Computers Math

New research from the University of Surrey has shown that silicon could be one of the most powerful materials for photonic informational manipulation — opening up new possibilities for the production of lasers and displays.
While computer chips’ extraordinary success has confirmed silicon as the prime material for electronic information control, silicon has a reputation as a poor choice for photonics; there are no commercially available silicon light-emitting diodes, lasers or displays.
Now, in a paper published by Light: Science and Applications journal, a Surrey-led international team of scientists has shown that silicon is an outstanding candidate for creating a device that can control multiple light beams.
The discovery means that it is now possible to produce silicon processors with built-in abilities for light beams to control other beams — boosting the speed and efficiency of electronic communications.
This is possible thanks to the wavelength band called the far-infrared or terahertz region of the electromagnetic spectrum. The effect works with a property called a nonlinearity, which is used to manipulate laser beams — for example, changing their colour. Green laser pointers work this way: they take the output from a very cheap and efficient but invisible infrared laser diode and change the colour to green with a nonlinear crystal that halves the wavelength.
Other kinds of nonlinearity can produce an output beam with a third of the wavelength or be used to redirect a laser beam to control the direction of the beam’s information. The stronger the nonlinearity, the easier it is to control with weaker input beams.
The researchers found that silicon possesses the strongest nonlinearity of this type ever discovered. Although the study was carried out with the crystal being cooled to very low cryogenic temperatures, such strong nonlinearities mean that extremely weak beams can be used.
Ben Murdin, co-author of the study and Professor of Physics at the University of Surrey, said: “Our finding was lucky because we weren’t looking for it. We were trying to understand how a very small number of phosphorus atoms in a silicon crystal could be used for making a quantum computer and how to use light beams to control quantum information stored in the phosphorus atoms.
“We were astonished to find that the phosphorus atoms were re-emitting light beams that were almost as bright as the very intense laser we were shining on them. We shelved the data for a couple of years while we thought about proving where the beams were coming from. It’s a great example of the way science proceeds by accident, and also how pan-European teams can still work together very effectively.”
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If a base station in a local area network tries to use a directional beam to transmit a signal to a user trying to connect to the network — instead of using a wide area network broadcast, as base stations commonly do — how does it know which direction to send the beam?
Researchers from Rice University and Brown University developed a link discovery method in 2020 using terahertz radiation, with high-frequency waves above 100 gigahertz. For this work, they deferred the question of what would happen if a wall or other reflector nearby creates a non-line-of-sight (NLOS) path from the base station to the receiver and focused on the simpler situation where the only existing path was along the line-of-sight (LOS).
In APL Photonics, from AIP Publishing, those same researchers address this question by considering two different generic types of transmitters and exploring how their characteristics can be used to determine whether an NLOS path contributes to the signal received by the receiver.
“One type of transmitter sends all frequencies more or less in the same direction,” said Daniel Mittleman, co-author and an engineering professor at Brown, “while the other type sends different frequencies in different directions, exhibiting strong angular dispersion. The situation is quite different in these two different cases.”
The researchers’ work shows that the transmitter sending different frequencies in different directions has distinct advantages in its ability to detect the NLOS path and distinguish them from the LOS path.
“A well-designed receiver would be able to detect both frequencies and use their properties to recognize the two paths and tell them apart,” Mittleman said.
Many recent reports within academic literature have focused on various challenges involved in using terahertz signals for wireless communications. Indeed, the term 6G has become a buzzword to encompass future generations of wireless systems that use these ultrahigh-frequency signals.
“For terahertz signals to be used for wireless communications, many challenges must be overcome, and one of the biggest is how to detect and exploit NLOS paths,” said Mittleman.
This work is among the first to provide a quantitative consideration of how to detect and exploit NLOS paths, as well as a comparison of the behavior of different transmitters within this context.
“For most realistic indoor scenarios we can envision for an above-100 gigahertz wireless network, the issue of NLOS path is definitely going to require careful consideration,” said Mittleman. “We need to know how to exploit these link opportunities to maintain connectivity.”
If, for example, the LOS path is blocked by something, an NLOS path can be used to maintain the link between the base station and receiver.
“Interestingly, with a transmitter creating strong angular dispersion, sometimes an NLOS link can provide even faster connectivity than the LOS link,” said Yasaman Ghasempour, co-author and assistant professor at Rice University. “But you can’t take advantage of such opportunities if you don’t know the NLOS path exists or how to find it.”
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An international team with researchers from the University of Bayreuth has succeeded for the first time in discovering a previously unknown two-dimensional material by using modern high-pressure technology. The new material, beryllonitrene, consists of regularly arranged nitrogen and beryllium atoms. It has an unusual electronic lattice structure that shows great potential for applications in quantum technology. Its synthesis required a compression pressure that is about one million times higher than the pressure of the Earth’s atmosphere. The scientists have presented their discovery in the journal Physical Review Letters.
