almost as long as Lawrence Livermore has existed, scientists have
been experimenting with materials to learn what happens to them
under high pressure. In the brief instant of a high-explosive detonation,
for example, shock waves produce pressure up to 500,000 times that
of Earths atmosphere, detonation waves travel as fast as 10
kilometers per second, and temperatures soar to 5,500 kelvins.
Early high-pressure experiments
were designed to investigate the properties of weapon materials
under these mind-boggling conditions and thus support the development
of new weapons. Today, experiments seek out the fundamental properties
of such deceptively simple materials as water and hydrogen. This
very basic information is being applied to work in high explosives,
planetary science, and materials science.
Experiments with a gas gun
that shocks a sample or with a diamond anvil cell that applies static
pressure demonstrate the changes brought about by pressurethe
after conditions that scientists can compare to the
before. Now, for the first time, using computer simulations,
researchers can get an accurate look at what happens to individual
atoms and molecules during those experiments.
Simulations based on quantum
molecular dynamics make it possible to view experimental activity
as it happens. Quantum molecular dynamics is quite different from
classical molecular dynamics, which is primarily concerned with
the classical motion of atoms interacting with a given potential.
The interesting chemistry and physics of many molecules take place
at the atomic and subatomic level. But Newtons laws of classical
mechanics no longer apply here. Physicists developed quantum mechanics
early in the 20th century to appropriately describe the physics
and chemistry of matter at the microscopic level. Quantum molecular
dynamics focuses on all the interactions between atoms and electrons
and does not involve fitting interactions to experimental data.
First-principles, or ab initio,
molecular dynamics models use only the laws of quantum mechanics,
the fundamental physics equations that describe electrons. (See
the box below.) These models in combination with Livermores
powerful computers allow scientists to create accurate, reliable
simulations of complex physical phenomena.
Physicist Giulia Galli leads
the Quantum Simulations Group at Livermore. In the four years since
this group was established, it has explored entirely new territory.
Early work included simulations of the mixing of water and hydrogen
fluoride, DNA, and the elasticity of silicon carbide, a semiconductor
material. (See S&TR, July/August
1999, Quantum Molecular
Virtual Laboratory.) Their more recent simulations of shocked
liquid hydrogen were the largest ab initio simulations to date on
Livermores terascale computers, which are part of the National
Nuclear Security Administrations Advanced Simulation and Computing
(ASCI) program. Our hydrogen simulations were the first to
look at an experiment in action, says Galli. We could
actually see how a real experiment had gotten from before
Quantum simulations are an
excellent tool for predicting the properties of materials that cannot
be measured directly. They provide accurate information about the
properties of materials subjected to extreme conditions (for example,
high temperature or high pressure) that are difficult to achieve
experimentally. Simulations also help experimental physicists to
interpret their results. Simulation results neatly complement
experimental results and may also guide the choice of new experiments,
Quantum Molecular Dynamics
In the classical molecular dynamics approach, a model
of interactions between atoms is supplied as input before
a simulation can be carried out. Such models are based
on a priori knowledge of the physical system being studied.
Those models work if you know the chemical bonds
already, says physicist Francois Gygi.
In contrast, first-principles,
or ab initio, molecular dynamics does not require any
a priori knowledge of interatomic interactions. These
simulations use only the laws of quantum mechanics, the
fundamental physics equations that describe electrons.
The existence of chemical bonds is the result of electron
interactions and the laws of quantum mechanics. Quantum
simulations can describe the forming and breaking of chemical
bonds, which cannot be done using classical molecular
dynamics. Thus, classical molecular dynamics cannot explain
complex states of matter such as hot, compressed fluids
in which molecules come apart and regroup. Quantum molecular
dynamics, however, is an ideal method for showing what
happens to fluids under pressure.
physics equations that must be solved in quantum simulations
are extraordinarily complex. Until powerful computers
such as Livermores ASCI White came along, ab initio
quantum molecular dynamics simulations could handle only
a few atoms. Even now, a model of a few hundred atoms
over less than a millionth of a second takes days of computing
time to complete on Livermores huge computers.
Modeling the behavior
of molecules at the quantum level requires not only unprecedented
computational power and speed but also specially designed
simulation codes. One such code is JEEP, which Gygi began
developing when he was at the Swiss Federal Institute
JEEP is based on density functional theory, which describes
the electronic density of a molecular or condensed system.
