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MIT physicists have found a new way to switch superconductivity on and off in magic-angle graphene. This figure shows a device with two graphene layers in the middle (in dark gray and in inset). The graphene layers are sandwiched in between boron nitride layers (in blue and purple). The angle and alignment of each layer enables the researchers to turn superconductivity on and off in graphene with a short electric pulse.
MIT physicists have found a new way to switch superconductivity on and off in magic-angle graphene. This figure shows a device with two graphene layers in the middle (in dark gray and in inset). The graphene layers are sandwiched in between boron nitride layers (in blue and purple). The angle and alignment of each layer enables the researchers to turn superconductivity on and off in graphene with a short electric pulse.
Tyler O'Neal, Staff Editor ACADEMIA January 30, 2023, 2:00 pm

MIT physicists demo exotic properties in magic-angle graphene to switch superconductivity abruptly for realizing neuromorphic supercomputing

A quick electric pulse completely flips the material’s electronic properties, opening a route to ultrafast, brain-inspired, superconducting electronics.

With some careful twisting and stacking, MIT physicists have revealed a new and exotic property in “magic-angle” graphene: superconductivity that can be turned on and off with an electric pulse, much like a light switch.

The discovery could lead to ultrafast, energy-efficient superconducting transistors for neuromorphic devices — electronics designed to operate in a way similar to the rapid on/off firing of neurons in the human brain.

Magic-angle graphene refers to a very particular stacking of graphene — an atom-thin material made from carbon atoms that are linked in a hexagonal pattern resembling chicken wire. When one sheet of graphene is stacked atop a second sheet at a precise “magic” angle, the twisted structure creates a slightly offset “moiré” pattern or superlattice, that can support a host of surprising electronic behaviors.

In 2018, Pablo Jarillo-Herrero and his group at MIT were the first to demonstrate magic-angle twisted bilayer graphene. They showed that the new bilayer structure could behave as an insulator, much like wood, when they applied a certain continuous electric field. When they upped the field, the insulator suddenly morphed into a superconductor, allowing electrons to flow, friction-free.

That discovery was a watershed in the field of “twistronics,” which explores how certain electronic properties emerge from the twisting and layering of two-dimensional materials. Researchers including Jarillo-Herrero have continued to reveal surprising properties in magic-angle graphene, including various ways to switch the material between different electronic states. So far, such “switches” have acted more like dimmers, in that researchers must continuously apply an electric or magnetic field to turn on superconductivity and keep it on.

Now Jarillo-Herrero and his team have shown that superconductivity in magic-angle graphene can be switched on, and kept on, with just a short pulse rather than a continuous electric field. The key, they found, was a combination of twisting and stacking.

The team reports that by stacking magic-angle graphene between two offset layers of boron nitride — a two-dimensional insulating material — the unique alignment of the sandwich structure enabled the researchers to turn graphene’s superconductivity on and off with a short electric pulse.

“For the vast majority of materials, if you remove the electric field, zzzzip, the electric state is gone,” says Jarillo-Herrero, who is the Cecil and Ida Green Professor of Physics at MIT. “This is the first time that a superconducting material has been made that can be electrically switched on and off, abruptly. This could pave the way for a new generation of twisted, graphene-based superconducting electronics.”

His MIT co-writers are lead researcher Dahlia Klein Ph.D. ’21, graduate student Li-Qiao Xia, and former postdoc David MacNeill, along with Kenji Watanabe and Takashi Taniguchi of the National Institute for Materials Science in Japan.

Flipping the switch

In 2019, a team at Stanford University discovered that magic-angle graphene could be coerced into a ferromagnetic state. Ferromagnets are materials that retain their magnetic properties, even in the absence of an externally applied magnetic field.

The researchers found that magic-angle graphene could exhibit ferromagnetic properties in a way that could be turned on and off. This happened when the graphene sheets were layered between two sheets of boron nitride such that the crystal structure of the graphene was aligned to one of the boron nitride layers. The arrangement resembled a cheese sandwich in which the top slice of bread and the cheese orientations are aligned, but the bottom slice of bread is rotated at a random angle with respect to the top slice. The result intrigued the MIT group.

“We were trying to get a stronger magnet by aligning both slices,” Jarillo-Herrero says. “Instead, we found something completely different.”

In their current study, the team fabricated a sandwich of carefully angled and stacked materials. The “cheese” of the sandwich consisted of magic-angle graphene — two graphene sheets, the top rotated slightly at the “magic” angle of 1.1 degrees with respect to the bottom sheet. Above this structure, they placed a layer of boron nitride, exactly aligned with the top graphene sheet. Finally, they placed a second layer of boron nitride below the entire structure and offset it by 30 degrees with respect to the top layer of boron nitride.

The team then measured the electrical resistance of the graphene layers as they applied a gate voltage. They found as others have, that the twisted bilayer graphene switched electronic states, changing between insulating, conducting, and superconducting states at certain known voltages.

