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Summit research creates new insights into correlated electronic systems

An international team of researchers used the summit to model the spin, charge, and pair density waves of copper oxide, a type of copper alloy, to investigate the superconducting properties of materials. The results reveal new insights into the relationships between these dynamics as superconductivity develops. Credit: Jason Smith / ORNL

A study led by researchers at the US Department of Energy’s Oak Ridge National Laboratory is a central question in modern physics that could help develop next-generation energy technologies using the fastest supercomputers in the United States. Approaching the answer to.


“This is primarily to solve problems that are now decades old,” said Thomas Maier, an ORNL physicist who led the study with researchers at the University of Tennessee and the ETH Zurich Institute for Theoretical Physics. “If we can answer the question, what is the mechanism of a particular superconductivity? Correlated electron system Once you understand the reason for that behavior, you can design materials to get the most out of it. “

The findings have appeared in Minutes of the National Academy of Sciences..

In this study, we used Summit, a 200-petaflops IBM AC922 supercomputing system at the Oak Ridge Leadership Computing Facility. Electronic In a solid. In the simulation, the Hubbard model, which is the simplest model of a system that interacts electrons in various dimensions, is applied, and a class of copper alloy called copper oxide is a superconductor that transfers electricity without losing energy. I investigated how it works as a.

Copper oxide can be used in power transmission and power generation, high speed magnetic levitation, or magnetic levitation, train, and medical applications, but typically exhibits full superconducting properties in extreme cold (usually hundreds of degrees below freezing). Explaining this superconductivity, the code could be cracked to obtain superconductivity. room temperature We provide cheap, speedy and sustainable energy.

Developed nearly 60 years ago and named after the British physicist John Hubbard, the Hubbard model places an electronic system within a 2D grid. Each electron has an up or down spin similar to the positive and negative electrodes of a magnet, and two electrons with the same spin cannot occupy the same site. The first term of the model represents kinetic energy. In this term, electrons move or “hop” back and forth between adjacent sites in the grid, and then move diagonally between the next closest adjacent sites. The second term represents the interaction energy and the increase in energy when two electrons with opposite spins try to occupy one site.

Hubbard did not design a model to explain the electron behavior of superconductors such as copper oxide. Researchers have experimented with layers of copper and oxygen to look for room-temperature superconductors, and have adjusted or “doped” the Hubbard model for many years to understand their superconducting properties.

The doped model removes electrons, leaving “holes” that help the remaining electrons form a pair that easily conducts electricity. Under the right conditions, the holes line up to form stripes, scientists believe they compete with superconductivity, and electrons form a wave pattern known as charge and spin density waves.

However, so far, these models have not been able to reliably explain or predict superconductivity in sufficient detail for practical use.

“The approach needed to solve this problem is not accurate, in theory the size of the model is infinite, there are many different phases, and it requires very large and complex calculations.” Maier said. “The energy difference is negligible and can be less than millielectronvolts. All of this can be approximated by a finite size grid, but that approach ignores many aspects and the grid is too small. We can’t draw any solid conclusions. We need a simple model that describes all the physics and consistently produces the same result. “

Maier’s team received a 900,000 node-hour allocation grant at the summit through an innovative and innovative Computational Impact (INCITE) program on DOE’s theory and experimentation.

Examine the model in detail. The results reveal new insights into the relationship between electron spins and charge stripes, including when stripes form as superconductivity develops.

“These were very heavy calculations that could only be done at the summit,” says Maier. “I had a little chance, but it was rewarded because I finally had a machine that could support the computation of a system large enough to see the stripes. This way, when the stripes were in charge of spinning. , Superconducting correlations form a similar wave-like pattern known as pair density waves. This result may set new criteria for understanding this model. “

The simulation does not elaborate on the secrets of raising the temperature for superconductivity. However, the lessons learned point to further research is needed, as researchers focus on how superconductivity occurs.

“Every year, I know more than last time,” Meyer said. “Now we need to solve the model and explore other ways to reproduce the results. We are closer than ever and want to get closer.”


Scientists have finally found superconductivity where they have been looking for decades


For more information:
Peizhi Mai et al, Correlation of intertwined spins, charges, and pairs of a two-dimensional Hubbard model in the thermodynamic limit, Minutes of the National Academy of Sciences (2022). DOI: 10.1073 / pnas.2112806119

Quote: Summit research to the correlated electronic system (February 18, 2022) obtained from https: //phys.org/news/2022-02-summit-insights-electron.html on February 18, 2022. Weaving new insights

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Summit research creates new insights into correlated electronic systems

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