Aurelia Butler

Nobel laureate in physics Richard Feynman once described turbulence as “the most important unsolved problem of classical physics.”
Understanding turbulence in classical fluids like water and air is difficult partly because of the challenge in identifying the vortices swirling within those fluids. Locating vortex tubes and tracking their motion could greatly simplify the modeling of turbulence.
But that challenge is easier in quantum fluids, which exist at low enough temperatures that quantum mechanics — which deals with physics on the scale of atoms or subatomic particles — govern their behavior.
In a new study published in Proceedings of the National Academy of Sciences, Florida State University researchers managed to visualize the vortex tubes in a quantum fluid, findings that could help researchers better understand turbulence in quantum fluids and beyond.
From left, Wei Guo, an associate professor of mechanical engineering at the FAMU-FSU College of Engineering, and Yuan Tang, a postdoctoral researcher at the National High Magnetic Field Laboratory, in front of the experimental setup. (Courtesy of Wei Guo)
“Our study is important not only because it broadens our understanding of turbulence in general, but also because it could benefit the studies of various physical systems that also involve vortex tubes, such as superconductors and even neutron stars,” said Wei Guo, an associate professor of mechanical engineering at the FAMU-FSU College of Engineering and the study’s principal investigator. More

Researchers have developed a new algorithm capable of identifying features of male zebra finch songs that may underlie the distinction between a short phrase sung during courtship, and the same phrase sung in a non-courtship context. Sarah Woolley of McGill University in Montreal, Canada, and colleagues present these findings in the open-access journal PLOS Computational Biology.
Like many animals, male zebra finches adjust their vocal signals for their audience. They may sing the same sequence of syllables during courtship interactions with females as when singing alone, but with subtle modifications. However, humans cannot detect these differences, and it was not clear that female zebra finches could, either.
For the new study, Woolley and colleagues first conducted behavioral experiments demonstrating that female zebra finches are indeed highly adept at discriminating between short segments of males’ songs recorded in courtship versus non-courtship settings.
Next, they sought to expand on earlier studies that have focused on just a few specific song features that may underlie the distinction between courtship and non-courtship song. Taking a “bottom-up” approach, the researchers extracted over 5,000 song features from recordings and trained an algorithm to use those features to distinguish between courtship and non-courtship song phrases.
The trained algorithm uncovered features that may be key for song perception, some of which had not been identified previously. It also made predictions about the distinction capabilities of female zebra finches that aligned well with the results of the behavioral experiments.
These findings highlight the potential for bottom-up approaches to reveal acoustic features important for communication and social discrimination.
“As vocal communicators ourselves, we have a tendency to focus on aspects of communication signals that are salient to us,” Woolley says. “Using our bottom-up approach, we identified features that might never have been on our radar.”
Next, the researchers plan to test whether manipulating the acoustic features they discovered alters what female finches think about those songs. They also hope to evaluate how well their findings might generalize to courtship and non-courtship songs in other species.
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How can large amounts of data be transferred or processed as quickly as possible? One key to this could be graphene. The ultra-thin material is only one atomic layer thick, and the electrons it contains have very special properties due to quantum effects. It could therefore be very well suited for use in high-performance electronic components. Up to this point, however, there has been a lack of knowledge about how to suitably control certain properties of graphene. A new study by a team of scientists from Bielefeld and Berlin, together with researchers from other research institutes in Germany and Spain, is changing this. The team’s findings have been published in the journal Science Advances.
Consisting of carbon atoms, graphene is a material just one atom thick where the atoms are arranged in a hexagonal lattice. This arrangement of atoms is what results in graphene’s unique property: the electrons in this material move as if they did not have mass. This “massless” behavior of electrons leads to very high electrical conductivity in graphene and, importantly, this property is maintained at room temperature and under ambient conditions. Graphene is therefore potentially very interesting for modern electronics applications.
It was recently discovered that the high electronic conductivity and “massless” behavior of its electrons allows graphene to alter the frequency components of electric currents that pass through it. This property is highly dependent on how strong this current is. In modern electronics, such a nonlinearity comprises one of the most basic functionalities for switching and processing of electrical signals. What makes graphene unique is that its nonlinearity is by far the strongest of all electronic materials. Moreover, it works very well for exceptionally high electronic frequencies, extending into the technologically important terahertz (THz) range where most conventional electronic materials fail.
In their new study, the team of researchers from Germany and Spain demonstrated that graphene’s nonlinearity can be very efficiently controlled by applying comparatively modest electrical voltages to the material. For this, the researchers manufactured a device resembling a transistor, where a control voltage could be applied to graphene via a set of electrical contacts. Then, ultrahigh-frequency THz signals were transmitted using the device: the transmission and subsequent transformation of these signals were then analyzed in relation to the voltage applied. The researchers found that graphene becomes almost perfectly transparent at a certain voltage — its normally strong nonlinear response nearly vanishes. By slightly increasing or lowering the voltage from this critical value, graphene can be turned into a strongly nonlinear material, significantly altering the strength and the frequency components of the transmitted and remitted THz electronic signals.