Walter Kohn of the University of California at Santa Barbara
won the Nobel Prize for Chemistry in 1998 for his development
of density functional theory. In its original form, this
theory was confined to ground-state properties of molecules.
Since then, it has been expanded and made applicable to
the study of atomic motion and complex dynamic effects
of matter. Kohns work on density functional theory
has revolutionized the way scientists approach the electronic
structure of atoms, molecules, and solid materials in
physics, chemistry, and materials science.
Since coming to
Livermore, Gygi has adapted and optimized JEEP for use
on the massively parallel computers of ASCI. Now, with
ASCI computers, he can examine materials systems with
hundreds of atoms and thousands of electrons extremely
Monte Carlo codes
are more accurate but have been extremely demanding of
computing time. Every increase in the number of particles
(N) being modeled requires N3 more computing time. Twice
as many electrons requires 8 times more computing time,
3 times as many electrons requires 27 times more computing
time, 4 times as many electrons requires 128 times more
computing time, and so on. Modeling more than a few atoms
requires prohibitively long periods of computing time.
Recently, however, physicists Andrew Williamson, Jeff
Grossman, and Randy Hood developed a technique that allows
for linear scaling of computing time for quantum Monte
Carlo calculations. In other words, doubling the number
of electrons only increases computing time by a factor
of two instead of a factor of eight. This important breakthrough
is based on techniques also used in some quantum molecular
Make It Work
computer code used to simulate dynamic processes is JEEP, which
physicist Francois Gygi began developing about eight years ago when
he was at the Swiss Federal Institute of Technology. Some physical
properties of matter, such as optical properties, can be obtained
more accurately using static calculations performed with quantum
Monte Carlo codes, which are the specialty of physicists Andrew
Williamson, Jeff Grossman, and Randy Hood.
JEEP and quantum Monte Carlo
codes operate differently. Both have to make approximations in their
equations, but quantum Monte Carlo codes make very few. JEEP operates
faster and excels at deriving the location of atoms and molecules.
The more accurate quantum Monte Carlo simulations cannot give dynamic
properties but are a better tool for determining the optical properties
of molecules. Quantum Monte Carlo calculations are also useful for
testing the validity of approximations made in the JEEP codes
theory and for improving the accuracy of this theory.
on (left) Livermores Nova laser and (right) Sandia National
Laboratories Z accelerator shocked liquid deuterium, an
isotope of hydrogen. In both experiments, a short, intense shock
caused the hydrogen to form a hot plasma and, very briefly,
become a conducting metal. The experiments found different compressibilities,
which could affect the equation of state for hydrogen and its
isotopes. Quantum simulations sought to point out physical reasons
for the differences.
Simulations Resolve Differences
simulations by Galli and Gygi may point out the differences found
during two sets of high-pressure experiments on deuterium, an isotope
of hydrogen with one proton and one neutron. One set of experiments
was performed on Lawrence Livermores Nova laser. The other
set was performed on Sandia National Laboratories Z accelerator,
the worlds most energetic pulsed-power machine, in Albuquerque,
The Livermore experiments
in 1997 and 1998 and the Sandia experiment in 2001 subjected a sample
of liquid deuterium to a short, intense shock that caused the hydrogen
to form a hot plasma and, very briefly, become a conducting metal.
In the Nova experiments, a laser beam produced a steady shock wave
aimed at the target cell holding the sample. The wave was smoothed
to ensure a spatially planar and uniform shock front, critical for
obtaining accurate measurements.
The experiment at Sandia
used an entirely different technique for producing a shock wave.
Pulsed-power machines have large banks of capacitors used to accumulate
electrical charges over many hours. All of that stored energy is
discharged in one enormous pulse that lasts for a fraction of a
microsecond. The pulse creates a powerful electromagnetic field
that slams a flyer plate into the deuterium sample capsule. Sandias
magnetically driven plate is faster although smaller than the flyers
used by Livermores two-stage gas guns for shock experiments.
It thus results in higher shock pressures. The Z accelerator also
sustains a shock for a longer time than the Nova laser.
