Aurelia Butler

Researchers at the National Institute of Standards and Technology (NIST) have created grids of tiny clumps of atoms known as quantum dots and studied what happens when electrons dive into these archipelagos of atomic islands. Measuring the behavior of electrons in these relatively simple setups promises deep insights into how electrons behave in complex real-world materials and could help researchers engineer devices that make possible powerful quantum computers and other innovative technologies.
In work published in Nature Communications, the researchers made multiple 3-by-3 grids of precisely spaced quantum dots, each comprising one to three phosphorus atoms. Attached to the grids were electrical leads and other components that enabled electrons to flow through them. The grids provided playing fields in which electrons could behave in nearly ideal, textbook-like conditions, free of the confounding effects of real-world materials.
The researchers injected electrons into the grids and observed how they behaved as the researchers varied conditions such as the spacing between the dots. For grids in which the dots were close, the electrons tended to spread out and act like waves, essentially existing in several places at one time. When the dots were far apart, they would sometimes get trapped in individual dots, like electrons in materials with insulating properties.
Advanced versions of the grid would allow researchers to study the behavior of electrons in controllable environments with a level of detail that would be impossible for the world’s most powerful conventional computers to simulate accurately. It would open the door to full-fledged “analog quantum simulators” that unlock the secrets of exotic materials such as high-temperature superconductors. It could also provide hints about how to create materials, such as topological insulators, by controlling the geometry of the quantum dot array.
In related work just published in ACS Nano, the same NIST researchers improved their fabrication method so they can now reliably create an array of identical, equally spaced dots with exactly one atom each, leading to even more ideal environments necessary for a fully accurate quantum simulator. The researchers have set their sights on making such a simulator with a larger grid of quantum dots: A 5×5 array of dots can produce rich electron behavior that is impossible to simulate in even the most advanced supercomputers.
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A research team consisting of NIMS, Hokkaido University and Yamaguchi University has developed a method for easily synthesizing a self-healing polymer gel made of ultrahigh molecular weight (UHMW) polymers (polymers with a molecular weight greater than 106 g/mol) and non-volatile ionic liquids. This recyclable and self-healable polymer gel is compatible with circular economy principles. In addition, it may potentially be used as a durable, ionically conductive material for flexible IoT devices.
Self-healing polymeric materials are capable of spontaneously repairing damaged areas, thereby increasing their material lifetimes, thus being expected to promote a circular economy. Most reported self-healing polymeric materials in recent years has taken a chemical approach, in which functional groups capable of reversible dissociation and reformation (e.g., hydrogen bonding) were integrated into polymeric networks. However, this approach often requires precise synthetic techniques and complex manufacturing processes. On the other hand, an alternative physical approach (i.e., the use of physical entanglement of polymer chains) to synthesizing versatile polymeric materials with self-healing capabilities had rarely been explored.
This research team recently developed a technique for easily synthesizing UHMW gels composed of entangled UHMW polymers using ionic liquids. The mechanical properties of UHMW gels were found to be superior to those of conventional, chemically crosslinked gels. In addition, they can be recycled via thermal processing, and exhibit high self-healing capabilities at room temperature.
The use of the newly developed recyclable, self-healing, easy-to-synthesize UHMW gel material is expected to promote a circular economy. In addition, because this material is synthesized using non-volatile, flammable ionic liquids, it may be used as a safe, ionically conductive soft material in flexible electronics.
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Scientists used the Advanced Photon Source to watch a nonliving material mimic behavior associated with learning, paving the way for better artificial intelligence.
Scientists looking to create a new generation of supercomputers are looking for inspiration from the most complex and energy-efficient computer ever built: the human brain.
In some of their initial forays into making brain-inspired computers, researchers are looking at different nonbiological materials whose properties could be tailored to show evidence of learning-like behaviors. These materials could form the basis for hardware that could be paired with new software algorithms to enable more potent, useful and energy-efficient artificial intelligence (AI).
In a new study led by scientists from Purdue University, researchers have exposed oxygen deficient nickel oxide to brief electrical pulses and elicited two different electrical responses that are similar to learning. The result is an all-electrically-driven system that shows these learning behaviors, said Rutgers University professor Shriram Ramanathan. (Ramanathan was a professor at Purdue University at the time of this work.) The research team used the resources of the Advanced Photon Source (APS), a U.S. Department of Energy (DOE) Office of Science user facility at DOE’s Argonne National Laboratory.
The first response, habituation, occurs when the material “gets used to” being slightly zapped. The scientists noticed that although the material’s resistance increases after an initial jolt, it soon becomes accustomed to the electric stimulus. “Habituation is like what happens when you live near an airport,” said Fanny Rodolakis, a physicist and beamline scientist at the APS. “The day you move in, you think ‘what a racket,’ but eventually you hardly notice anymore.”
The other response shown by the material, sensitization, occurs when a larger dose of electricity is administered. “With a larger stimulus, the material’s response grows instead of diminishing over time,” Rodolakis said. “It’s akin to watching a scary movie, and then having someone say ‘boo!’ from behind a corner — you see it really jump.”
“Pretty much all living organisms demonstrate these two characteristics,” Ramanathan said. “They really are a foundational aspect of intelligence.” More

