Aurelia Butler

A team of mathematicians and physicists has discovered how ice formations are shaped by external forces, such as water temperature. Its newly published research may offer another means for gauging factors that cause ice to melt.
“The shapes and patterning of ice are sensitive indicators of the environmental conditions at which it melted, allowing us to ‘read’ the shape to infer factors such as the ambient water temperature,” explains Leif Ristroph, an associate professor at New York University’s Courant Institute of Mathematical Sciences and one of the authors of the paper, which appears in the journal Physical Review Letters.
“Our work helps to understand how melting induces unusual flow patterns that in turn affect melting, which is one of the many complexities affecting the ice on our planet,” adds author Alexandra Zidovska, an associate professor in NYU’s Department of Physics.
The paper’s other authors were Scott Weady, an NYU graduate student, and Josh Tong, an undergraduate in NYU’s College of Arts and Science at the time of the study.
In NYU’s Applied Mathematics Laboratory and Center for Soft Matter Research, the researchers studied, through a series of experiments, the melting of ice in water and, in particular, how the water temperature affects the eventual shapes and patterning of ice. To do so, they created ultra-pure ice, which is free of bubbles and other impurities. The team recorded the melting of ice submerged into water tanks in a “cold room,” which is similar to a walk-in refrigerator whose temperature is controlled and varied.
“We focused on the cold temperatures — 0 to 10 degrees Celsius — at which ice in natural waters typically melts, and we found a surprising variety of shapes that formed,” says Ristroph, who directs the Applied Mathematics Laboratory. More

Researchers at the Yale School of Public Health were able to accurately predict outbreaks of COVID-19 in Connecticut municipalities using anonymous location information from mobile devices, according to a new study published in Science Advances.
The novel analysis applied in the study could help health officials stem community outbreaks of COVID-19 and allocate testing resources more efficiently, the researchers said.
The study was conducted by data scientists and epidemiologists from the Yale School of Public Health, the Connecticut Department of Public Health, the U.S. Centers for Disease Control and Prevention and Whitespace Ltd., a spatial data analytics firm.
The key to the findings was the precision with which researchers were able to identify incidents of high frequency close personal contact (defined as a radius of 6 feet) in Connecticut down to the municipal level. The CDC advises people to keep at least six feet of distance with others to avoid possible transmission of COVID-19.
“Close contact between people is the primary route for transmission of SARS-CoV-2, the virus that causes COVID-19,” said the study’s lead author Forrest Crawford, an associate professor of biostatistics at the Yale School of Public Health and an associate professor of ecology and evolutionary biology, management, statistics and data science at Yale.
“We measured close interpersonal contact within a 6-foot radius everywhere in Connecticut using mobile device geolocation data over the course of an entire year,” Crawford said. “This effort gave Connecticut epidemiologists and policymakers insight to people’s social distancing behavior statewide.”
Other studies have used so-called “mobility metrics” as proxy measures for social distancing behavior and potential COVID-19 transmission. But that analysis can be flawed. More

Surveys that ask too many of the same type of question tire respondents and return unreliable data, according to a new UC Riverside-led study.
The study found that people tire from questions that vary only slightly and tend to give similar answers to all questions as the survey progresses. Marketers, policymakers, and researchers who rely on long surveys to predict consumer or voter behavior will have more accurate data if they craft surveys designed to elicit reliable, original answers, the researchers suggest.
“We wanted to know, is gathering more data in surveys always better, or could asking too many questions lead to respondents providing less useful responses as they adapt to the survey,” said first author Ye Li, a UC Riverside assistant professor of management. “Could this paradoxically lead to asking more questions but getting worse results?”
While it may be tempting to assume more data is always better, the authors wondered if the decision processes respondents use to answer a series of questions might change, especially when those questions use a similar, repetitive format.
The research addressed quantitative surveys of the sort typically used in market research, economics, or public policy research that seek to understand people’s values about certain things. These surveys often ask a large number of structurally similar questions.
Researchers analyzed four experiments that asked respondents to answer questions involving choice and preference. More