The two sets of experiments
on the Nova laser showed that the deuterium samples were compressed
to a density much higher than anyone had expected. These data differed
from those used to predict the then-current model of the equation
of state (EOS) for hydrogen and its isotopes. An EOS is a mathematical
representation of a materials physical state as defined by
its pressure, density, and either temperature or energy. It is a
necessary constituent of all calculations involving material properties.
Predictions concerning the formation and evolution of large planets,
such as Jupiter, strongly depend on the EOS of hydrogen at pressures
reached in the Nova experiments.
The Z flyer data reached
pressures up to 70 gigapascals, which overlapped part of the pressure
regime of the Nova laser experiments. The Nova experiments determined
the EOS by using an x-ray probe and x-ray microscope to look into
the deuterium as it was being shocked. The Sandia experiments simultaneously
shocked a deuterium sample and a foil of aluminum. Researchers then
found the EOS by comparing deuteriums behavior with that of
aluminum. Although the Sandia EOS data required the comparison with
aluminum, the Z flyer produced a shock in the deuterium that held
a constant pressure for much longer than did the experiments with
the Nova laser.
At a pressure of 40 gigapascals,
the Nova and Z data agree, showing that the hydrogen EOS is about
20 percent more compressible than it was earlier thought to be.
In other words, at this pressure, hydrogen will squeeze into a smaller
volume with a higher density than previous models had predicted.
At a pressure of 70 gigapascals, the Nova data show an even larger
compressibility compared with equilibrium theoryalmost 50
percent higherwhile the Z flyer data are about 7 percent higher
than theory predicted. This is a considerable and important
discrepancy, says Livermore physicist Robert Cauble, who oversaw
the experiments on both the Nova laser and the Z accelerator.
Galli and Gygi performed
two sets of simulations as they sought an explanation for the experimental
results. The first simulations were of hydrogen under fixed pressure
and temperature. The pressure values ranged from 20 to 120 gigapascals
while temperatures ranged from 5,000 to 12,000 kelvins. Galli and
Gygi then simulated the behavior of liquid deuterium during a shock
experiment. Although the simulations of static conditions gave results
that agreed with Sandias data, the simulation of a shock in
deuterium gave results that agreed with the Livermore Nova shocks.
Gygi notes that the conditions
of the Nova and Z accelerator experiments differed. For one thing,
the time scales of the pulse were different: 2 to 4 nanoseconds
in Nova and about 30 nanoseconds in the Z machine. Another
variable may be that a laser beam is very different from a magnetic
pulse, says Gygi.
Although the simulations
did not supply a full explanation for the difference between the
two sets of experimental results, Galli and Gygis calculations
did help to point out possible important differences. In the
past, says Gygi, experimentalists with different results
just pointed fingers at each other. Now, we hope that simulations
will help to explain the physical reasons causing disagreement between
different experiments. Also, big experiments are often expensive
to repeat. The Nova laser is gone completely, so reproducing part
of the Nova results with simulations can be very useful.
simulations of shocked hydrogen reveal the atomic-scale structure
of the shock front. (top) Thirteen hundred and twenty deuterium
atoms are arranged in a periodically repeating molecular dynamic
cell that contains an impactor, a wall, and a liquid sample.
Four computer experiments used different impactor velocities
in an effort to mimic experimental results. (bottom) The shock
front and the compression of the deuterium atoms are shown
from one computer experiment.
the QuickTime movie of this simulation.
Recent experiments also explored
one of the most common liquidswater. You would think
that everybody knows everything about water, says Galli, but
that is far from the truth. And water is in practically everything
in our world. Water is in many materials studied at Livermore:
Biological systems are largely water, high explosives contain water,
and water vapor may accumulate inside an aging nuclear weapon.
Physicist Eric Schwegler,
Galli, and Gygi were interested in what happens to water under pressure,
information important to Livermores U.S. nuclear weapons stockpile
stewardship mission. In particular, they were interested in learning
how the water molecule comes apart under high-pressure conditions.
First, they developed a model
of liquid water at ambient conditions, which compared favorably
with recent x-ray data gathered at the University of California
at Berkeley and with neutron diffraction data gathered in England.
Then they modeled water at moderate pressure and found structural
data that agreed with recent diamond anvil cell experiments performed
at Commissariat à lÉnergie Atomique (CEA) in
of the dissociation of a water molecule at high pressure.
