Computers Math

They are regarded as one of the most interesting materials for future electronics: Topological insulators conduct electricity in a special way and hold the promise of novel circuits and faster mobile communications. Under the leadership of the Helmholtz-Zentrum Dresden-Rossendorf (HZDR), a research team from Germany, Spain and Russia has now unravelled a fundamental property of this new class of materials: How exactly do the electrons in the material respond when they are “startled” by short pulses of so-called terahertz radiation? The results are not just significant for our basic understanding of this novel quantum material, but could herald faster mobile data communication or high-sensitivity detector systems for exploring distant worlds in years to come, the team reports in NPJ Quantum Materials.
Topological insulators are a very recent class of materials which have a special quantum property: on their surface they can conduct electricity almost loss-free while their interior functions as an insulator — no current can flow there. Looking to the future, this opens up interesting prospects: Topological insulators could form the basis for high efficiency electronic components, which makes them an interesting research field for physicists.
But a number of fundamental questions are still unanswered. What happens, for example, when you give the electrons in the material a “nudge” using specific electromagnetic waves — so-called terahertz radiation — thus generating an excited state? One thing is clear: the electrons want to rid themselves of the energy boost forced upon them as quickly as possible, such as by heating up the crystal lattice surrounding them. In the case of topological insulators, however, it was previously unclear whether getting rid of this energy happened faster in the conducting surface than in the insulating core. “So far, we simply didn’t have the appropriate experiments to find out,” explains study leader Dr. Sergey Kovalev from the Institute of Radiation Physics at HZDR. “Up to now, at room temperature, it was extremely difficult to differentiate the surface reaction from that in the interior of the material.”
In order to overcome this hurdle, he and his international team developed an ingenious test set-up: intensive terahertz pulses hit a sample and excite the electrons. Immediately after, laser flashes illuminate the material and register how the sample responds to the terahertz stimulation. In a second test series, special detectors measure to what extent the sample exhibits an unusual non-linear effect and multiplies the frequency of the terahertz pulses applied. Kovalev and his colleagues conducted these experiments using the TELBE terahertz light source at HZDR’s ELBE Center for High-Power Radiation Sources. Researchers from the Catalan Institute of Nanoscience and Nanotechnology in Barcelona, Bielefeld University, the German Aerospace Center (DLR), the Technical University of Berlin, and Lomonosov University and the Kotelnikov Institute of Radio Engineering and Electronics in Moscow were involved.
Rapid energy transfer
The decisive thing was that the international team did not only investigate a single material. Instead, the Russian project partners produced three different topological insulators with different, precisely determined properties: in one case, only the electrons on the surface could directly absorb the terahertz pulses. In the others, the electrons were mainly excited in the interior of the sample. “By comparing these three experiments we were able to differentiate precisely between the behavior of the surface and the interior of the material,” Kovalev explains. “And it emerged that the electrons in the surface became excited significantly faster than those in the interior of the material.” Apparently, they were able to transfer their energy to the crystal lattice immediately.
Put into figures: while the surface electrons reverted to their original energetic state in a few hundred femtoseconds, the “inner” electrons took approximately ten times as long, that is, a few picoseconds. “Topological insulators are highly-complex systems. The theory is anything but easy to understand,” emphasizes Michael Gensch, former head of the TELBE facility at HZDR and now head of department in the Institute of Optical Sensor Systems at the German Aerospace Center (DLR) and professor at TU Berlin. “Our results can help decide which of the theoretical ideas hold true.”
Highly effective multiplication
But the experiment also augurs well for interesting developments in digital communication like WLAN and mobile communications. Today, technologies such as 5G function in the gigahertz range. If we could harness higher frequencies in the terahertz range, significantly more data could be transmitted by a single radio channel, whereby frequency multipliers could play an important role: They are able to translate relatively low radio frequencies into significantly higher ones.
Some time ago, the research team had already realized that, under certain conditions, graphene — a two-dimensional, super thin carbon — can act as an efficient frequency multiplier. It is able to convert 300 gigahertz radiation into frequencies of some terahertz. The problem is that when the applied radiation is extremely intensive, there is a significant drop in the efficiency of the graphene. Topological insulators, on the other hand, even function with the most intensive stimulation, the new study discovered. “This might mean it’s possible to multiply frequencies from a few terahertz to several dozen terahertz,” surmises HZDR physicist Jan-Christoph Deinert, who heads the TELBE team together with Sergey Kovalev. “At the moment, there is no end in sight when it comes to topological insulators.”