“This is a significant step forward towards implementation of graphene in electrical signal processing and signal modulation applications,” says Prof. Dmitry Turchinovich, a physicist at Bielefeld University and one of the heads of this study. “Earlier we had already demonstrated that graphene is by far the most nonlinear functional material we know of. We also understand the physics behind nonlinearity, which is now known as thermodynamic picture of ultrafast electron transport in graphene. But until now we did not know how to control this nonlinearity, which was the missing link with respect to using graphene in everyday technologies.”
“By applying the control voltage to graphene, we were able to alter the number of electrons in the material that can move freely when the electrical signal is applied to it,” explains Dr. Hassan A. Hafez, a member of Professor Dr. Turchinovich’s lab in Bielefeld, and one of the lead authors of the study. “On one hand, the more electrons can move in response to the applied electric field, the stronger the currents, which should enhance the nonlinearity. But on the other hand, the more free electrons are available, the stronger the interaction between them is, and this suppresses the nonlinearity. Here we demonstrated — both experimentally and theoretically — that by applying a relatively weak external voltage of only a few volts, the optimal conditions for the strongest THz nonlin-earity in graphene can be created.”
“With this work, we have reached an important milestone on the path towards to using graphene as an extremely efficient nonlinear functional quantum material in devices like THz frequency converters, mixers, and modulators,” says Professor Dr. Michael Gensch from the Institute of Optical Sensor Systems of the German Aerospace Center (DLR) and the Technical University of Berlin, who is the other head of this study. “This is extremely relevant because graphene is perfectly compatible with existing electronic ultrahigh-frequency semiconductor technology such as CMOS or Bi-CMOS. It is therefore now possible to envision hybrid devices in which the initial electric signal is generated at lower frequency using existing semiconductor technology but can then very efficiently be up-converted to much higher THz frequencies in graphene, all in a fully controllable and predictable manner.”
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Powerful algorithms used by Netflix, Amazon and Facebook can ‘predict’ the biological language of cancer and neurodegenerative diseases like Alzheimer’s, scientists have found.
Big data produced during decades of research was fed into a computer language model to see if artificial intelligence can make more advanced discoveries than humans.
Academics based at St John’s College, University of Cambridge, found the machine-learning technology could decipher the ‘biological language’ of cancer, Alzheimer’s, and other neurodegenerative diseases.
Their ground-breaking study has been published in the scientific journal PNAS today (April 8 2021) and could be used in the future to ‘correct the grammatical mistakes inside cells that cause disease’.
Professor Tuomas Knowles, lead author of the paper and a Fellow at St John’s College, said: “Bringing machine-learning technology into research into neurodegenerative diseases and cancer is an absolute game-changer. Ultimately, the aim will be to use artificial intelligence to develop targeted drugs to dramatically ease symptoms or to prevent dementia happening at all.”
Every time Netflix recommends a series to watch or Facebook suggests someone to befriend, the platforms are using powerful machine-learning algorithms to make highly educated guesses about what people will do next. Voice assistants like Alexa and Siri can even recognise individual people and instantly ‘talk’ back to you. More

Using DNA structures as scaffolds, Tim Liedl, a scientist of Ludwig-Maximilians-Universitaet (LMU) in Munich, has shown that precisely positioned gold nanoparticles can serve as efficient energy transmitters.
Since the inception of the field in 2006, laboratories around the world have been exploring the use of ‘DNA origami’ for the assembly of complex nanostructures. The method is based on DNA strands with defined sequences that interact via localized base pairing. “With the aid of short strands with appropriate sequences, we can connect specific regions of long DNA molecules together, rather like forming three-dimensional structures by folding a flat sheet of paper in certain ways,” as Professor Tim Liedl of the Faculty of Physics at LMU explains.
Image and mirror image
Liedl has now used DNA origami to construct chiral objects, i.e. structures that cannot be superimposed by any combination of rotation and translation. Instead they possess ‘handedness’, and are mirror images of one another. Such pairs often differ in their physical properties, for example, in the degree to which they absorb polarized light. This effect can be exploited in many ways. For example, it is the basis for CD spectroscopy (the ‘CD’ here stands for ‘circular dichroism’), a technique that is used to elucidate the overall spatial configuration of chemical compounds, and even whole proteins.