Since the discovery of graphene, which is made of carbon atoms, interest in two-dimensional materials has grown steadily in research and industry. Under extremely high pressures of up to 100 gigapascals, researchers from the University of Bayreuth, together with international partners, have now produced novel compounds composed of nitrogen and beryllium atoms. These are beryllium polynitrides, some of which conform to the monoclinic, others to the triclinic crystal system. The triclinic beryllium polynitrides exhibit one unusual characteristic when the pressure drops. They take on a crystal structure made up of layers. Each layer contains zigzag nitrogen chains connected by beryllium atoms. It can therefore be described as a planar structure consisting of BeN? pentagons and Be?N? hexagons. Thus, each layer represents a two-dimensional material, beryllonitrene.
Qualitatively, beryllonitrene is a new 2D material. Unlike graphene, the two-dimensional crystal structure of beryllonitrene results in a slightly distorted electronic lattice. Because of its resulting electronic properties, beryllonitrene would be excellently suited for applications in quantum technology if it could one day be produced on an industrial scale. In this still young field of research and development, the aim is to use the quantum mechanical properties and structures of matter for technical innovations — for example, for the construction of high-performance computers or for novel encryption techniques with the goal of secure communication.
“For the first time, close international cooperation in high-pressure research has now succeeded in producing a chemical compound in that was previously completely unknown. This compound could serve as a precursor for a 2D material with unique electronic properties. The fascinating achievement was only possible with the help of a laboratory-generated compression pressure almost a million times greater than the pressure of the Earth’s atmosphere. Our study thus once again proves the extraordinary potential of high-pressure research in materials science,” says co-author Prof. Dr. Natalia Dubrovinskaia from the Laboratory for Crystallography at the University of Bayreuth. “However, there is no possibility of devising a process for the production of beryllonitrene on an industrial scale as long as extremely high pressures, such as can only be generated in the research laboratory, are required for this. Nevertheless, it is highly significant that the new compound was created during decompression and that it can exist under ambient conditions. In principle, we cannot rule out that one day it will be possible to reproduce beryllonitrene or a similar 2D material with technically less complex processes and use it industrially. With our study, we have opened up new prospects for high-pressure research in the development of technologically promising 2D materials that may surpass graphene,” says corresponding author Prof. Dr. Leonid Dubrovinsky from the Bavarian Research Institute of Experimental Geochemistry & Geophysics at the University of Bayreuth.
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University of South Australia researchers have drawn inspiration from a 300-million-year-old superior flying machine — the dragonfly — to show why future flapping wing drones will probably resemble the insect in shape, wings and gearing.
A team of PhD students led by UniSA Professor of Sensor Systems, Javaan Chahl, spent part of the 2020 COVID-19 lockdown designing and testing key parts of a dragonfly-inspired drone that might match the insect’s extraordinary skills in hovering, cruising and aerobatics.
The UniSA students worked remotely on the project, solving mathematical formulas at home on whiteboards, digitising stereo photographs of insect wings into 3D models, and using spare rooms as rapid prototyping workshops to test parts of the flapping wing drone.
Their findings have been published in the journal Drones.
Describing the dragonfly as the “apex insect flyer,” Prof Chahl says numerous engineering lessons can be learned from its mastery in the air.
“Dragonflies are supremely efficient in all areas of flying. They need to be. After emerging from under water until their death (up to six months), male dragonflies are involved in perpetual, dangerous combat against male rivals. Mating requires an aerial pursuit of females and they are constantly avoiding predators. Their flying abilities have evolved over millions of years to ensure they survive,” Prof Chahl says. More

Engineers at Duke University have developed the world’s first fully recyclable printed electronics. By demonstrating a crucial and relatively complex computer component — the transistor — created with three carbon-based inks, the researchers hope to inspire a new generation of recyclable electronics to help fight the growing global epidemic of electronic waste.
The work appears online April 26 in the journal Nature Electronics.
“Silicon-based computer components are probably never going away, and we don’t expect easily recyclable electronics like ours to replace the technology and devices that are already widely used,” said Aaron Franklin, the Addy Professor of Electrical and Computer Engineering at Duke. “But we hope that by creating new, fully recyclable, easily printed electronics and showing what they can do, that they might become widely used in future applications.”
As people worldwide adopt more electronics into their lives, there’s an ever-growing pile of discarded devices that either don’t work anymore or have been cast away in favor of a newer model. According to a United Nations estimate, less than a quarter of the millions of pounds of electronics thrown away each year is recycled. And the problem is only going to get worse as the world upgrades to 5G devices and the Internet of Things (IoT) continues to expand.