An artificial intelligence tool developed by researchers at UCL and Queen Mary University of London could help governments decide whether or not to bail out a bank in crisis by predicting if the intervention will save money for taxpayers in the long term.
The AI tool, described in a new paper in Nature Communications, assesses not only if a bailout is the best strategy for taxpayers, but also suggests how much should be invested in the bank, and which bank or banks should be bailed out at any given time.
The algorithm was tested by the authors using data from the European Banking Authority on a network of 35 European financial institutions judged to be the most important to the global financial system, but it can also be used and calibrated by national banks using detailed proprietary data unavailable to the public.
Dr Neofytos Rodosthenous (UCL Mathematics), corresponding author of the paper, said: “Government bank bailouts are complex decisions that have financial, social and political implications. We believe the AI approach we have developed can be an important tool for governments, helping officials assess specifically financial implications — this means checking if a bailout is in the best interest of taxpayers, or whether it would be better value for money to let the bank fail. Our techniques are freely available for banking authorities to use as tools in their decision-making process.”
Co-author Professor Vito Latora (Queen Mary University of London) added: “Governments and banking authorities can also use our approach to retrospectively review past crises and gain valuable learnings to inform future actions. One could, for example, review the UK government bailout of the Royal Bank of Scotland (RBS) during the financial crisis of 2007-9 and reflect on how this could potentially be improved (from a financial standpoint) in the future in order to primarily benefit taxpayers.”
In a bank bailout, a government investment in a bank increases the bank’s equity and reduces its risk of defaulting. This cost in the short term may be justified to the taxpayer if it leads to lower taxpayer losses in the long term — i.e., it prevents bank defaults that are more damaging to government finances. More

Sharing medical data between laboratories and medical experts is important for medical research. However, data sharing is often sufficiently complex and sometimes even impossible due to the strict data regulatory legislation in Europe. Researchers at the University of Jyväskylä Digital Health Intelligence Laboratory addressed the problem and developed an artificial neural network that creates synthetic x-ray images that can fool even medical experts.
A group of researchers from University of Jyväskylä’s AI Hub Central Finland project developed an AI based method to create synthetic knee x-ray images to replace or complement real x-ray images in knee osteoarthritis classification.
Researchers used synthetically generated X-ray images to complement a data set of real X-ray images from the osteoarthritis study. The authenticity of the images was then assessed together with specialists from the central Finland healthcare district.
Medical experts were asked to rate osteoarthritis severity without knowing that the data set included synthetic images. In the second phase, experts tried to identify authentic and synthetic images. The results showed that on average, it was improbable even for medical experts to distinguish between real and synthetic x-ray images.
“The use of synthetic data is not subject to the same data protection regulations as real data. Using synthetic data can facilitate collaboration between, for example, research groups, companies and educational institutions,” says Sami Äyrämö, Head of Digital Health Intelligence Laboratory at the University of Jyväskylä.
According to Äyrämö, the use of synthetic data also speeds up authorisation processes and thus, among other things, testing of new ideas. More

Femtosecond pulsed lasers — which emit light in ultrafast bursts lasting a millionth of a billionth of a second — are powerful tools used in a range of applications from medicine and manufacturing, to sensing and precision measurements of space and time. Today, these lasers are typically expensive table-top systems, which limits their use in applications that have size and power consumption restrictions.
An on-chip femtosecond pulse source would unlock new applications in quantum and optical computing, astronomy, optical communications and beyond. However, it’s been a challenge to integrate tunable and highly efficient pulsed lasers onto chips.
Now, researchers from the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS) have developed a high-performance, on-chip femtosecond pulse source using a tool that seems straight out of science fiction: a time lens.
The research is published in Nature.
“Pulsed lasers that produce high-intensity, short pulses consisting of many colors of light have remained large,” said Marko Lon?ar, the Tiantsai Lin Professor of Electrical Engineering at SEAS and senior author of the study. “To make these sources more practical, we decided to shrink a well-known approach, used to realize conventional — and large — femtosecond sources, leveraging a state of the art integrated photonics platform that we have developed. Importantly, our chips are made using microfabrication techniques like those used to make computer chips, which ensures not only reduced cost and size, but also improved performance and reliability of our femtosecond sources.”
Traditional lenses, like contact lenses or those found in magnifying glasses and microscopes, bend rays of light coming from different directions by altering their phase so that they hit the same location in space — the focal point. More