If such a development comes about, the new quantum materials could be used in a much wider frequency range than with graphene. “At DLR, we are very interested in using quantum materials of this kind in high-performance heterodyne receivers for astronomy, especially in space telescopes,” Gensch explains. More

The discovery in 2018 of superconductivity in two single-atom-thick layers of graphene stacked at a precise angle of 1.1 degrees (called ‘magic’-angle twisted bilayer graphene) came as a big surprise to the scientific community. Since the discovery, physicists have asked whether magic graphene’s superconductivity can be understood using existing theory, or whether fundamentally new approaches are required — such as those being marshalled to understand the mysterious ceramic compound that superconducts at high temperatures. Now, as reported in the journal Nature, Princeton researchers have settled this debate by showing an uncanny resemblance between the superconductivity of magic graphene and that of high temperature superconductors. Magic graphene may hold the key to unlocking new mechanisms of superconductivity, including high temperature superconductivity.
Ali Yazdani, the Class of 1909 Professor of Physics and Director of the Center for Complex Materials at Princeton University led the research. He and his team have studied many different types of superconductors over the years and have recently turned their attention to magic bilayer graphene.
“Some have argued that magic bilayer graphene is actually an ordinary superconductor disguised in an extraordinary material,” said Yazdani, “but when we examined it microscopically it has many of the characteristics of high temperature cuprate superconductors. It is a déjà vu moment.”
Superconductivity is one of nature’s most intriguing phenomena. It is a state in which electrons flow freely without any resistance. Electrons are subatomic particles that carry negative electric charges; they are vital to our way of life because they power our everyday electronics. In normal circumstances, electrons behave erratically, jumping and jostling against each other in a manner that is ultimately inefficient and wastes energy.
But under superconductivity, electrons suddenly pair up and start to flow in unison, like a wave. In this state the electrons not only do not lose energy, but they also display many novel quantum properties. These properties have allowed for a number of practical applications, including magnets for MRIs and particle accelerators as well as in the making of quantum bits that are being used to build quantum computers. Superconductivity was first discovered at extremely low temperatures in elements such as aluminum and niobium. In recent years, it has been found close to room temperatures under extraordinarily high pressure, and also at temperatures just above the boiling point of liquid nitrogen (77 degrees Kelvin) in ceramic compounds.
But not all superconductors are created equal. More

Without enzymes, an organism would not be able to survive. It is these biocatalysts that facilitate a whole range of chemical reactions, producing the building blocks of the cells. Enzymes are also used widely in biotechnology and in our households, where they are used in detergents, for example.
To describe metabolic processes facilitated by enzymes, scientists refer to what is known as the Michaelis-Menten equation. The equation describes the rate of an enzymatic reaction depending on the concentration of the substrate — which is transformed into the end products during the reaction. A central factor in this equation is the ‘Michaelis constant’, which characterises the enzyme’s affinity for its substrate.
It takes a great deal of time and effort to measure this constant in a lab. As a result, experimental estimates of these constants exist for only a minority of enzymes. A team of researchers from the HHU Institute of Computational Cell Biology and Chalmers University of Technology in Stockholm has now chosen a different approach to predict the Michaelis constants from the structures of the substrates and enzymes using AI.
They applied their approach, based on deep learning methods, to 47 model organisms ranging from bacteria to plants and humans. Because this approach requires training data, the researchers used known data from almost 10,000 enzyme-substrate combinations. They tested the results using Michaelis constants that had not been used for the learning process.
Prof. Lercher had this to say about the quality of the results: “Using the independent test data, we were able to demonstrate that the process can predict Michaelis constants with an accuracy similar to the differences between experimental values from different laboratories. It is now possible for computers to estimate a new Michaelis constant in just a few seconds without the need for an experiment.”
The sudden availability of Michaelis constants for all enzymes of model organisms opens up new paths for metabolic computer modelling, as highlighted by the journal PLOS Biology in an accompanying article.