(left) As the water molecules dissociate, (middle) a proton
is transferred to a neighboring water molecule so that (right)
a hydroxide (OH) and a hydronium ion (H3O+) are formed.
the QuickTime movie of this simulation.
Scientists already knew that
under ambient conditions, water molecules rarely dissociate (come
apart)just once every 11 hours. When dissociation does occur,
two water (H2O) molecules become hydroxide (OH) and hydronium
(H3O+), with one proton hopping to the other H2O molecule. How increased
pressure affects dissociation has long been debated.
Experiments on water at extreme
temperatures and pressures have been few. One pioneering 1985 experiment
at Livermore used a two-stage gas gun to shock water with pressures
up to 26 gigapascals and temperatures to 1,700 kelvins. This experiment
did not find any evidence of H3O+ under pressure. These data led
to the suggestion that the dissociation mechanism at high pressures
might be different from the one at ambient conditions, that perhaps
a single H2O molecule dissociates to H+ and OH.
In quantum simulations of
static pressure conditions ranging up to 30 gigapascals, Schweglers
team found that the dissociation process begins in earnest at 14
gigapascals. By 30 gigapascals, dissociation is occurring once every
billionth of a second. The team was surprised to discover the same
dissociation process that occurs at ambient conditions in which
a proton jumps across to another water molecule. The simulations
also indicated why the 1985 experiment did not reveal this process.
At very high pressures, the lifetime of a H3O+ molecule is on average
only 9.8 trillionths of a second, too short to be observed in the
1985 experiment with detection technologies available then.
of the flexibility in DNA comes from rotations around the bonds
found in the backbone, which consists of deoxyriboses linked
together by phosphodiester bridges. Shown here is a simple model
of the phosphodiester linkage found in the backbone of DNA.
The molecule can adopt a variety of conformations by rotations
around the phosphorusoxygen bonds.
Schwegler, Galli, and Gygi
are also working with researchers in Livermores Biology and
Biotechnology Research Program (BBRP) Directorate to simulate the
dynamic behavior of DNA and other biomolecules. The goal is to combine
Livermores expertise in biology, simulation methods, and high-performance
computing to nurture a new Laboratory core competency in computational
biology. (See S&TR, April
New Kind of Biological Research.)
The simulations of water
at ambient conditions were a necessary jumping-off point since all
biomolecules contain a high percentage of water. Such liquid-phase
simulations are far more complicated than those of isolated molecules
in the gas phase because of the increased number of atoms that must
Getting water right
made our future work much easier, says Schwegler. And
there are lots of experimental data to compare.
Subsequently, the team developed
first-principles simulations of the dissolution of sodium and magnesium
ions in water. In each case, their simulations agreed with numerous
experimental investigations by others, but they also found several
interesting features that had not been seen before.
That work was preparation
for quantum simulations of the DNA sugarphosphate backbone
connecting the millions of base pairs that make up our genetic code.
The flexibility of DNA in solution is central to the formation of
DNAprotein complexes, which in turn mediate the replication,
transcription, and packaging of DNA. Part of this flexibility comes
from rotations around the bonds found in the backbone.
To learn more about how
these rotations work, the team modeled the smallest part of the
DNA backbone, the dimethyl phosphate anion (DMP). They observed
changes in the shape of DMP when it was exposed to a sodium
cation, changes that had not been seen in any previous classical
molecular dynamics simulation of DMP in water. In future simulations,
they plan to examine the influence of magnesium and other cations
on the shape and flexibility of DNA.
Schweglers team has
also been collaborating on studies of cancer-fighting drugs known
as phosphoramides being done by Mike Colvin and his associates in
BBRP. These nitrogen-mustard-based drugs have been used to treat
cancer for 50 years, so there is plenty of experimental data to
compare with simulations. By examining how the phosphoramide molecules
are activated, this team hopes to find ways to improve the drug
and to make it more effective. (See S&TR, April
the Attack on Cancer.)
Mustard drugs are believed
to work by forming cross-links between the two strands of a cancer
cells DNA. Because the cell cannot easily eliminate the cross-links,
the cell cannot replicate itself and dies. Before the drug can attach
itself to the cancer cells DNA, it has to lose chlorine ions.