Drilling with the beam of an electron microscope, scientists at the Department of Energy’s Oak Ridge National Laboratory precisely machined tiny electrically conductive cubes that can interact with light and organized them in patterned structures that confine and relay light’s electromagnetic signal. This demonstration is a step toward potentially faster computer chips and more perceptive sensors.
The seeming wizardry of these structures comes from the ability of their surfaces to support collective waves of electrons, called plasmons, with the same frequency as light waves but with much tighter confinement. The light-guiding structures are measured in nanometers, or billionths of a meter — 100,000 times thinner than a human hair.
“These nanoscale cube systems allow extreme confinement of light in specific locations and tunable control of its energy,” said ORNL’s Kevin Roccapriore, first author of a study published in the journal Small. “It’s a way to connect signals with very different length scales.”
The feat may prove critical for quantum and optical computing. Quantum computers encode information with quantum bits, or qubits, determined by a quantum state of a particle, such as its spin. Qubits can store many values compared with the single value stored by a classical bit.
Light — electromagnetic radiation that propagates by massless elementary particles called photons — replaces electrons as the messenger in optical computers. Because photons travel faster than electrons and do not generate heat, optical computers could have performance and energy efficiency superior to classical computers.
Future technologies may use the best of both worlds. More

Trapped ions excited with a laser beam can be used to create entangled qubits in quantum information systems, but addressing several stationary pairs of ions in a trap requires multiple optical switches and complex controls. Now, scientists at the Georgia Tech Research Institute (GTRI) have demonstrated the feasibility of a new approach that moves trapped ion pairs through a single laser beam, potentially reducing power requirements and simplifying the system.
In a paper scheduled to be published January 31 in the journal Physical Review Letters, the researchers describe implementing two-qubit entangling gates by moving calcium ions held in a surface electrode trap through a stationary bichromatic optical beam. Maintaining a constant Doppler shift during the ion movement required precise control of the timing.
“We’ve shown that ion transport is an interesting tool that can be applied in unique ways to produce an entangled state using fine control over the ion transport,” said Holly Tinkey, a GTRI research scientist who led the study. “Most ion trap experiments have some control over the motion of the ions, so what we have shown is that we can potentially integrate that existing transport into quantum logic operations.”
Measurements showed that the entangled quantum state of the two qubits transported through the optical beam had a fidelity comparable to entangled states produced by stationary gates performed in the same trapping system. The experiment used an optical qubit transition between an electronic ground state and a metastable state of 40Ca+ ions within a surface trap, a setup which allowed both one-qubit and two-qubit gates to be performed using a single beam.
The researchers moved the pair of trapped ions by precisely varying the electrical confinement fields in the trap by controlling the voltages applied to adjacent electrodes. The ions themselves have an electrical charge, a property which makes them subject to the changing electrical fields around them.
“We perform some interactions where the ions are trapped together in a single potential well and where they are very close and can interact, but then we sometimes want to separate them to do something distinct to one ion that we don’t want to do to the other ion,” Tinkey explained. More

A joint research team from the Hong Kong University of Science and Technology (HKUST) and the University of Tokyo discovered an unusual topological aspect of sodium chloride, commonly known as table salt, which will not only facilitate the understanding of the mechanism behind salt’s dissolution and formation, but may also pave the way for the future design of nanoscale conducting quantum wires.
There is a whole variety of advanced materials in our daily life, many gadgets and technology are created through the assembly of different materials. Cellphone, for example, adopted a combination of many different substances — glass for the monitor, aluminum alloy for the frame, and metals like gold, silver and copper for its internal wirings. But nature has its own genius way of ‘cooking’ different properties into one wonder material, or what is known as ‘topological material’.
Topology, as a mathematical concept, studies what aspects of an object are robust under a smooth deformation. For instance, we can squeeze, stretch, or twist a T-shirt, but the number its openings would still remain as four so long as we do not tear it apart. The discovery of topological phases of matter, highlighted by the 2016 Nobel Prize in Physics, suggests that certain quantum materials are inherently a combination of electrical insulator and conductor. This could necessitate a conducting boundary even when the bulk of the material is insulating. Such materials are neither classified as a metal nor an insulator, but a natural assembly of the two.
While the topological qualities of materials attract a lot of research interests, at present they are only realized in an exclusive set of exotic materials — such as the two-dimensional graphene. However, in a recent work, Prof. Adrian PO Hoi Chun, Assistant Professor from HKUST’s Department of Physics and his collaborator, Prof. Haruki WATANABE from the University of Tokyo, have discovered a surprising connection between topology and a large class of ordinary substances, including table salt.
Table salt, or sodium chloride, is one of the most common crystals frequently featured in high-school chemistry textbooks as a prototypical ionic compound. It’s long believed that such well-known substance are topologically boring. However, the research team discovered that table salt can actually, in theory, realize a form of recently introduced, “higher-order” topology. Instead of conducting two-dimensional surfaces or one-dimensional edges, the zero-dimensional corner of a grain of salt showcases an anomalous behavior in which electric charges are effectively fractionalized into one-eighth of the fundamental unit of Nature. Furthermore, the robustness of this topological property implies that even if the chemical structure is modified into other formats such as silver chloride or potassium fluoride, the result would still be upheld.
Prof. Watanabe said the connection between topological materials and everyday substances like table salt is totally unexpected. Prof. Po said the result suggests an overlooked aspect of topology in common ionic compounds. “The finding may inspire future design of nanoscale conducting quantum wires, or novel drug delivery method, which is so often studied along with the salt dissolution processes,” Prof. Po said, adding that “it is amusing to realize how we ingest fractions of an electron upon our every meal.”
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Researchers have known about high-temperature superconducting copper-based materials, or cuprates, since the 1980s. Below a certain temperature (approximately -130 degree Celsius), electrical resistance vanishes from these materials and magnetic flux fields are expelled. However, the basis for that superconductivity continues to be debated and explored.
“It has been widely accepted that traditional superconductors result from electrons interacting with phonons, where the phonons pair two electrons as an entity and the latter can run in a material without resistance,” said Yao Wang, assistant professor of physics and astronomy at Clemson University.
However, in cuprates, strong repulsions known as the Coulomb force were found between electrons and were believed to be the cause of this special and high-temperature superconductivity.
Phonons are the vibrational energy that arise from oscillating atoms within a crystal. The behavior and dynamics of phonons are very different from those of electrons, and putting these two interacting pieces of the puzzle together has been a challenge.
In November 2021, writing in the journal Physical Review Letters, Wang, along with researchers from Stanford University, presented compelling evidence that phonons are in fact contributing to a key feature observed in cuprates, which may indicate their indispensable contribution to superconductivity.
The study innovatively accounted for the forces of both electrons and phonons together. They showed that phonons impact not only electrons in their immediate vicinity, but act on electrons several neighbors away. More