Story Source:
Materials provided by Heinrich-Heine University Duesseldorf. Original written by Arne Claussen. Note: Content may be edited for style and length. More

Diagnosing and treating cancer can be a race against time. By the time the disease is diagnosed in a patient, all too often it is advanced and able to spread throughout the body, decreasing chances of survival. Early diagnosis is key to stopping it.
In a new Concordia-led paper published in the journal Biosensors and Bioelectronics, researchers describe a new liquid biopsy method using lab-on-a-chip technology that they believe can detect cancer before a tumour is even formed.
Using magnetic particles coated in a specially designed bonding agent, the liquid biopsy chip attracts and captures particles containing cancer-causing biomarkers. A close analysis can identify the type of cancer they are carrying. This, the researchers say, can significantly improve cancer diagnosis and treatment.
Trapping the messenger
The chip targets extracellular vesicles (EVs), a type of particle that is released by most kinds of organic cells. EVs — sometimes called exosomes — are extremely small, usually measuring between 40 and 200 nanometres. But they contain a cargo of proteins, nucleic acids such as RNA, metabolites and other molecules from the parent cell, and they are taken up by other cells. If EVs contain biomarkers associated with cancer and other diseases, they will spread their toxic cargo from cell to cell.
To capture the cancer-carrying exosomes exclusively, the researchers developed a small microfluidic chip containing magnetic or gold nanoparticles coated with a synthetic polypeptide to act as a molecular bonding agent. When a droplet of organic liquid, be it blood, saliva, urine or any other, is run through the chip, the exosomes attach themselves to the treated nanoparticles. After the exosomes are trapped, the researchers then separate them from the nanoparticles and carry out proteomic and genomic analysis to determine the specific cancer type.
“This technique can provide a very early diagnosis of cancer that would help find therapeutic solutions and improve the lives of patients,” says the paper’s senior author Muthukumaran Packirisamy, a professor in the Department of Mechanical, Industrial and Aerospace Engineering and director of Concordia’s Optical Bio-Microsystems Laboratory.
Alternatives to conventional chemo and exploratory surgeries
“Liquid biopsies avoid the trauma of invasive biopsies, which involve exploratory surgery,” he adds. “We can get all the cancer markers and cancer prognoses just by examining any bodily fluid.”
Having detailed knowledge of a particular form of cancer’s genetic makeup will expose its weaknesses to treatment, notes Anirban Ghosh, a co-author and affiliate professor at Packirisamy’s laboratory. “Conventional chemotherapy targets all kinds of cells and results in significant and unpleasant side effects,” he says. “With the precision diagnostics afforded to us here, we can devise a treatment that only targets cancer cells.”
The paper’s lead author is PhD student Srinivas Bathini, whose academic background is in electrical engineering. He says the interdisciplinary approach to his current area of study has been challenging and rewarding and notes that the technology’s potential could revolutionize medical diagnostics. The researchers used breast cancer cells in this study but are looking at ways to expand their capabilities to include a wide range of disease testing.
“Perhaps one day this product could be as readily available as other point-of-care devices, such as home pregnancy tests,” he speculates.
Story Source:
Materials provided by Concordia University. Original written by Patrick Lejtenyi. Note: Content may be edited for style and length. More

In many parts of the world, the supply of COVID-19 vaccines continues to lag behind the demand. While most vaccines are designed as a two-dose regimen, some countries, like Canada, have prioritized vaccinating as many people as possible with a single dose before giving out an additional dose.
In Chaos, by AIP Publishing, researchers from the Frankfurt School of Finance and Management and the University of California, Los Angeles illustrate the conditions under which a “prime first” vaccine campaign is most effective at stopping the spread of the COVID-19 virus.
The prime first campaign does not suggest people should receive only one dose of the vaccine. Instead, it emphasizes vaccinating large numbers of people as quickly as possible, then doubling back to give out second doses. In comparison, the “prime boost” vaccine campaign prioritizes fully vaccinating fewer people.
Immunologically speaking, the prime boost scenario is always superior. However, under supply constraints, the advantages of vaccinating twice as many people may outweigh the advantages of a double dose.
The scientists simulated the transmission of COVID-19 with a susceptible, exposed, infected, recovered, deceased model. Each of these disease states is associated with a compartment containing individual people. Transitions between compartments depend on disease parameters like virus transmissibility.
