Doctoral student Soumendu Bagchi, along with his adviser Huck Beng Chew in the Department of Aerospace Engineering in collaboration with Harley Johnson from Mechanical Sciences and Engineering identified how twisted graphene sheets behave and their stability at different sizes and temperatures.

“We concentrated on two graphene sheets stacked on top of each other but with a twist angle,” said Bagchi. “We did atomistic simulations at different temperatures for different sizes of graphene sheets. Using insights from these simulations, we developed an analytical model — you can plug in any sheet size, any twist angle, and the model will predict the number of local stable states it has as well as the critical temperature required to reach each of those states.”

Bagchi explained that bilayer graphene exists in an untwisted Bernal-stacked configuration, which is also the repeated stacking sequence of crystalline hexagonal graphite. When bilayer graphene is twisted, it wants to untwist back to its original state because that’s the most stable state and placement of the atoms.

“When the twisted atomic structure is heated, it tends to rotate back, but there are certain magic twist angles at which the structure remains stable below a specific temperature. And, there is a size dependency as well. What’s exciting about our work is, depending upon the size of the graphene sheet, we can predict how many stable states you will have, the magic twist angles at these stable states, as well as the range of temperatures required for twisted graphene to transition from one stable state to another,” Bagchi said.

According to Chew, manufacturers have been trying to make graphene transistors, and twisted graphene bilayers are known to exhibit exciting electronic properties. In manufacturing these graphene transistors, it’s important to know what temperature will excite the material to achieve a certain rotation or mechanical response.

“They’ve known that a graphene sheet has certain electronic properties, and adding a second sheet at an angle yields new unique properties. But a single atomic sheet is not easy to manipulate. Fundamentally, this study answers questions about how twisted graphene sheets behave under thermal loading, and provides insights into the self-alignment mechanisms and forces at the atomic level. This could potentially pave the way for manufacturers to achieve fine control over the twist angle of 2D material structures. They can directly plug in parameters into the model to understand the necessary conditions required to achieve a specific twisted state.”

Bagchi said no one has studied the 2D properties of materials like this. It is a very fundamental study, and one that began as a different project, when he bumped into something unusual.

“He noticed that the graphene sheets showed some temperature dependence,” Chew said. “We wondered why it behaved this way — not like a normal material.

“In normal materials, the interface is typically very strong. With graphene, the interface is very weak allowing the layers to slide and rotate. Observing this interesting temperature dependency wasn’t planned. This is the beauty of discovery in science.”

The goal of DES, which completed six years of data collection in January, is to understand the nature of dark energy by collecting high-precision images of the southern sky. While DES wasn’t specifically designed with TNOs in mind, its breadth and depth of coverage made it particularly adept at finding new objects beyond Neptune. “The number of TNOs you can find depends on how much of the sky you look at and what’s the faintest thing you can find,” says Bernstein.

Because DES was designed to study galaxies and supernovas, the researchers had to develop a new way to track movement. Dedicated TNO surveys take measurements as frequently as every hour or two, which allows researchers to more easily track their movements. “Dedicated TNO surveys have a way of seeing the object move, and it’s easy to track them down,” says Bernardinelli. “One of the key things we did in this paper was figure out a way to recover those movements.”

Using the first four years of DES data, Bernardinelli started with a dataset of 7 billion “dots,” all of the possible objects detected by the software that were above the image’s background levels. He then removed any objects that were present on multiple nights — things like stars, galaxies, and supernova — to build a “transient” list of 22 million objects before commencing a massive game of “connect the dots,” looking for nearby pairs or triplets of detected objects to help determine where the object would appear on subsequent nights.

With the 7 billion dots whittled down to a list of around 400 candidates that were seen over at least six nights of observation, the researchers then had to verify their results. “We have this list of candidates, and then we have to make sure that our candidates are actually real things,” Bernardinelli says.

To filter their list of candidates down to actual TNOs, the researchers went back to the original dataset to see if they could find more images of the object in question. “Say we found something on six different nights,” Bernstein says. “For TNOs that are there, we actually pointed at them for 25 different nights. That means there’s images where that object should be, but it didn’t make it through the first step of being called a dot.”

Bernardinelli developed a way to stack multiple images to create a sharper view, which helped confirm whether a detected object was a real TNO. They also verified that their method was able to spot known TNOs in the areas of the sky being studied and that they were able to spot fake objects that were injected into the analysis. “The most difficult part was trying to make sure that we were finding what we were supposed to find,” says Bernardinelli.

After many months of method-development and analysis, the researchers found 316 TNOs, including 245 discoveries made by DES and 139 new objects that were not previously published. With only 3,000 objects currently known, this DES catalog represents 10% of all known TNOs. Pluto, the best-known TNO, is 40 times farther away from the sun than Earth is, and the TNOs found using the DES data range from 30 to 90 times Earth’s distance from the sun. Some of these objects are on extremely long-distance orbits that will carry them far beyond Pluto.

