Computers Math

Scientists at Oak Ridge National Laboratory used new techniques to create a composite that increases the electrical current capacity of copper wires, providing a new material that can be scaled for use in ultra-efficient, power-dense electric vehicle traction motors.
The research is aimed at reducing barriers to wider electric vehicle adoption, including cutting the cost of ownership and improving the performance and life of components such as electric motors and power electronics. The material can be deployed in any component that uses copper, including more efficient bus bars and smaller connectors for electric vehicle traction inverters, as well as for applications such as wireless and wired charging systems.
To produce a lighter weight conductive material with improved performance, ORNL researchers deposited and aligned carbon nanotubes on flat copper substrates, resulting in a metal-matrix composite material with better current handling capacity and mechanical properties than copper alone.
Incorporating carbon nanotubes, or CNTs, into a copper matrix to improve conductivity and mechanical performance is not a new idea. CNTs are an excellent choice due to their lighter weight, extraordinary strength and conductive properties. But past attempts at composites by other researchers have resulted in very short material lengths, only micrometers or millimeters, along with limited scalability, or in longer lengths that performed poorly.
The ORNL team decided to experiment with depositing single-wall CNTs using electrospinning, a commercially viable method that creates fibers as a jet of liquid speeds through an electric field. The technique provides control over the structure and orientation of deposited materials, explained Kai Li, a postdoctoral researcher in ORNL’s Chemical Sciences Division. In this case, the process allowed scientists to successfully orient the CNTs in one general direction to facilitate enhanced flow of electricity.
The team then used magnetron sputtering, a vacuum coating technique, to add thin layers of copper film on top of the CNT-coated copper tapes. The coated samples were then annealed in a vacuum furnace to produce a highly conductive Cu-CNT network by forming a dense, uniform copper layer and to allow diffusion of copper into the CNT matrix.

advertisement

Using this method, ORNL scientists created a copper-carbon nanotube composite 10 centimeters long and 4 centimeters wide, with exceptional properties. The microstructural properties of the material were analyzed using instruments at the Center for Nanophase Materials Sciences at ORNL, a U.S. Department of Energy Office of Science user facility. Researchers found the composite reached 14% greater current capacity, with up to 20% improved mechanical properties compared with pure copper, as detailed in ACS Applied Nano Materials.
Tolga Aytug, lead investigator for the project, said that “by embedding all the great properties of carbon nanotubes into a copper matrix, we are aiming for better mechanical strength, lighter weight and higher current capacity. Then you get a better conductor with less power loss, which in turn increases the efficiency and performance of the device. Improved performance, for instance, means we can reduce volume and increase the power density in advanced motor systems.”
The work builds on a rich history of superconductivity research at ORNL, which has produced superior materials to conduct electricity with low resistance. The lab’s superconductive wire technology was licensed to several industry suppliers, enabling such uses as high-capacity electric transmission with minimal power losses.
While the new composite breakthrough has direct implications for electric motors, it also could improve electrification in applications where efficiency, mass and size are a key metric, Aytug said. The improved performance characteristics, accomplished with commercially viable techniques, means new possibilities for designing advanced conductors for a broad range of electrical systems and industrial applications, he said.
The ORNL team also is exploring the use of double-wall CNTs and other deposition techniques such as ultrasonic spray coating coupled with a roll-to-roll system to produce samples of some 1 meter in length.
“Electric motors are basically a combination of metals — steel laminations and copper windings,” noted Burak Ozpineci, manager of the ORNL Electric Drive Technologies Program and leader of the Power Electronics and Electric Machinery group. “To meet DOE’s Vehicle Technologies Office’s 2025 electric vehicle targets and goals, we need to increase power density of the electric drive and reduce the volume of motors by 8 times, and that means improving material properties.”
Other ORNL scientists on the project were Michael McGuire, Andrew Lupini, Lydia Skolrood, Fred List and Soydan Ozcan. The work was funded by DOE’s Office of Energy Efficiency and Renewable Energy, Vehicle Technologies Office. More