Researchers at Purdue University have discovered new waves with picometer-scale spatial variations of electromagnetic fields which can propagate in semiconductors like silicon. The research team, led by Dr. Zubin Jacob, Elmore Associate Professor of Electrical and Computer Engineering and Department of Physics and Astronomy (courtesy), published their findings in APS Physics Review Applied in a paper titled, “Picophotonics: Anomalous Atomistic Waves in Silicon.”
“The word microscopic has its origins in the length scale of a micron which is a million times smaller than a meter. Our work is for light matter interaction within the picoscopic regime which is far smaller, where the discrete arrangement of atomic lattices changes light’s properties in surprising ways,” says Jacob.
These intriguing findings demonstrate that natural media host a variety of rich light-matter interaction phenomena at the atomistic level. The use of picophotonic waves in semiconducting materials may lead researchers to design new, functional optical devices, allowing for applications in quantum technologies.
Light-matter interaction in materials is central to several photonic devices from lasers to detectors. Over the past decade, nanophotonics, the study of how light flows on the nanometer scale in engineered structures such as photonic crystals and metamaterials have led to important advances. This existing research can be captured within the realm of classical theory of atomic matter. The current finding leading to picophotonics was made possible by a major leap forward using a quantum theory of atomistic response in matter. The team consists of Jacob as well as Dr. Sathwik Bharadwaj, research scientist at Purdue University, and Dr. Todd Van Mechelen, former post-doc at Purdue University.
The long-standing puzzle in the field was the missing link between atomic lattices, their symmetries and the role it plays on deeply picoscopic light fields. To answer this puzzle, the theory team developed a Maxwell Hamiltonian framework of matter combined with a quantum theory of light induced response in materials.
“This is a pivotal shift from the classical treatment of light flow applied in nanophotonics,” says Jacob. “The quantum nature of light’s behavior in materials is the key for the emergence of picophotonics phenomena.”
Bharadwaj and colleagues showed that hidden amidst traditional well-known electromagnetic waves, new anomalous waves emerge in the atomic lattice. These light waves are highly oscillatory even within one fundamental building block of the silicon crystal (sub-nanometer length scale).
“Natural materials itself have rich intrinsic crystal lattice symmetries and light is strongly influenced by these symmetries,” says Bharadwaj. “The immediate next goal is to apply our theory to the plethora of quantum and topological materials and also verify the existence of these new waves experimentally.”
“Our group has been leading the frontier of research on pico-scale electrodynamic fields inside matter at the atomistic level,” says Jacob. “We recently initiated the picoelectrodynamics theory network where we are bringing together diverse researchers to explore macroscopic phenomena stemming from microscopic pico-electrodynamic fields inside matter.”
This research was funded by the DARPA QUEST program.
Writer: Cheryl Pierce, communications specialist, Earth, Atmospheric, Planetary Sciences | Physics/Astronomy, Purdue University
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This little robot can go almost anywhere.
Researchers at Carnegie Mellon University’s School of Computer Science and the University of California, Berkeley, have designed a robotic system that enables a low-cost and relatively small legged robot to climb and descend stairs nearly its height; traverse rocky, slippery, uneven, steep and varied terrain; walk across gaps; scale rocks and curbs; and even operate in the dark.
“Empowering small robots to climb stairs and handle a variety of environments is crucial to developing robots that will be useful in people’s homes as well as search-and-rescue operations,” said Deepak Pathak, an assistant professor in the Robotics Institute. “This system creates a robust and adaptable robot that could perform many everyday tasks.”
The team put the robot through its paces, testing it on uneven stairs and hillsides at public parks, challenging it to walk across stepping stones and over slippery surfaces, and asking it to climb stairs that for its height would be akin to a human leaping over a hurdle. The robot adapts quickly and masters challenging terrain by relying on its vision and a small onboard computer.
The researchers trained the robot with 4,000 clones of it in a simulator, where they practiced walking and climbing on challenging terrain. The simulator’s speed allowed the robot to gain six years of experience in a single day. The simulator also stored the motor skills it learned during training in a neural network that the researchers copied to the real robot. This approach did not require any hand-engineering of the robot’s movements — a departure from traditional methods.
Most robotic systems use cameras to create a map of the surrounding environment and use that map to plan movements before executing them. The process is slow and can often falter due to inherent fuzziness, inaccuracies, or misperceptions in the mapping stage that affect the subsequent planning and movements. Mapping and planning are useful in systems focused on high-level control but are not always suited for the dynamic requirements of low-level skills like walking or running over challenging terrains. More