Each compartment is further divided to account for unvaccinated, partially vaccinated, and fully vaccinated individuals. The researchers measured how each vaccine group compared to the others under different conditions.
“We have this giant degree of uncertainty about the parameters of COVID-19,” said author Jan Nagler. “We acknowledge that we don’t know these precise values, so we sample over the entire parameter space. We give a nice idea of when prime first campaigns are better with respect to saving lives than prime boost vaccination.”
The team found the vaccine waning rate to be a critically important factor in the decision. If the waning, or decrease in vaccine effectiveness, is too strong after a single dose, the double dose vaccination strategy is often the better option.
However, the vaccine strategy flips if the waning rate after a single dose is more like the waning rate after a double dose.
“Our results suggest that better estimates of immunity waning rates are important to decide if prime first protocols are more effective than prime boost vaccination,” said author Lucas Böttcher.
As the scientific community gathers more data on COVID-19 vaccinations, the scientists hope this model will become more informative for public health experts and politicians who must decide for or against a certain vaccination protocol.
Story Source:
Materials provided by American Institute of Physics. Note: Content may be edited for style and length. More

Along with the use of face masks, social distancing in public remains one of the most practiced front-line defenses against the spread of COVID-19. However, flows of pedestrians, including those practicing the 6-foot rule for distancing, are dynamic and characterized by nuances not always carefully considered in the context of everyday, public spaces.
In Physics of Fluids, by AIP Publishing, researchers from Carnegie Mellon University examine the dynamics of social distancing practices through the lens of particle-based flow simulations. The study models social distance as the distance at which particles, representing pedestrians, repel fellow particles.
“Even at modest pedestrian density levels, a strong preference for 6 feet of social distance can cause large-scale pedestrian ‘traffic jams’ that take a long time to clear up,” said Gerald J. Wang, of Carnegie Mellon University. “This is pretty evident to all of us who have engaged in that ‘awkward dance of social distance’ in a grocery store aisle during the past 18 months, but it has important implications for how we set occupancy thresholds as workplaces, campuses, and entertainment venues return to pre-pandemic densities.”
Motivated by the pandemic, the researchers shed light on the relationship between social distancing and pedestrian flow dynamics in corridors by illustrating how adherence to social distancing protocols affects two-way pedestrian movement in a shared space. The results add to a significant body of recent work around the effects of various factors on pedestrian counterflows and focuses on the characterization of jamming phenomena in relatively narrow corridors, a topic of current interest.
“Dense pedestrian flows plus social distancing recommendations is a recipe for a lot of frustration,” said Wang. “I mean this both in the physics sense of the word ‘frustration,’ with low particle mobilities because a bunch of ‘stuff’ is seemingly in their way, and in the everyday sense of the word ‘frustration,’ with people feeling flustered because, well, a bunch of ‘stuff’ is seemingly in their way!”
Wang noted public health messaging should be aligned with realistic, achievable behavior, adding that “strict adherence to social distancing — a la ‘the 6-foot rule’ — is simply not a practical recommendation in pedestrian flows at densities that are typical of large, shared venues.”
Though conceptually easy to digest, the findings underscore the complications of applying a “one-size-fits-all” policy recommendation to a public sphere characterized by nuanced pedestrian flow dynamics.
“Particle-based flow simulation, powered by high-performance computing, has enormous potential to rapidly explore a broad range of pedestrian flow problems, both during the pandemic and beyond,” said co-author Kelby B. Kramer.
Story Source:
Materials provided by American Institute of Physics. Note: Content may be edited for style and length. More

The COVID-19 pandemic has led to more than 218 million infections and over 4.5 million deaths as of Sept. 3, 2021. Nonpharmaceutical interventions (NPIs), such as case isolation, quarantining contacts, and the complete lockdown of entire countries, were implemented in an effort to contain the pandemic. But these NPIs often come at the expense of economic disruption, harm to social and mental well-being, and costly administration costs to ensure compliance.
Given the slow rollout of vaccination programs worldwide and the rise of several mutations of the coronavirus, the use of these types of interventions will continue for some time. In Chaos, by AIP Publishing, researchers in China use a data-driven agent-based model to identify new and sustainable NPIs to contain outbreaks while minimizing the economic and social costs.