Tiny magnetic whirls that can occur in materials — so-called skyrmions — hold high promises for novel electronic devices or magnetic memory in which they are used as bits to store information. A fundamental prerequisite for any application is the stability of these magnetic whirls. A research team of the Institute of Theoretical Physics and Astrophysics of Kiel University has now demonstrated that so far neglected magnetic interactions can play a key role for skyrmion stability and can drastically enhance skyrmion lifetime. Their work, which has been published today (September 21, 2020) in Nature Communications, opens also the perspective to stabilize skyrmions in new material systems in which the previously considered mechanisms are not sufficient.
Intensive research on stability at room temperature
Their unique magnetic structure — more precisely their topology — lends stability to skyrmions and protects them from collapse. Therefore, skyrmions are denoted as knots in the magnetization. However, on the atomic lattice of a solid this protection is imperfect and there is only a finite energy barrier. “The situation is comparable to a marble lying in a trough which thus needs a certain impetus, energy, to escape from it. The larger the energy barrier, the higher is the temperature at which the skyrmion is stable,” explains Professor Stefan Heinze from Kiel University. Especially skyrmions with diameters below 10 nanometers, which are needed for future spinelectronic devices, have so far only been detected at very low temperatures. Since applications are typically at room temperature the enhancement of the energy barrier is a key objective in today’s research on skyrmions.
Previously, a standard model of the relevant magnetic interactions contributing to the barrier has been established. A team of theoretical physicists from the research group of Professor Stefan Heinze has now demonstrated that one type of magnetic interactions has so far been overlooked. In the 1920s Werner Heisenberg could explain the occurrence of ferromagnetism by the quantum mechanical exchange interaction which results from the spin dependent “hopping” of electrons between two atoms. “If one considers the electron hopping between more atoms, higher-order exchange interactions occur,” says Dr. Souvik Paul, first author of the study. However, these interactions are much weaker than the pair-wise exchange proposed by Heisenberg and were thus neglected in the research on skyrmions.
Weak higher-order exchange interactions stabilize skyrmions
Based on atomistic simulations and quantum mechanical calculations performed on the super computers of the North-German Supercomputing Alliance (HLRN) the scientists from Kiel have now explained that these weak interactions can still provide a surprisingly large contribution to skyrmion stability. Especially the cyclic hopping over four atomic sites influences the energy of the transition state extraordinarily strongly, where only a few atomic bar magnets are tilted against each other. Even stable antiskyrmions were found in the simulations which are advantageous for some future data storage concepts but typically decay too fast.
Higher-order exchange interactions appear in many magnetic materials used for potential skyrmion applications such as cobalt or iron. They can also stabilize skyrmions in magnetic structures in which the previously considered magnetic interactions cannot occur or are too small. Therefore, the present study opens new promising routes for the research on these fascinating magnetic knots.

Story Source:
Materials provided by Kiel University. Note: Content may be edited for style and length. More

An international research team has developed “electronic skin” sensors capable of mimicking the dynamic process of human motion. This work could help severely injured people, such as soldiers, regain the ability to control their movements, as well as contribute to the development of smart robotics, according to Huanyu “Larry” Cheng, Dorothy Quiggle Early Career Professor in the Penn State Department of Engineering Science and Mechanics.
Cheng and collaborating researchers based in China published their work in a recent issue of Nano Energy.
“The skin of the human hand is amazing — that’s what we tried to imitate,” Cheng said. “How do we capture texture and force? What about the years of evolution that produced the impressive sensitivity of the fingertip? We’re attempting to reproduce this biological and dynamic process to enable objects to behave similarly to the human hand.”
The dual-mode sensor measures both the magnitude and load of movement, such as the effort of swinging a tennis racquet, as well as rate, duration and direction. The trick was to decouple this measurement and understand how the separate parameters influence each other.
For example, bouncing a tennis ball gently on a racquet requires different input than serving a ball to an opponent. Those same variables come into play when a person with a prosthetic arm needs to differentiate between handling an egg or carrying a watermelon.
“We can apply these sensors to help people capture the magnitude for pressing, bending and more,” Cheng said. “We can also use these sensors on soft robotics to manipulate delicate objects, like catching a fish, or even in a disaster when they may need to crawl into irregular spaces and move debris.”
The data is informed by synergy created between the piezoelectric and piezoresistive signals, according to Cheng. Piezoelectric signals measure outside force — such as pressure — to create electrical charge, while piezoresistive signals mitigate the current.?The dual mode sensors are sandwiched together, with two internal layers of pyramid-shaped microstructures facing one another. The microstructures measure magnitude and duration measurements from the piezoresistive layer and the dynamic loading rate and direction from the piezoelectric layer. This synergistic effect allows for a high sensitivity over a broad pressure and frequency range, meaning that researchers can precisely measure the force and flexibility needed to imitate specific movements.
“We combined the best of the best models and sensors to create something new,” Cheng said.