With a view to assembling chiral metal structures, Liedl and his group synthesized complex DNA-origami structures that provide precisely positioned binding sites for the attachment of spherical and rod-shaped gold nanoparticles. The scaffold therefore serves as a template or mold for the placement of nanoparticles at predetermined positions and in a defined spatial orientation. “One can assemble a chiral object based solely on the arrangement of the gold nanoparticles,” says Liedl
Gold is not only chemically robust, as a noble metal it exhibits what are known as surface plasmon resonances. Plasmons are coherent electron oscillations that are generated when light interacts with the surface of a metal structure. “One can picture these oscillations as being like the waves that are excited when a bottle of water is shaken either parallel or at right angles to its long axis,” says Liedl.
Gold nanoparticles as energy transmitters
Oscillations excited in spatially contiguous gold particles can couple to one another, and the plasmons in Liedl’s experiments behave as image and mirror image, thanks to their chiral disposition on the origami scaffold. “This is confirmed by our CD spectroscopic measurements,” says Liedl. In the experiments, the chiral structures are irradiated with circularly polarized light and the level of absorption is measured as a percentage of the input. This enables right- and left-handed arrangements to be distinguished from one another.
In principle, two gold nanorods should be sufficient for the construction of chiral object, as they can be arranged either in the form of an L or an inverted L. However, the rods used in the experiments were relatively far apart (on the nanoscale) and the plasmons excited in one had little effect on those generated in the other, i.e. the two hardly coupled to each other at all. But Liedl and his colleagues had a trick up their sleeves. By appropriate redesign of the origami structure, they were able to position a gold nanosphere between the pair of L-formed rods, which effectively amplified the coupling. CD spectroscopy revealed the presence of energy transitions, thus confirming the hypothesis which the team had derived from simulations.
Liedl envisages two potential settings in which these nanostructures could find practical application. They could be used to detect viruses, since the binding of viral nucleic acids to a gold particle will amplify the CD signal. In addition, chiral plasmonic transmitters could serve as model switching devices in optical computers, in which optical elements replace the transistors that are the workhorses of electronic computers.
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It may be possible in the future to use information technology where electron spin is used to store, process and transfer information in quantum computers. It has long been the goal of scientists to be able to use spin-based quantum information technology at room temperature. A team of researchers from Sweden, Finland and Japan have now constructed a semiconductor component in which information can be efficiently exchanged between electron spin and light at room temperature and above. The new method is described in an article published in Nature Photonics.
It is well known that electrons have a negative charge, and they also have another property, namely spin. The latter may prove instrumental in the advance of information technology. To put it simply, we can imagine the electron rotating around its own axis, similar to the way in which the Earth rotates around its own axis. Spintronics — a promising candidate for future information technology — uses this quantum property of electrons to store, process and transfer information. This brings important benefits, such as higher speed and lower energy consumption than traditional electronics.
Developments in spintronics in recent decades have been based on the use of metals, and these have been highly significant for the possibility of storing large amounts of data. There would, however, be several advantages in using spintronics based on semiconductors, in the same way that semiconductors form the backbone of today’s electronics and photonics.
“One important advantage of spintronics based on semiconductors is the possibility to convert the information that is represented by the spin state and transfer it to light, and vice versa. The technology is known as opto-spintronics. It would make it possible to integrate information processing and storage based on spin with information transfer through light,” says Weimin Chen, professor at Linköping University, Sweden, who led the project.
As electronics used today operates at room temperature and above, a serious problem in the development of spintronics has been that electrons tend to switch and randomise their direction of spin when the temperature rises. This means that the information coded by the electron spin states is lost or becomes ambiguous. It is thus a necessary condition for the development of semiconductor-based spintronics that we can orient essentially all electrons to the same spin state and maintain it, in other words that they are spin polarised, at room temperature and higher temperatures. Previous research has achieved a highest electron spin polarisation of around 60% at room temperature, untenable for large-scale practical applications.
Researchers at Linköping University, Tampere University and Hokkaido University have now achieved an electron spin polarisation at room temperature greater than 90%. The spin polarisation remains at a high level even up to 110 °C. This technological advance, which is described in Nature Photonics, is based on an opto-spintronic nanostructure that the researchers have constructed from layers of different semiconductor materials. It contains nanoscale regions called quantum dots. Each quantum dot is around 10,000 times smaller than the thickness of a human hair. When a spin polarised electron impinges on a quantum dot, it emits light — to be more precise, it emits a single photon with a state (angular momentum) determined by the electron spin. Thus, quantum dots are considered to have a great potential as an interface to transfer information between electron spin and light, as will be necessary in spintronics, photonics and quantum computing. In the newly published study, the scientists show that it is possible to use an adjacent spin filter to control the electron spin of the quantum dots remotely, and at room temperature.
The quantum dots are made from indium arsenide (InAs), and a layer of gallium nitrogen arsenide (GaNAs) functions as a filter of spin. A layer of gallium arsenide (GaAs) is sandwiched between them. Similar structures are already being used in optoelectronic technology based on gallium arsenide, and the researchers believe that this can make it easier to integrate spintronics with existing electronic and photonic components.