Part of the problem is that electronic devices are difficult to recycle. Large plants employ hundreds of workers who hack at bulky devices. But while scraps of copper, aluminum and steel can be recycled, the silicon chips at the heart of the devices cannot.
In the new study, Franklin and his laboratory demonstrate a completely recyclable, fully functional transistor made out of three carbon-based inks that can be easily printed onto paper or other flexible, environmentally friendly surfaces. Carbon nanotubes and graphene inks are used for the semiconductors and conductors, respectively. While these materials are not new to the world of printed electronics, Franklin says, the path to recyclability was opened with the development of a wood-derived insulating dielectric ink called nanocellulose.
“Nanocellulose is biodegradable and has been used in applications like packaging for years,” said Franklin. “And while people have long known about its potential applications as an insulator in electronics, nobody has figured out how to use it in a printable ink before. That’s one of the keys to making these fully recyclable devices functional.”
The researchers developed a method for suspending crystals of nanocellulose that were extracted from wood fibers that — with the sprinkling of a little table salt — yields an ink that performs admirably as an insulator in their printed transistors. Using the three inks in an aerosol jet printer at room temperature, the team shows that their all-carbon transistors perform well enough for use in a wide variety of applications, even six months after the initial printing.
The team then demonstrates just how recyclable their design is. By submerging their devices in a series of baths, gently vibrating them with sound waves and centrifuging the resulting solution, the carbon nanotubes and graphene are sequentially recovered with an average yield of nearly 100%. Both materials can then be reused in the same printing process while losing very little of their performance viability. And because the nanocellulose is made from wood, it can simply be recycled along with the paper it was printed on.
Compared to a resistor or capacitor, a transistor is a relatively complex computer component used in devices such as power control or logic circuits and various sensors. Franklin explains that, by demonstrating a fully recyclable, multifunctional printed transistor first, he hopes to make a first step toward the technology being commercially pursued for simple devices. For example, Franklin says he could imagine the technology being used in a large building needing thousands of simple environmental sensors to monitor its energy use or customized biosensing patches for tracking medical conditions.
“Recyclable electronics like this aren’t going to go out and replace an entire half-trillion-dollar industry by any means, and we’re certainly nowhere near printing recyclable computer processors,” said Franklin. “But demonstrating these types of new materials and their functionality is hopefully a stepping stone in the right direction for a new type of electronics lifecycle.”
This work was supported by the Department of Defense Congressionally Directed Medical Research Program (W81XWH-17-2-0045), the National Institutes of Health (1R01HL146849) and the Air Force Office of Scientific Research (FA9550-18-1-0222).
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Anyone with children knows that while controlling one child can be hard, controlling many at once can be nearly impossible. Getting swarms of robots to work collectively can be equally challenging, unless researchers carefully choreograph their interactions — like planes in formation — using increasingly sophisticated components and algorithms. But what can be reliably accomplished when the robots on hand are simple, inconsistent, and lack sophisticated programming for coordinated behavior?
A team of researchers led by Dana Randall, ADVANCE Professor of Computing and Daniel Goldman, Dunn Family Professor of Physics, both at Georgia Institute of Technology, sought to show that even the simplest of robots can still accomplish tasks well beyond the capabilities of one, or even a few, of them. The goal of accomplishing these tasks with what the team dubbed “dumb robots” (essentially mobile granular particles) exceeded their expectations, and the researchers report being able to remove all sensors, communication, memory and computation — and instead accomplishing a set of tasks through leveraging the robots’ physical characteristics, a trait that the team terms “task embodiment.”
The team’s BOBbots, or “behaving, organizing, buzzing bots” that were named for granular physics pioneer Bob Behringer, are “about as dumb as they get,” explains Randall. “Their cylindrical chassis have vibrating brushes underneath and loose magnets on their periphery, causing them to spend more time at locations with more neighbors.” The experimental platform was supplemented by precise computer simulations led by Georgia Tech physics student Shengkai Li, as a way to study aspects of the system inconvenient to study in the lab.
Despite the simplicity of the BOBbots, the researchers discovered that, as the robots move and bump into each other, “compact aggregates form that are capable of collectively clearing debris that is too heavy for one alone to move,” according to Goldman. “While most people build increasingly complex and expensive robots to guarantee coordination, we wanted to see what complex tasks could be accomplished with very simple robots.”