Story Source:
Materials provided by Penn State. Original written by Ashley J. WennersHerron. Note: Content may be edited for style and length. More

An international team of researchers has now found that computerised training can support preterm children’s academic success. In their randomised controlled study “Fit for School,” the researchers compared two learning apps. The project at the University Hospital Essen and at Ruhr-Universität Bochum was funded by Mercator Research Center Ruhr (Mercur) with approximately 300,000 Euros for four years. Results have been published online as unedited manuscript in the journal Pediatric Research on 12 September 2020.
Every 11. baby is born too early in Germany, over 15 million globally each year. Although survival rates have increased, long-term development has not improved much. At school age, children born preterm often struggle with attention and complex tasks, such as math.
“Preemies need special support,” says neonatologist Dr. Britta Hüning of the Clinic for Pediatrics I, University Hospital Essen. Together with psychologist Dr. Julia Jaekel from the University of Tennessee Knoxville, previously at Ruhr-Universität Bochum, she was part of a multidisciplinary team that led the study with Professor Ursula Felderhoff-Müser, Director of the Clinic for Pediatrics I. Their findings are promising and novel, as few intervention studies have ever shown academic improvements for school-aged preterm children.
Two learning apps tested
The study included 65 first graders, born between five and twelve weeks preterm in the Ruhr Region. They practiced daily for five weeks, using the software app Xtramath or Cogmed. Teachers rated their academic progress in math, attention, reading and writing through first and second grade.
The final results: parents and children liked both apps. “The different trainings supported long-term school success to a similar degree,” says Julia Jaekel. “However, Xtramath received more positive ratings and led to better short-term academic progress.”
In times of increasing remote and online instruction for all children, apps with documented effectiveness are scarce. Parents and teachers may turn to adaptive apps such as Xtramath for learning at home.

Story Source:
Materials provided by Ruhr-University Bochum. Note: Content may be edited for style and length. More

Researchers at the University of Helsinki have developed a technique in which a computer models visual perception by monitoring human brain signals. In a way, it is as if the computer tries to imagine what a human is thinking about. As a result of this imagining, the computer is able to produce entirely new information, such as fictional images that were never before seen.
The technique is based on a novel brain-computer interface. Previously, similar brain-computer interfaces have been able to perform one-way communication from brain to computer, such as spell individual letters or move a cursor.
As far as is known, the new study is the first where both the computer’s presentation of the information and brain signals were modelled simultaneously using artificial intelligence methods. Images that matched the visual characteristics that participants were focusing on were generated through interaction between human brain responses and a generative neural network.
The study was published in the Scientific Reports journal in September. Scientific Reports is an online multidisciplinary, open-access journal from the publishers of Nature.
Neuroadaptive generative modelling
The researchers call this method neuroadaptive generative modelling. A total of 31 volunteers participated in a study that evaluated the effectiveness of the technique. Participants were shown hundreds of AI-generated images of diverse-looking people while their EEG was recorded.

advertisement

The subjects were asked to concentrate on certain features, such as faces that looked old or were smiling. While looking at a rapidly presented series of face images, the EEGs of the subjects were fed to a neural network, which inferred whether any image was detected by the brain as matching what the subjects were looking for.
Based on this information, the neural network adapted its estimation as to what kind of faces people were thinking of. Finally, the images generated by the computer were evaluated by the participants and they nearly perfectly matched with the features the participants were thinking of. The accuracy of the experiment was 83 per cent.
“The technique combines natural human responses with the computer’s ability to create new information. In the experiment, the participants were only asked to look at the computer-generated images. The computer, in turn, modelled the images displayed and the human reaction toward the images by using human brain responses. From this, the computer can create an entirely new image that matches the user’s intention,” says Tuukka Ruotsalo, Academy of Finland Research Fellow at the University of Helsinki, Finland and Associate Professor at the University of Copenhagen, Denmark.
Unconscious attitudes may be exposed
Generating images of the human face is only one example of the technique’s potential uses. One practical benefit of the study may be that computers can augment human creativity.
“If you want to draw or illustrate something but are unable to do so, the computer may help you to achieve your goal. It could just observe the focus of attention and predict what you would like to create,” Ruotsalo says. However, the researchers believe that the technique may be used to gain understanding of perception and the underlying processes in our mind.
“The technique does not recognise thoughts but rather responds to the associations we have with mental categories. Thus, while we are not able to find out the identity of a specific ‘old person’ a participant was thinking of, we may gain an understanding of what they associate with old age. We, therefore, believe it may provide a new way of gaining insight into social, cognitive and emotional processes,” says Senior Researcher Michiel Spapé.
According to Spapé, this is also interesting from a psychological perspective.
“One person’s idea of an elderly person may be very different from another’s. We are currently uncovering whether our technique might expose unconscious associations, for example by looking if the computer always renders old people as, say, smiling men.”