Now that DES is complete, the researchers are rerunning their analysis on the entire DES dataset, this time with a lower threshold for object detection at the first filtering stage. This means that there’s an even greater potential for finding new TNOs, possibly as many as 500, based on the researchers’ estimates, in the near future.

The method developed by Bernardinelli can also be used to search for TNOs in upcoming astronomy surveys, including the new Vera C. Rubin Observatory. This observatory will survey the entire southern sky and will be able to detect even fainter and more distant objects than DES. “Many of the programs we’ve developed can be easily applied to any other large datasets, such as what the Rubin Observatory will produce,” says Bernardinelli.

This catalog of TNOs will also be a useful scientific tool for research about the solar system. Because DES collects a wide spectrum of data on each detected object, researchers can attempt to figure out where the TNO originated from, since objects that form more closely to the Sun have are expected to have different colors than those that originated in more distant and colder locations. And, by studying the orbits of these objects, researchers might be one step closer to finding Planet Nine, a hypothesized Neptune-sized planet that’s thought to exist beyond Pluto.

“There are lots of ideas about giant planets that used to be in the solar system and aren’t there anymore, or planets that are far away and massive but too faint for us to have noticed yet,” says Bernstein. “Making the catalog is the fun discovery part. Then when you create this resource; you can compare what you did find to what somebody’s theory said you should find.”

“As human genomic data collection rises, the organizations responsible for managing these data are developing and refining their internal policies and protocols related to data end uses, transparency and security, for example,” said Forrest Briscoe, professor of management and organization, Penn State. “In a survey of more than 2,000 people, we found that the majority of respondents clearly prefer a more transparent and participant-centric governance approach that gives them more control, confidence and compensation.”

The researchers created a survey based on in-depth field interviews with officials and employees who were involved in genomic governance at 12 different organizations. They recruited 2,020 participants — representative of the U.S. population — through Qualtrics to participate in the survey and provided them with mainstream media coverage of genomic database companies. The results will appear on March 11 in PLOS ONE.

Next, the team provided participants with a scenario:

“Imagine that today you are presented with an opportunity to provide your DNA data to Genetic Data Inc. [one of five similarly named fictitious companies], to be used in a biomedical research program. They can obtain your DNA data if you provide them with a small saliva sample. Genetic Data Inc. is a U.S. for-profit technology corporation. Based on this information, and what you have just learned about DNA data, how willing would you be to provide your DNA data to Genetic Data Inc.?”

The four response options were: “Willing as a charitable donation,” “Willing if I’m paid at least a certain amount of money,” “Unwilling, at least for now” and “Unwilling, now or ever.” Those who were willing to provide their data if they were paid were asked how much they would expect to be paid. All of the participants were also asked how much they would pay the company to obtain a report containing information about their ancestry and forecasting their risk for 20 different genetically based health conditions.

The team found that 11.7% of respondents were willing to altruistically donate their data, 50.6% were willing to provide data only if they were financially compensated and 37.8% were unwilling to provide data regardless of compensation. For the altruistic donors, the median net expected payment — after subtracting the amount they were willing to pay for a personalized report — was -$75, while the median net expected payment for respondents who wanted to be compensated for their data was +$95.

“Our results suggest that as public awareness grows regarding the commercial aspects and privacy issues of genomic databases, individuals’ expectations for compensation in exchange for data provision may rise,” said Briscoe.

The researchers also asked participants questions about how willing they would be to provide genomic data to companies given 12 different governance policies.

The three policies that increased willingness the most were:

• ability for data providers to request that their data be deleted
• assurance that providers’ data would not be sold or shared beyond the organization collecting it
• assurance that companies’ re-use of provider data would require specific permissions

The three policies that decreased willingness the most were:

• selling database access to pharmaceutical firms
• providing data to the federal government
• retaining data indefinitely without a specified date for destruction

“A common denominator across our governance policy findings is a preference for restrictions on sharing or reuse, unless permission is specifically granted by the individual,” said Briscoe. “These preferences appear to pose a challenge for the goals and business models of many commercial and public database-owning organizations, which often envision that their databases will serve multiple scientific and commercial purposes through access arrangements with multiple outside partners.”

Yet, Briscoe added, technological solutions are being pursued that might give individual data providers more control over who accesses and uses their data and what their data are used for, while also allowing data sharing to meet the needs of health care, academic and industry communities. For example, DNA blockchains can enable people to have their genomes sequenced and then rent or sell access to them at their own discretion.

“Our findings offer a forward-looking window on individual preferences that can be useful for institutions of all types as they develop governance approaches in this area of large-scale data sharing,” he said.

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