Their work, as reported April 23, 2021 in the journal Science Advances, was inspired by a theoretical model of particles moving around on a chessboard. A theoretical abstraction known as a self-organizing particle system was developed to rigorously study a mathematical model of the BOBbots. Using ideas from probability theory, statistical physics and stochastic algorithms, the researchers were able to prove that the theoretical model undergoes a phase change as the magnetic interactions increase — abruptly changing from dispersed to aggregating in large, compact clusters, similar to phase changes we see in common everyday systems, like water and ice.
“The rigorous analysis not only showed us how to build the BOBbots, but also revealed an inherent robustness of our algorithm that allowed some of the robots to be faulty or unpredictable,” notes Randall, who also serves as a professor of computer science and adjunct professor of mathematics at Georgia Tech.
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Scientists from the Theory Department of the Fritz-Haber Institute in Berlin and Technical University of Munich use machine learning to discover suitable molecular materials. To deal with the myriad of possibilities for candidate molecules, the machine decides for itself which data it needs.
How can I prepare myself for something I do not yet know? Scientists from the Fritz Haber Institute in Berlin and from the Technical University of Munich have addressed this almost philosophical question in the context of machine learning. Learning is no more than drawing on prior experience. In order to deal with a new situation, one needs to have dealt with roughly similar situations before. In machine learning, this correspondingly means that a learning algorithm needs to have been exposed to roughly similar data. But what can we do if there is a nearly infinite amount of possibilities so that it is simply impossible to generate data that covers all situations?
This problem comes up a lot when dealing with an endless number of possible candidate molecules. Organic semiconductors enable important future technologies such as portable solar cells or rollable displays. For such applications, improved organic molecules — which make up these materials — need to be discovered. Tasks of this nature are increasingly using methods of machine learning, while training on data from computer simulations or experiments. The number of potentially possible small organic molecules is, however, estimated to be on the order of 1033. This overwhelming number of possibilities makes it practically impossible to generate enough data to reflect such a large material diversity. In addition, many of those molecules are not even suitable for organic semiconductors. One is essentially looking for the proverbial needle in a haystack.
In their work published recently in Nature Communications the team around Prof. Karsten Reuter, Director of the Theory Department at the Fritz-Haber-Institute, addressed this problem using so-called active learning. Instead of learning from existing data, the machine learning algorithm iteratively decides for itself which data it actually needs to learn about the problem. The scientists first carry out simulations on a few smaller molecules, and obtain data related to the molecules’ electrical conductivity — a measure of their usefulness when looking at possible solar cell materials. Based on this data, the algorithm decides if small modifications to these molecules could already lead to useful properties or whether it is uncertain due to a lack of similar data. In both cases, it automatically requests new simulations, improves itself through the newly generated data, considers new molecules, and goes on to repeat this procedure. In their work, the scientists show how new and promising molecules can efficiently be identified this way, while the algorithm continues its exploration into the vast molecular space, even now, at this very moment. Every week new molecules are being proposed that could usher in the next generation of solar cells and the algorithm just keeps getting better and better.
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Being unable to walk quickly can be frustrating and problematic, but it is a common issue, especially as people age. Noting the pervasiveness of slower-than-desired walking, engineers at Stanford University have tested how well a prototype exoskeleton system they have developed — which attaches around the shin and into a running shoe — increased the self-selected walking speed of people in an experimental setting.
The exoskeleton is externally powered by motors and controlled by an algorithm. When the researchers optimized it for speed, participants walked, on average, 42 percent faster than when they were wearing normal shoes and no exoskeleton. The results of this study were published April 20 in IEEE Transactions on Neural Systems and Rehabilitation Engineering.
“We were hoping that we could increase walking speed with exoskeleton assistance, but we were really surprised to find such a large improvement,” said Steve Collins, associate professor of mechanical engineering at Stanford and senior author of the paper. “Forty percent is huge.”
For this initial set of experiments, the participants were young, healthy adults. Given their impressive results, the researchers plan to run future tests with older adults and to look at other ways the exoskeleton design can be improved. They also hope to eventually create an exoskeleton that can work outside the lab, though that goal is still a ways off.
“My research mission is to understand the science of biomechanics and motor control behind human locomotion and apply that to enhance the physical performance of humans in daily life,” said Seungmoon Song, a postdoctoral fellow in mechanical engineering and lead author of the paper. “I think exoskeletons are very promising tools that could achieve that enhancement in physical quality of life.”
Walking in the loop
The ankle exoskeleton system tested in this research is an experimental emulator that serves as a testbed for trying out different designs. It has a frame that fastens around the upper shin and into an integrated running shoe that the participant wears. It is attached to large motors that sit beside the walking surface and pull a tether that runs up the length of the back of the exoskeleton. Controlled by an algorithm, the tether tugs the wearer’s heel upward, helping them point their toe down as they push off the ground. More