What the group did not expect was that each electronic state persisted rather than immediately disappearing once the voltage was removed — a property known as bistability. They found that, at a particular voltage, the graphene layers turned into a superconductor, and remained superconducting, even as the researchers removed this voltage.  

This bistable effect suggests that superconductivity can be turned on and off with short electric pulses rather than a continuous electric field, similar to flicking a light switch. It isn’t clear what enables this switchable superconductivity, though the researchers suspect it has something to do with the special alignment of the twisted graphene to both boron nitride layers, which enables a ferroelectric-like response of the system. (Ferroelectric materials display bistability in their electric properties.)

“By paying attention to the stacking, you could add another tuning knob to the growing complexity of magic-angle, superconducting devices,” Klein says. 

For now, the team sees the new superconducting switch as another tool researchers can consider as they develop materials for faster, smaller, more energy-efficient electronics.

“People are trying to build electronic devices that do calculations in a way that’s inspired by the brain,” Jarillo-Herrero says. “In the brain, we have neurons that, beyond a certain threshold, they fire. Similarly, we now have found a way for magic-angle graphene to switch superconductivity abruptly, beyond a certain threshold. This is a key property in realizing neuromorphic computing.”  

This research was supported in part by the U.S. Air Force Office of Scientific Research, the U.S. Army Research Office, and the Gordon and Betty Moore Foundation.

Examples showing the four types of training data.
Examples showing the four types of training data.

SETI deploys machine-learning to reveal signals of interest

Tyler O'Neal, Staff Editor ACADEMIA January 30, 2023, 12:00 pm

When pondering the probability of discovering technologically advanced extraterrestrial life, the question that often arises is, "if they're out there, why haven't we found them yet?" And often, the response is that we have only searched a tiny portion of the galaxy. Further, algorithms developed decades ago for the earliest digital computers can be outdated and inefficient when applied to modern petabyte-scale datasets. Now, research led by an undergraduate student at the University of Toronto, Peter Ma, along with researchers from the SETI Institute, Breakthrough Listen, and scientific research institutions around the world, has applied a deep learning technique to a previously studied dataset of nearby stars and uncovered eight previously unidentified signals of interest.

“In total, we had searched through 150 TB of data of 820 nearby stars, on a dataset that had previously been searched through in 2017 by classical techniques but labeled as devoid of interesting signals," said Peter Ma, lead author. “We're scaling this search effort to 1 million stars today with the MeerKAT telescope and beyond. We believe that work like this will help accelerate the rate we’re able to make discoveries in our grand effort to answer the question ‘are we alone in the universe?’”

The search for extraterrestrial intelligence (SETI) looks for evidence of extraterrestrial intelligence originating beyond Earth by trying to detect technosignatures, or evidence of technology, that alien civilizations could have developed. The most common technique is to search for radio signals. Radio is a great way to send information over the incredible distances between the stars; it quickly passes through the dust and gas that permeate space, and it does so at the speed of light (about 20,000 times faster than our best rockets). Many SETI efforts use antennas to eavesdrop on any radio signals aliens might be transmitting.

This study re-examined data taken with the Green Bank Telescope in West Virginia as part of a Breakthrough Listen campaign that initially indicated no targets of interest. The goal was to apply new deep learning techniques to a classical search algorithm to yield faster, more accurate results. After running the new algorithm and manually re-examining the data to confirm the results, newly detected signals had several key characteristics:

  1. The signals were narrow band, meaning they had narrow spectral width, on the order of just a few Hz. Signals caused by natural phenomena tend to be broadband.
  2. The signals had non-zero drift rates, which means the signals had a slope. Such slopes could indicate a signal’s origin had some relative acceleration with our receivers, hence not local to the radio observatory.
  3. The signals appeared in ON-source observations and not in OFF-source observations. If a signal originates from a specific celestial source, it appears when we point our telescope toward the target and disappears when we look away. Human radio interference usually occurs in ON and OFF observations due to the source being close by.

Cherry Ng, another of Ma’s research advisors and an astronomer at both the SETI Institute and the French National Center for Scientific Research said, “These results dramatically illustrate the power of applying modern machine learning and computer vision methods to data challenges in astronomy, resulting in both new detections and higher performance. Application of these techniques at scale will be transformational for radio techno signature science.”

While re-examinations of these new targets of interest have yet to result in re-detections of these signals, this new approach to analyzing data can enable researchers to more effectively understand the data they collect and act quickly to re-examine targets.  Ma and his advisor Dr. Cherry Ng are looking forward to deploying extensions of this algorithm on the SETI Institute’s COSMIC system.

Since SETI experiments began in 1960 with Frank Drake’s Project Ozma at the Greenbank Observatory, a site now home to the telescope used in this latest work, technological advances have enabled researchers to collect more data than ever. This massive volume of data requires new computational tools to process and analyze that data quickly to identify anomalies that could be evidence of extraterrestrial intelligence. This new machine-learning approach is breaking new ground in the quest to answer the question, “are we alone?”