Computers could mimic neural networks in the brain — and be much more energy efficient — with a new computer component that mimics how the brain works by acting like a synaptic cell. It’s called an electrochemical random access memory (ECRAM), and researchers have developed materials that offer a commercially-viable way to build these components.
Researchers from KTH Royal Institute of Technology and Stanford University have now fabricated a material for computer components that enable the commercial viability of computers that mimic the human brain.
Electrochemical random access (ECRAM) memory components made with 2D titanium carbide showed outstanding potential for complementing classical transistor technology, and contributing toward commercialization of powerful computers that are modeled after the brain’s neural network. Such neuromorphic computers can be thousands times more energy efficient than today’s computers.
These advances in computing are possible because of some fundamental differences from the classic computing architecture in use today, and the ECRAM, a component that acts as a sort of synaptic cell in an artificial neural network, says KTH Associate Professor Max Hamedi.
“Instead of transistors that are either on or off, and the need for information to be carried back and forth between the processor and memory — these new computers rely on components that can have multiple states, and perform in-memory computation,” Hamedi says.
The scientists at KTH and Stanford have focused on testing better materials for building an ECRAM, a component in which switching occurs by inserting ions into an oxidation channel, in a sense similar to our brain which also works with ions. What has been needed to make these chips commercially viable are materials that overcome the slow kinetics of metal oxides and the poor temperature stability of plastics.
The key material in the ECRAM units that the researchers fabricated is referred to as MXene — a two-dimensional (2D) compound, barely a few atoms thick, consisting of titanium carbide (Ti3C2Tx). The MXene combines the high speed of organic chemistry with the integration compatibility of inorganic materials in a single device operating at the nexus of electrochemistry and electronics, Hamedi says.
Co-author Professor Alberto Salleo at Stanford University, says that MXene ECRAMs combine the speed, linearity, write noise, switching energy, and endurance metrics essential for parallel acceleration of artificial neural networks.
“MXenes are an exciting materials family for this particular application as they combine the temperature stability needed for integration with conventional electronics with the availability of a vast composition space to optimize performance, Salleo says”
While there are many other barriers to overcome before consumers can buy their own neuromorphic computers, Hamedi says the 2D ECRAMs represent a breakthrough at least in the area of neuromorphic materials, potentially leading to artificial intelligence that can adapt to confusing input and nuance, the way the brain does with thousands time smaller energy consumption. This can also enable portable devices capable of much heavier computing tasks without having to rely on the cloud.
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Materials provided by KTH, Royal Institute of Technology. Note: Content may be edited for style and length. More