With his quantum simulations, Schwegler is learning more about the
activation process, examining how the drug loses the chlorine ions
and how much energy is required.
cyclization of phosphoramide mustard in solution. (left) As
the new carbonnitrogen bond is formed, a chloride ion
(circled) leaves the mustard and (right) is solvated by the
surrounding water molecules.
theQuickTime movie of this simulation.
Chemistry Is Key
Livermore researchers used
both density functional theory (on which the JEEP code is based)
and quantum Monte Carlo codes to perform first-principles calculations
of silicon nanoclusters, or quantum dots, which are tiny silicon
molecules just a few nanometers in size, about 100,000 times smaller
than the width of a human hair. These nanoclusters produce different
colors of light depending on their diameter and are being considered
as replacements for the fluorescent markers that researchers now
use to tag proteins during experiments. With the markers, scientists
can locate specific proteins and watch them as they go about their
Existing fluorescent dyes
work well as markers. But they are short-lived. Their fluorescence
rapidly fades until they are no longer detectable. They also have
to be excited by a specific wavelength of laser light that matches
their absorption. If researchers are studying more than one protein
at a time and use multiple fluorescent markers, they must also use
as many lasers as there are different markers.
Silicon quantum dots have
several advantages as biomarkers. They do not bleach out, and multiple
markers can be excited by a single laser. Given their small
size, they would be a gnat on the side of a protein, says
Williamson, and the protein should continue to act and react
The synthesis of silicon
dots is still in its infancy. Livermore has several experimental
efforts under way to synthesize them. A long-term goal is to use
silicon nanoparticles in biosensors to detect biological and chemical
During the manufacture of
the quantum dots, contamination is a concern. Oxygen, especially,
can be a killer for silicon, notes Williamson. Recent Livermore
simulations examined the effect of oxygen on silicon particles.
A single oxygen atom, as well as many other contaminants, can make
a big difference on a quantum dot because of the dots large
ratio of surface area to volume. Surface chemistry plays a big role
in the study of these tiny particles.
The effects of surface chemistry
are illustrated in the figure above. The left portion of the figure
shows a nanometer-size silicon quantum dot made up of 71 atoms.
The white atoms on the surface are hydrogen atoms bonded to the
dot in such a way as to passivate the surface. This
means they attach themselves to the highly reactive surface silicon
atoms (gray). The purple cloud shows the region where the electrons
that will absorb light are most likely to be located in this silicon
quantum dot. For a silicon dot completely passivated by hydrogen,
the electrons are located in the center of the dot. The right portion
of the figure above shows how the situation changes when two of
the hydrogen atoms are replaced by a more reactive oxygen atom.
The electron charge cloud is drawn toward the oxygen atom, and this
change in the electron density dramatically changes the optical
properties of the silicon dot.
The team is currently broadening
the scope of its nanostructure investigations to include other semiconductor
materials such as germanium and cadmiumselenide.
In a 71-atom silicon quantum dot, the white atoms are hydrogen
atoms bonded to the surface that are passivating
the dot and making it less reactive. A silicon dot that is completely
passivated by hydrogen will have all its electrons in the center.
(right) When two of the hydrogen atoms are replaced by a more
reactive oxygen atom, the electron charge cloud is drawn toward
the oxygen atom. This dramatically changes the optical properties
(wavelength) of the silicon quantum dot.
Chemistry Is Key
One goal of Gallis
group for the next few years is to apply quantum simulations to
a wider and broader set of problems and to use quantum simulations
on a par with laboratory experiments as a tool for research in science
and engineering. Quantum simulations are a fully predictive approach
that will provide a new window through which scientists can observe
the world at the atomistic level in exquisite detail, avoiding uncontrolled
approximations. Gallis group will focus on fluids under extreme
conditionsfor example, water under shocked conditionsand
on building knowledge and expertise in the field of nanoscience,
in particular, modeling artificial and biological nanostructures
for labeling and sensing applications.
Because of the success of
their quantum simulations, Galli and Gygi are working with IBM on
the design of the next-generation ASCI computers. When these monster
computers arrive, extremely complex simulations may be able to answer
questions that cannot now be answered.
Key Words: hydrogen,
JEEP, nanostructures, quantum dots, quantum molecular dynamics,
quantum Monte Carlo calculations, quantum simulations, water.
information, contact Giulia Galli (925) 423-4223 (email@example.com).