“Based on the proposed model, we proposed targeted interventions, which can contain the outbreak with minimal disruption of society. This is of particular importance in cities like Hong Kong, whose economy relies on international trade,” said author Qingpeng Zhang.
The researchers built a data-driven mobility model to simulate COVID-19 spreading in Hong Kong by combining synthetic population, human behavior patterns, and a viral transmission model. This model generated 7.55 million agents to describe the infectious state and movement for each Hong Kong resident.
Since mobile phone data is difficult to obtain in most countries, the researchers calibrated their model with open-source data, so it could be easily extended to the modeling of other metropolises with various demographic and human mobility patterns.
“With the agent-based model, we can simulate very detailed scenarios in Hong Kong, and based on these simulations, we are able to propose targeted interventions in only a small portion of the city instead of city-level NPIs,” said Zhang.
The researchers found that by controlling a small percentage (top 1%-2%) of grids in Hong Kong, the virus could be largely contained. While such interventions are not as effective as citywide NPIs and compulsory COVID-19 testing, such targeted control has the benefit of a much smaller disruption of society.
The proposed model leading to the targeted interventions has the potential to guide current citywide NPIs to achieve a balance between lowering the risk and preserving human mobility and economy of the city.
“Our findings also apply to other major cities in the world, such as Beijing, New York, London, and Toyko, as COVID-19 is likely to be around indefinitely, and we have to learn how to live with it,” said Zhang.
Story Source:
Materials provided by American Institute of Physics. Note: Content may be edited for style and length. More

A team of physicists from Germany and Sweden working with first author Jens Christian Grauer from Heinrich Heine University Düsseldorf (HHU) has examined a special system of colloidal particles that they activated using laser light. The researchers discovered that self-propelling droplets, which they have named ‘droploids’, formed which contain the particles as an internal motor. They describe these droploids in more detail in the latest edition of the journal Nature Communications.
According to an age-old saying, the whole is often more than the sum of its parts. After all, a sandwich made of bread, lettuce and mayonnaise tastes better than its individual components. A team of physicists from HHU, TU Darmstadt and Sweden’s University of Gothenburg has determined that this adage is also true in the realm of physics, and that combining individual parts can create something with entirely new properties.
The research project involved combining different atoms and larger particles and studying the effects they have on each other. It is ultimately a typical example of what the matter that surrounds us is composed of. The researchers extended this general principle of combination to include additional feedback processes, thus creating new kinds of dynamic structures referred to as ‘positive feedback loops’.
Specifically, they combined two different types of colloid particles — in a water-lutidine heat bath. They irradiated the bath with lasers, and the light from the lasers brought the liquid near the particles to the critical point. The fluctuations are particularly strong at this point, allowing droplet-like structures to form that in turn surround the particles.
Inside the droplets, the two types of colloid particles heat up to different temperatures. This results in effective forces that contradict Newton’s fundamental law of motion (actio = reactio) to propel the droplets forwards. This means that the colloid particles induce the formation of droplets that encapsulate the colloids and are in turn propelled by the particles. This feedback loop results in novel superstructures with a self-organised colloidal motor. The researchers adopted the term ‘droploids’, a portmanteau of the words ‘droplets’ and ‘colloids’, to describe these superstructures.
The research team combined theoretical and experimental approaches, with the system modelling performed in Düsseldorf and Darmstadt, while the colleagues in Gothenburg verified the findings using real-life experiments, thus confirming the theoretical models.
Prof. Dr. Hartmut Löwen, Head of the Institute of Theoretical Physics II at HHU, had this to say: “It’s important here that the process can be controlled entirely by laser illumination. This makes it possible to steer the system externally so that it is flexible for different applications.”
Prof. Dr. Benno Liebchen, leader of the “Theory of Soft Matter” working group at TU Darmstadt, explained the actual use of the droploids as follows: “Besides justifying a novel concept for micromotors, the droploids and the non-reciprocal interactions involved could serve as important ingredients for generating future biomimetic materials.”
Story Source:
Materials provided by Heinrich-Heine University Duesseldorf. Note: Content may be edited for style and length. More