast codes to treat many-particle systems. An
important facilitating component is the Computational Materials Science
Network (CMSN), which enables groups of scientists from DOE
laboratories, universities, and (to a lesser extent) industry to address
materials problems requiring larger-scale collaboration across
disciplinary and organizational boundaries.

**Unique Aspects:**

New areas of materials science are being identified and studied. New
technology is enabling a much closer examination of the existing ones.
This healthy progress dictates that new theories be developed and that
established ones be reexamined and possibly extended. A very important
contribution of the theorist is enforcing a rational, consistent
understanding of experimental observations so that we can go forward.
Often, this involves working out the implications of a theory for a
specific material or situation. In materials, this can be an extremely
difficult task because of the very many atoms involved. Many conceptual
tools such as quasiparticles, entities defined to examine phenomena at
different length scales, or summary statistical approaches have been
developed. Further development of such conceptual tools continues to be
a very important aspect of this theoretical program. However, for many
phenomena now being studied, large scale computation must be utilized to
perform the complex calculations involved or to perform the simulations
of many interacting components. The rapid advance in computational
capabilities now enables research at such a level of sophistication that
computational science has become a "third way of doing science", but at
a price. The complexity of such research very often requires larger
groups of collaborating researchers from a diversity of disciplines. One
response has been formation of the Computational Materials Science
Network to bring together multi-disciplinary groups of scientists from
DOE laboratories, universities, and industry to collaborate on
computational materials science projects. At present, CMSN consists of
five sub-projects: Excited States and Response Functions (testing the
accuracy of current levels of fundamental theory); Microstructural
Effects on the Mechanics of Materials (computational study of the
fundamental basics of metallurgy); Microstructural Evolution Based on
Fundamental Interfacial Properties (a fundamental factor to understand
the processing of real materials); Polymers at Interfaces (a study of
failure modes since this region is the weakest link in composite
materials); Magnetic Materials Bridging Basic and Applied Science (an
attempt to interconnect different scales of magnetic behavior from
quantum mechanical electronic behavior all the way to continuum
micro-mechanical properties).

**Relationship to Others:**

This activity interacts with all the other research activities within
the Division of Materials Science and Engineering driven by mutual
interest Also, because the computational resources at the National
Energy Research Scientific Computing facility utilized by the division
are administered here, there is an enhanced awareness of opportunity.
Within DOE, frequent interaction occurs with the Mathematics,
Information and Computer Sciences division. Information on university
grants is shared with NSF, peer reviews are sometimes shared, and on
occasion there is joint funding of grants. On the international level
participation in organizing and steering committees is frequent, as are
exchanges of experts between foreign and domestic institutions.

**Significant Accomplishments:**

Consistent with the emphasis on nanoscience enabled by developments in
technology and computational techniques, notable achievements in this
area have been made within the Condensed Matter Theory Activity.

Research into low dimensional materials has revealed exciting new
information and has pointed to new possibilities in creating new
tailored materials and devices. Highlights include:

1.  The discovery that magnetization around defects in quasi-one
    dimensional materials greatly influences the phase in which they
    reside points to the development of sensors highly sensitive to
    external stimuli.

2.  The discovery that loading electrons into quantum dots results in
    the formation, within the dot, of complexes of holes and electrons.
    These decay in a theoretically predictable manner, pointing to the
    possibility of fabricating quantum dots with tailored light emitting
    properties.

3.  The discovery that electrons confined in a thin film segregate into
    discreet energy levels, in analogy to the discreet energy levels in
    atoms, points to the possibility of constructing ultra-stable
    materials by controlling the thickness of the film.

4.  4\. Calculations show that the conductance across two crossed carbon
    nanotubes is very sensitive to the force applied at that junction.
    While the inter-tube conductance is dramatically increased, the
    intra-tube conductance is diminished. When this arrangement is
    realized experimentally, crossed nanotubes can be expected to be
    excellent sensors for applied forces within nanoscaled devices.

Significant progress has also been made in other areas as illustrated by
the following examples.

Dynamic mean-field theory, which is exact for infinite dimensions, has
been successfully coupled with three dimensional band theory. The
resulting hybrid theory predicts the anomalous properties of highly
correlated rare-earth and actinide materials.

When metals solidify they form highly branched patterns called
dendrites. These solidification patterns control many aspects of
processing and microstructure and hence our ability to use materials. A
Collaborative Research Team of the Computational Materials Science
Network has devised an entirely new method for extracting the anisotropy
of energy and mobility responsible for dendrite formation from
supercomputer simulations of the atomic processes occurring during
solidification.