Story Source:
Materials provided by University of Helsinki. Original written by Aino Pekkarinen. Note: Content may be edited for style and length. More

Physicists from Lancaster University have established why objects moving through superfluid helium-3 lack a speed limit in a continuation of earlier Lancaster research.
Helium-3 is a rare isotope of helium, in which one neutron is missing. It becomes superfluid at extremely low temperatures, enabling unusual properties such as a lack of friction for moving objects.
It was thought that the speed of objects moving through superfluid helium-3 was fundamentally limited to the critical Landau velocity, and that exceeding this speed limit would destroy the superfluid. Prior experiments in Lancaster have found that it is not a strict rule and objects can move at much greater speeds without destroying the fragile superfluid state.
Now scientists from Lancaster University have found the reason for the absence of the speed limit: exotic particles that stick to all surfaces in the superfluid.
The discovery may guide applications in quantum technology, even quantum computing, where multiple research groups already aim to make use of these unusual particles.
To shake the bound particles into sight, the researchers cooled superfluid helium-3 to within one ten thousandth of a degree from absolute zero (0.0001K or -273.15°C). They then moved a wire through the superfluid at a high speed, and measured how much force was needed to move the wire. Apart from an extremely small force related to moving the bound particles around when the wire starts to move, the measured force was zero.
Lead author Dr Samuli Autti said: “Superfluid helium-3 feels like vacuum to a rod moving through it, although it is a relatively dense liquid. There is no resistance, none at all. I find this very intriguing.”
PhD student Ash Jennings added: “By making the rod change its direction of motion we were able to conclude that the rod will be hidden from the superfluid by the bound particles covering it, even when its speed is very high.” “The bound particles initially need to move around to achieve this, and that exerts a tiny force on the rod, but once this is done, the force just completely disappears,” said Dr Dmitry Zmeev, who supervised the project.
The Lancaster researchers included Samuli Autti, Sean Ahlstrom, Richard Haley, Ash Jennings, George Pickett, Malcolm Poole, Roch Schanen, Viktor Tsepelin, Jakub Vonka, Tom Wilcox, Andrew Woods and Dmitry Zmeev. The results are published in Nature Communications.

Story Source:
Materials provided by Lancaster University. Note: Content may be edited for style and length. More

As our lives become increasingly intertwined with technology — whether supporting communication while working remotely or streaming our favorite show — so too does our reliance on the data these devices create. Data centers supporting these technology ecosystems produce a significant carbon footprint — and consume 200 terawatt hours of energy each year, greater than the annual energy consumption of Iran. To balance ecological concerns yet meet growing demand, advances in microelectronic processors — the backbone of many Internet of Things (IoT) devices and data hubs — must be efficient and environmentally friendly.
Northwestern University materials scientists have developed new design principles that could help spur development of future quantum materials used to advance (IoT) devices and other resource-intensive technologies while limiting ecological damage.
“New path-breaking materials and computing paradigms are required to make data centers more energy-lean in the future,” said James Rondinelli, professor of materials science and engineering and the Morris E. Fine Professor in Materials and Manufacturing at the McCormick School of Engineering, who led the research.
The study marks an important step in Rondinelli’s efforts to create new materials that are non-volatile, energy efficient, and generate less heat — important aspects of future ultrafast, low-power electronics and quantum computers that can help meet the world’s growing demand for data.
Rather than certain classes of semiconductors using the electron’s charge in transistors to power computing, solid-state spin-based materials utilize the electron’s spin and have the potential to support low-energy memory devices. In particular, materials with a high-quality persistent spin texture (PST) can exhibit a long-lived persistent spin helix (PSH), which can be used to track or control the spin-based information in a transistor.
Although many spin-based materials already encode information using spins, that information can be corrupted as the spins propagate in the active portion of the transistor. The researchers’ novel PST protects that spin information in helix form, making it a potential platform where ultralow energy and ultrafast spin-based logic and memory devices operate.
The research team used quantum-mechanical models and computational methods to develop a framework to identify and assess the spin textures in a group of non-centrosymmetric crystalline materials. The ability to control and optimize the spin lifetimes and transport properties in these materials is vital to realizing the future of quantum microelectronic devices that operate with low energy consumption.
“The limiting characteristic of spin-based computing is the difficulty in attaining both long-lived and fully controllable spins from conventional semiconductor and magnetic materials,” Rondinelli said. “Our study will help future theoretical and experimental efforts aimed at controlling spins in otherwise non-magnetic materials to meet future scaling and economic demands.”
Rondinelli’s framework used microscopic effective models and group theory to identify three materials design criteria that would produce useful spin textures: carrier density, the number of electrons propagating through an effective magnetic field, Rashba anisotropy, the ratio between intrinsic spin-orbit coupling parameters of the materials, and momentum space occupation, the PST region active in the electronic band structure. These features were then assessed using quantum-mechanical simulations to discover high-performing PSHs in a range of oxide-based materials.
The researchers used these principles and numerical solutions to a series of differential spin-diffusion equations to assess the spin texture of each material and predict the spin lifetimes for the helix in the strong spin-orbit coupling limit. They also found they could adjust and improve the PST performance using atomic distortions at the picoscale. The group determined an optimal PST material, Sr3Hf2O7, which showed a substantially longer spin lifetime for the helix than in any previously reported material.
“Our approach provides a unique chemistry-agnostic strategy to discover, identify, and assess symmetry-protected persistent spin textures in quantum materials using intrinsic and extrinsic criteria,” Rondinelli said. “We proposed a way to expand the number of space groups hosting a PST, which may serve as a reservoir from which to design future PST materials, and found yet another use for ferroelectric oxides — compounds with a spontaneous electrical polarization. Our work also will help guide experimental efforts aimed at implementing the materials in real device structures.”

