Rutgers team develops computational model for predicting superconductivity
Researchers studying iron-based superconductors are combining novel electronic structure algorithms with the high-performance computing power of the Department of Energy’s Titan supercomputer at Oak Ridge National Laboratory to predict spin dynamics, or the ways electrons orient and correlate their spins in a material. Because researchers have suggested that spin dynamics create the conditions needed for superconductivity, this approach could expedite the search for new or modified materials that conduct electricity with little or no resistance at higher temperatures, unlike current commercial superconductors, which must be expensively cooled to exhibit superconducting properties.
The 15 boxes in this image show the simulated intensity of spin excitations in 15 iron-based materials, including iron compounds that are high-temperature superconductors (images d–h). The x axis shows the momentum of the spin excitation in selected locations of 3D space, and the y axis shows the energy measured in electron volts (eV). The color code indicates the intensity of spin excitations with a given energy and momentum, which is compared with available experimental results (shown in black bars in images f, g, l, and m). The locations with the greatest number of spin excitations are shown in red with decreasing frequency shown from orange to blue. By visualizing the spin dynamics of multiple iron-based materials—information that can be time-consuming and expensive to collect experimentally—researchers can better predict which materials are likely to be superconducting.
In a Nature Physics paper published in October, Zhiping Yin, Kristjan Haule, and Gabriel Kotliar of Rutgers University compute the dynamic spin structure factors—or the measure of how the spins of electrons align relative to each other at a given distance at different times—of 15 iron-based materials, including several high-temperature superconductors, in unprecedented detail.
“Our computational results are in good agreement with experimental results for experiments that have been performed, and we have several predictions for compounds that have not yet been measured,” Kotliar said. “Once we validate the theory that our computational models are based on with experiments, then we can investigate materials computationally that are not being studied experimentally.”
Computation offers a way for researchers to better understand spin dynamics and other material properties under many conditions, such as temperature change, rather than the singular condition present during a given experiment. Computation also allows researchers to simulate many of these materials at once, and the number of potential materials to explore rapidly increases as scientists introduce modifications to improve performance.
With the computational power at hand on the 27-petaflop Titan system managed by the Oak Ridge Leadership Computing Facility, the team was able to compare and contrast spin dynamics for all 15 materials simulated to identify tell-tale superconducting properties.
“By comparing simulations and experiments, we learned about which type of spin fluctuations actually promote superconductivity and which ones do not,” Kotliar said.
In their model, the team used a technique called Dynamical Mean Field Theory to reduce the vast number of interactions involving electrons in a unit cell (the most detailed slice of material simulated) and averaged these interactions in a mean field environment across the rest of the solid. The team used the Monte Carlo method to statistically select the best solutions for these techniques, achieving a new level of predictive accuracy for spin dynamics in these kinds of materials.
“We find these complex problems, as in superconductors, where you have to solve many degrees of freedom or a large number of variables, require supercomputing rather than computing on smaller clusters,” Haule said. “Our algorithms are designed to work very efficiently on Titan’s massively parallel architecture.”
Using 20 million processor-hours on Titan, the team also discovered through simulation a new superconducting state, or electron pairing, found in the lithium-iron-arsenic compound, LiFeAs, that is consistent with experimental results.
In the future, they plan to simulate spin dynamics in other classes of superconductors and in non-superconducting materials that are exceptionally difficult to study experimentally, such as radioactive materials.
“Using computation as a substitute for experiment is an important step forward for designing new materials,” Kotliar said. “The next time someone comes to us with potential materials for an application and asks, ‘Should I work on this?’ we hope to simulate that material through computation to select the most promising ones.”
The work was supported by the National Science Foundation and made use of the Oak Ridge Leadership Computing Facility, a DOE Office of Science User Facility at ORNL.
UT-Battelle manages ORNL for the Department of Energy's Office of Science. The Office of Science is the single largest supporter of basic research in the physical sciences in the United States, and is working to address some of the most pressing challenges of our time.
For more information, please visit http://science.energy.gov/
Katie Elyce Jones
Katie Jones | newswise
From ancient fossils to future cars
21.10.2016 | University of California - Riverside
Study explains strength gap between graphene, carbon fiber
20.10.2016 | Rice University
Researchers from the Institute for Quantum Computing (IQC) at the University of Waterloo led the development of a new extensible wiring technique capable of controlling superconducting quantum bits, representing a significant step towards to the realization of a scalable quantum computer.
"The quantum socket is a wiring method that uses three-dimensional wires based on spring-loaded pins to address individual qubits," said Jeremy Béjanin, a PhD...
In a paper in Scientific Reports, a research team at Worcester Polytechnic Institute describes a novel light-activated phenomenon that could become the basis for applications as diverse as microscopic robotic grippers and more efficient solar cells.
A research team at Worcester Polytechnic Institute (WPI) has developed a revolutionary, light-activated semiconductor nanocomposite material that can be used...
By forcefully embedding two silicon atoms in a diamond matrix, Sandia researchers have demonstrated for the first time on a single chip all the components needed to create a quantum bridge to link quantum computers together.
"People have already built small quantum computers," says Sandia researcher Ryan Camacho. "Maybe the first useful one won't be a single giant quantum computer...
COMPAMED has become the leading international marketplace for suppliers of medical manufacturing. The trade fair, which takes place every November and is co-located to MEDICA in Dusseldorf, has been steadily growing over the past years and shows that medical technology remains a rapidly growing market.
In 2016, the joint pavilion by the IVAM Microtechnology Network, the Product Market “High-tech for Medical Devices”, will be located in Hall 8a again and will...
'Ferroelectric' materials can switch between different states of electrical polarization in response to an external electric field. This flexibility means they show promise for many applications, for example in electronic devices and computer memory. Current ferroelectric materials are highly valued for their thermal and chemical stability and rapid electro-mechanical responses, but creating a material that is scalable down to the tiny sizes needed for technologies like silicon-based semiconductors (Si-based CMOS) has proven challenging.
Now, Hiroshi Funakubo and co-workers at the Tokyo Institute of Technology, in collaboration with researchers across Japan, have conducted experiments to...
14.10.2016 | Event News
14.10.2016 | Event News
12.10.2016 | Event News
21.10.2016 | Health and Medicine
21.10.2016 | Information Technology
21.10.2016 | Materials Sciences