*Ab initio* calculations have been performed for the hysteresis loop and
domain wall dynamics of magnets. Long thought to be beyond the scope of
*ab initio* calculations because of the large number of atoms involved,
it became possible to perform detailed studies of some less demanding
materials such as FePt and CoPt, which are technologically important.

When atomic motions within a material are simulated by molecular
dynamics, much of the computational effort is expended to describe the
rapid vibrations of the atoms about their equilibrium positions. This
expenditure precludes running the simulation for long enough times to
see a significant number of jumps of atoms between equilibrium positions
\-\-- the interesting phenomena in this case. To deal with this problem,
a modified or hyper dynamics was developed that damps the rapid
oscillations while accurately representing the site to site jumps. This
greatly facilitates our ability to calculate atomic diffusion in
materials.

**Mission Relevance:**

The program's ultimate purpose is to understand the properties of
existing materials and to reveal new ones that are more efficient in
producing, storing, and using energy. To this end, the programs in this
portfolio have the common goal of achieving a basic understanding of
matter at all scales ranging all the way from the atomic to the bulk.
The experimental and theoretical programs work closely together, but
there are also more independent modes of research. The theorists will
try to establish a theoretical basis for experimentally observed
results, which almost always suggests further experiments, and thus
leads to new results. But new science is also produced by simulating
processes on computers. "Computer experiments" can be performed which
are difficult or impossible perform in the laboratory. They are also
much easier to dissect and vary to determine the effective mechanisms.
For example, the behavior of the surface layers of materials sliding on
each other and a new understanding of the role of lubricants has been
obtained in this way. Other examples include investigations into the
behavior of electrons flowing in nano wires and nanotubes and in the
properties of matter at extreme conditions of temperature and pressure.

**Scientific Challenges:**

The close relationship between the experimental and theoretical programs
dictates that many challenges are common to both. Examples are exploring
the behavior of complex systems, investigating nano-scale systems, and
understanding superconductivity. New ways of conceptually visualizing
and characterizing phenomena will broaden our horizons. Stripes
occurring in cuprate superconductors and two dimensional electron gasses
are an excellent example. Bridging length scales is a major thrust. The
tactic of dividing up the effects in materials according to the length
scale at which they occur has greatly facilitated our understanding. But
for the theorists, this creates the problem of how to pass needed
information between the different constructs used at the different
length scales. Only in that way can one calculate parameters rather than
make phenomenological fits. Such is the basis for improved understanding
and greater precision of our modeling. It is a continuing major goal on
which limited progress has been made. Bridging time scales is similarly
important but far less progress has been made. Basic theory improvements
are also needed. For example, density functional theory is our most
computationally tractable many body theory but it defines many
functionals both for the ground state or ensemble energy and separately
for the properties that must be determined. Whereas knowledge of the
exchange-correlation functional for the ground state energy is
reasonably advanced, knowledge of all other functionals is still quite
rudimentary. Improvements are also needed in our computational tools.
Materials theory is a very heavy consumer of computer resources even if
not so visibly as in other disciplines. (This is because materials
theory deals with many dissimilar problems rather than a few overarching
ones.) The materials community could very productively make use of vast
increases in computational capability. Because the phenomenal growth due
to hardware improvements is actually overshadowed by those due to clever
algorithm design, further improvements in "tool development" will
significantly impact future development in a qualitative way.

**Funding Summary:**

**Dollars in Thousands**

**[FY 2002]{.underline}** **[FY 2003 Request]{.underline}** **[FY 2004
Request]{.underline}**

18,007 18,007 17,982

> **[Performer]{.underline} [Funding Percentage]{.underline}**
>
> DOE Laboratories 75%
>
> Universities 25%

The program provides funding for 48 university grants supporting about
as many students and partially supporting about 50 faculty and senior
staff and programs at 9 national laboratories. There are approximately
70 postdocs fully or partially supported by this CRA. Programs at the
laboratories are multi-investigator efforts on problems that require
extensive participation by experimental and theoretical scientists. This
program supports research at LBNL, AMES, BNL, ANL, LLNL, MRS, LANL,
ORNL, and NREL. Many of the research efforts at national laboratories
involve interfaces with the university and industrial communities and
user facilities. In addition, about \$1.4M is provided to projects of
the Computational Materials Science Network.

**Projected Evolution:**

Materials will be modeled with ever-greater sophistication and realism
and complexity. Needs and opportunities will drive the effort inexorably
in this direction. Science at the nanoscale will continue a major
example, although it is only one of many. With the Chemistry Division, a
cooperative effort will be begun with Mathematics, Information, and
Computer Sciences seeking to enhance our capabilities to model and
simulate at the nanoscale. As a way to bring together teams adequate to
address the more complex problems envisioned, the Computational
Materials Science Network will be enhanced.

February 14, 2003