Story Source:
Materials provided by Northwestern University. Original written by Alex Gerage. Note: Content may be edited for style and length. More

Solar storm analysis carried out by an army of citizen scientists has helped researchers devise a new and more accurate way of forecasting when Earth will be hit by harmful space weather. Scientists at the University of Reading added analysis carried out by members of the public to computer models designed to predict when coronal mass ejections (CMEs) — huge solar eruptions that are harmful to satellites and astronauts — will arrive at Earth.
The team found forecasts were 20% more accurate, and uncertainty was reduced by 15%, when incorporating information about the size and shape of the CMEs in the volunteer analysis. The data was captured by thousands of members of the public during the latest activity in the Solar Stormwatch citizen science project, which was devised by Reading researchers and has been running since 2010.
The findings support the inclusion of wide-field CME imaging cameras on board space weather monitoring missions currently being planned by agencies like NASA and ESA.
Dr Luke Barnard, space weather researcher at the University of Reading’s Department of Meteorology, who led the study, said: “CMEs are sausage-shaped blobs made up of billions of tonnes of magnetised plasma that erupt from the Sun’s atmosphere at a million miles an hour. They are capable of damaging satellites, overloading power grids and exposing astronauts to harmful radiation.
“Predicting when they are on a collision course with Earth is therefore extremely important, but is made difficult by the fact the speed and direction of CMEs vary wildly and are affected by solar wind, and they constantly change shape as they travel through space.
“Solar storm forecasts are currently based on observations of CMEs as soon as they leave the Sun’s surface, meaning they come with a large degree of uncertainty. The volunteer data offered a second stage of observations at a point when the CME was more established, which gave a better idea of its shape and trajectory.

advertisement

“The value of additional CME observations demonstrates how useful it would be to include cameras on board spacecraft in future space weather monitoring missions. More accurate predictions could help prevent catastrophic damage to our infrastructure and could even save lives.”
In the study, published in AGU Advances, the scientists used a brand new solar wind model, developed by Reading co-author Professor Mathew Owens, for the first time to create CME forecasts.
The simplified model is able to run up to 200 simulations — compared to around 20 currently used by more complex models — to provide improved estimates of the solar wind speed and its impact on the movement of CMEs, the most harmful of which can reach Earth in 15-18 hours.
Adding the public CME observations to the model’s predictions helped provide a clearer picture of the likely path the CME would take through space, reducing the uncertainty in the forecast. The new method could also be applied to other solar wind models.
The Solar Stormwatch project was led by Reading co-author Professor Chris Scott. It asked volunteers to trace the outline of thousands of past CMEs captured by Heliospheric Imagers — specialist, wide-angle cameras — on board two NASA STEREO spacecraft, which orbit the Sun and monitor the space between it and Earth.
The scientists retrospectively applied their new forecasting method to the same CMEs the volunteers had analysed to test how much more accurate their forecasts were with the additional observations.
Using the new method for future solar storm forecasts would require swift real-time analysis of the images captured by the spacecraft camera, which would provide warning of a CME being on course for Earth several hours or even days in advance of its arrival.

Story Source:
Materials provided by University of Reading. Note: Content may be edited for style and length. More