麻豆淫院

Gold is shiny, diamonds are transparent, and iron is magnetic. Why is that? The answer lies with a material 鈥檚 electronic structure, which determines its electrical, optical, and magnetic properties.

Predicting a material鈥檚 properties by first calculating its electronic structure would cut down experimental time and might lead researchers to uncover new materials with unexpected benefits.

But commonly used simulations are inaccurate, especially for materials like silicon, whose strongly correlated electrons influence each other over a distance and make simple calculations difficult.

Now a team of researchers at Sandia National Laboratories may have a solution that offers huge potential. Sergey Faleev and his colleagues applied theoretical innovations and novel algorithms to make a hard-to-use theoretical approach from 1965 amenable to computation. The team 鈥檚 approach may open the door to discovering new phases of matter, creating new materials, or optimizing performance of compounds and devices such as alloys and solar cells.

Their paper, 鈥淨uasiparticle Self-Consistent GW Theory, 鈥� appeared in the June 9, 2006, issue of 麻豆淫院ical Review Letters. GW refers to Lars Hedin 鈥檚 1965 theory that elegantly predicts electronic energy for ground and excited states of materials. 鈥淕 鈥� stands for the Greens function 鈥� used to derive potential and kinetic energy 鈥� and 鈥淲 鈥� is the screened Coulomb interaction, which represents electrostatic force acting on the electrons. 鈥淨uasiparticles 鈥� are a concept used to describe particle-like behavior in a complex system of interacting particles. Self-consistent means the particle 鈥檚 motion and effective field, which determine each other, are iteratively solved, coming closer and closer to a solution until the result stops changing.

鈥淥ur code has no approximation except GW itself, 鈥� said Faleev. 鈥淚t 鈥檚 considered to be the most accurate of all GW implementations to date. 鈥�

鈥淚t works well for everything in the periodic table, 鈥� adds coauthor Mark van Schilfgaarde, a former Sandian now at Arizona State University. The paper reports results for diverse materials whose properties cannot be consistently predicted by any other theory. The 32 examples include alkali metals, semiconductors, wide band-gap insulators, transition metals, transition metal oxides, magnetic insulators, and rare earth compounds.

Describing force

鈥淓verything in solids is held together by electrostatic forces, 鈥� says van Schilfgaarde. 鈥淵ou can think of this as a huge dance with an astronomically large number of particles, 1023, that is essentially impossible to solve. The raw interactions among the particles are remarkably complex.

鈥淗edin replaced the raw interactions with 鈥榙ressing 鈥� the particle with a screened interaction, 鈥� van Schilfgaarde continues, 鈥渟o the effective charge is much smaller. It becomes much more tractable but the equations become more complicated 鈥� you have an infinite number of an infinite number of terms. The hope is that the higher-order terms die out quickly. 鈥�

The researchers 鈥� use of GW makes the expansion much more rapidly convergent.

鈥淲e 鈥檙e pretty confident we got the approach right, 鈥� he says. He now would like another group to independently verify this way of framing the task.

Promise and challenges ahead

The researchers use a molecular dynamics code, VASP (Vienna Ab-initio Simulation Package) to model, for example, equations of state in high-energy-density matter. These equations of state depend on quantities like electrical conductivity. Calculating this requires detailed knowledge of the electronic structure 鈥� a perfect application for Faleev 鈥檚 work. The researchers hope to describe optical spectra, calculate total energy, and account for more than 10 atoms in a unit cell 鈥� at 100 times the current speed.

Accelerating the code would facilitate modeling in other research areas at Sandia, such as simulating titanium dioxide used in surface science, or aiding research into carbon nanotubes that might be used in electronic or optical devices.

鈥淭o calculate absorption or optical spectra is a huge problem, 鈥� Faleev says with anticipation. 鈥淭o make it faster is a huge problem. To make it more accurate is a huge problem. To incorporate VASP is a huge problem. 鈥�

Van Schilfgaarde agrees. 鈥淚t 鈥檚 quite an accomplishment to do it at all. It takes someone who is very strong in math, and a clever programmer. We spent easily five to six man-years between us to make it work.

鈥淚f we can get the approach right, we can have a theory that 鈥檚 universally accurate for anything we want 鈥� that 鈥檚 really pretty neat, just requiring knowledge of where the atoms are. 鈥�

Van Schilfgaarde believes the theory 鈥檚 advantage would be to offer true insight into material behavior. 鈥淚t 鈥檚 kind of like adding night-vision goggles to soldiers working in the dark, 鈥� he says. 鈥淧robably in 10 years, 鈥� adds Sergey, 鈥渆veryone will use this. 鈥�

Source: Sandia National Laboratories