FAU Harbor Branch wins EPA grant to study connectivity between Everglades, Florida Keys

Tyler O'Neal, Staff Editor ACADEMIA June 22, 2022, 10:14 am

The ongoing Comprehensive Everglades Restoration Plan (CERP) is working to restore the historical flow of the Florida Everglades to bring back the health of the ecosystem, which has seen declines in water quality and habitat loss and degradation. 

Using drifters, researchers will investigate the transport and dispersion of freshwater through the Florida Bay.

The Southwest Florida coast, the Florida Keys Reef Tract, and Florida Bay together support abundant underwater vegetation, corals, and fish as well as a prosperous tourist economy. At the epicenter of this region is the Florida Bay ecosystem, which is directly impacted by these watershed inputs and plays a critical role in buffering downstream ecosystems.

Reallocating freshwater flow to the Florida Bay is expected to reduce hypersaline conditions, which, on the other hand, may deliver more nutrients that elevate phytoplankton blooms. 

Significant evidence shows that these waters and associated nutrients can move further downstream and impact the Florida Keys National Marine Sanctuary and the Florida Keys Reef Tract. Interactions between nutrient inputs, phytoplankton blooms, and sediment processes change water properties before they reach the Florida Keys, and the transport pathways and subsequent biogeochemical responses are complex. At the same time, climate change including sea-level rise is modifying both oceanic boundary conditions of the regions, and watershed hydrological conditions and outputs, among other effects.

Currently, the predictive capability of these watershed impacts is limited. Most of the biogeochemical observations are through discrete water samples that are not continuous. New methods are urgently needed to synthesize all of the available sporadic observations and empirical biogeochemical theories into a coherent system for the region.

Researchers from Florida Atlantic University’s Harbor Branch Oceanographic Institute have received a $350,000 grant from the United States Environmental Protection Agency to study the connectivity between the Everglades and the Florida Keys via the Florida Bay. They are developing an ocean model for the region, an innovative tool to holistically examine and diagnose key processes with numerical simulations and experiments, and to predict changes in responses to water management, ecological restoration, and climate change. 

“Our model, when fully developed and validated, is expected to be a powerful tool that is currently lacking for this region,” said Mingshun Jiang, Ph.D., principal investigator, physical oceanographer specializing in ocean coupled physical-biogeochemical-ecological modeling, and an associate of research professor at FAU Harbor Branch. “It is designed to provide a suite of environmental and ecological information on the state of the greater Florida Bay ecosystem as well as potential future changes. Importantly, our model could potentially predict underwater aquatic vegetation coverage, harmful algal blooms, and fisheries resources under climate change and/or CERP management scenarios.”

To assist in the model development, Jiang and co-PI Laurent Chérubin, Ph.D., a physical oceanographer who specializes in the understanding of ocean dynamics and a research professor at FAU Harbor Branch, will measure currents and water quality parameters at several key locations in the Florida Bay during dry and wet seasons. They will gauge estimates of nutrients and organic export from the Florida Bay to the Florida Keys National Marine Sanctuary and the Florida Keys Reef Tract.

Jiang and Chérubin will release neutrally buoyant (artificial) drifters from designated locations and track their trajectories to observe the movements of waters and associated pollutants. Using these drifters, they will investigate the transport and dispersion of freshwater through the Florida Bay, particularly in the northeast region. These drifters have been successfully used for studying the transport and dispersion of waters in shallow waters such as Florida’s Indian River Lagoon.  

Fieldwork also will include moorings of three small benthic landers each equipped with one acoustic Doppler current profiler (ADCP) and a water quality sampling and monitoring meter. Deployed at strategic locations, the researchers will measure exchanges of waters between the northeastern basin, which receives high freshwater nutrients and inputs, the southeastern basin, and water exchanges between the Florida Bay and the southwest Florida shelf where fluxes remain highly uncertain.

A new biogeochemical model will be developed to simulate nutrient (nitrogen, phosphorus) cycles, phytoplankton blooms including Karenia Brevis (red tide), cyanobacteria (blue-green algae) blooms, zooplankton, and dissolved oxygen. This model will be coupled with an existing hydrodynamic model to synthesize the observations and empirical theories. In particular, using new and historical measurements along with the new model, researchers will quantify the Florida Bay export of nutrients and organic matter and evaluate the impacts of these exports on nutrients, phytoplankton blooms, and water clarity.

“New and historical data combined with our modeling will allow us to construct a full picture of connectivity of waters and associated pollutants such as nutrients, organics, and other emerging pollutants such as microplastics in this region under various conditions including wet and dry seasons as well as storms,” said Chérubin. “Results from our project will help water management agencies develop better plans for minimizing the environmental, ecological, and human impacts of discharges from the Everglades as well as potentially improving habitat restoration efforts for seagrass and corals.”

Collaborators on the project include the South Florida Water Management District, Florida International University, University of South Florida, Fish and Wildlife Research Institute, and NOAA’s Atlantic Oceanographic and Meteorological Laboratory.  

  1. MD simulations of proteins help unravel why chemotherapy resistance occurs
  2. Japan unveils the mysteries of the genome structure in the human cell nucleus using simulation

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