“We are very happy that our long-term efforts to increase the expertise required to fabricate highly-controlled N-containing semiconductors is defining a new frontier in spintronics. So far, we have had a good level of success when using such materials for optoelectronics devices, most recently in high-efficiency solar-cells and laser diodes. Now we are looking forward to continuing this work and to unite photonics and spintronics, using a common platform for light-based and spin-based quantum technology,” says Professor Mircea Guina, head of the research team at Tampere University in Finland.
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Materials provided by Linköping University. Original written by Karin Söderlund Leifler. Note: Content may be edited for style and length. More

A decade ago, the discovery of quasiparticles called magnetic skyrmions provided important new clues into how microscopic spin textures will enable spintronics, a new class of electronics that use the orientation of an electron’s spin rather than its charge to encode data.
But although scientists have made big advances in this very young field, they still don’t fully understand how to design spintronics materials that would allow for ultrasmall, ultrafast, low-power devices. Skyrmions may seem promising, but scientists have long treated skyrmions as merely 2D objects. Recent studies, however, have suggested that 2D skyrmions could actually be the genesis of a 3D spin pattern called hopfions. But no one had been able to experimentally prove that magnetic hopfions exist on the nanoscale.
Now, a team of researchers co-led by Berkeley Lab has reported in Nature Communications the first demonstration and observation of 3D hopfions emerging from skyrmions at the nanoscale (billionths of a meter) in a magnetic system. The researchers say that their discovery heralds a major step forward in realizing high-density, high-speed, low-power, yet ultrastable magnetic memory devices that exploit the intrinsic power of electron spin.
“We not only proved that complex spin textures like 3D hopfions exist — We also demonstrated how to study and therefore harness them,” said co-senior author Peter Fischer, a senior scientist in Berkeley Lab’s Materials Sciences Division who is also an adjunct professor in physics at UC Santa Cruz. “To understand how hopfions really work, we have to know how to make them and study them. This work was possible only because we have these amazing tools at Berkeley Lab and our collaborative partnerships with scientists around the world,” he said.
According to previous studies, hopfions, unlike skyrmions, don’t drift when they move along a device and are therefore excellent candidates for data technologies. Furthermore, theory collaborators in the United Kingdom had predicted that hopfions could emerge from a multilayered 2D magnetic system.
The current study is the first to put those theories to test, Fischer said. More

Working safely is not only about processes, but context — understanding the work environment and circumstances, and being able to predict what other people will do next. A new system empowers robots with this level of context awareness, so they can work side-by-side with humans on assembly lines more efficiently and without unnecessary interruptions.
Instead of being able to only judge distance between itself and its human co-workers, the human-robot collaboration system can identify each worker it works with, as well as the person’s skeleton model, which is an abstract of body volume, says Hongyi Liu, a researcher at KTH Royal Institute of Technology. Using this information, the context-aware robot system can recognize the worker’s pose and even predict the next pose. These abilities provide the robot with a context to be aware of while interacting.
Liu says that the system operates with artificial intelligence that requires less computational power and smaller datasets than traditional machine learning methods. It relies instead on a form of machine learning called transfer learning — which reuses knowledge developed through training before being adapted into an operational model.
The research was published in the recent issue of Robotics and Computer-Integrated Manufacturing, and was co-authored by KTH Professor Lihui Wang.
Liu says that the technology is out ahead of today’s International Organization for Standards (ISO) requirements for collaborative robot safety, so implementation of the technology would require industrial action. But the context awareness offers better efficiency than the one-dimensional interaction workers now experience with robots, he says.
“Under the ISO standard and technical specification, when a human approaches a robot it slows down, and if he or she comes close enough it will stop. If the person moves away it resumes. That’s a pretty low level of context awareness,” he says.
“It jeopardizes efficiency. Production is slowed and humans cannot work closely to robots.”
Liu compares the context-aware robot system to a self-driving car that recognizes how long a stoplight has been red and anticipates moving again. Instead of braking or downshifting, it begins to adjust its speed by cruising toward the intersection, thereby sparing the brakes and transmission further wear.
Experiments with the system showed that with context, a robot can operate more safely and efficiently without slowing down production.
In one test performed with the system, a robot arm’s path was blocked unexpectedly by someone’s hand. But rather than stop, the robot adjusted — it predicted the future trajectory of the hand and the arm moved around the hand.
“This is safety not just from the technical point of view in avoiding collisions, but being able to recognize the context of the assembly line,” he says. “This gives an additional layer of safety.”
The research was an extension of the Symbiotic Human Robot Collaborative Assembly project, which was completed in 2019.
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