Aurelia Butler

Scientists at Osaka University have simulated heat transport at the smallest scales using a molecular dynamics computer simulation. By studying the motions of the individual particles that make up the boundary between a solid and a liquid, they have been able to calculate heat flux with unprecedented precision. This work may lead to significant improvements in our ability to fabricate nanoscale devices, as well as functional surfaces and nanofluidic devices.
The process by which heat is transferred at the point where a solid meets a liquid may seem to be a simple physics problem. Traditionally, macroscopic quantities — such as density, pressure, temperature, and heat capacity — were used to compute the rate at which thermal energy moves between materials. However, properly accounting for the motion of individual molecules, while observing the laws of conservation of energy and momentum, adds a great deal of complexity. Improved atomic-scale computer simulations would be invaluable to more accurately understanding a wide array of real-world applications, especially within the field of nanotechnology.
Now, a team of researchers at Osaka University has developed a new numerical technique to visualize a modeled heat flux at the atomic scale for the first time. “To fundamentally understand thermal transport through a solid-liquid interface, the transport properties of atoms and molecules must be considered,” first author of the study Kunio Fujiwara explains. “We modeled the heat flux near a solid-liquid interface region with sub-atomic spatial resolution by using classical molecular dynamics simulations. This allowed us to create images of the three-dimensional structure of the energy flow while heat was being transferred between the layers.”
Using the popular Lennard-Jones potential to calculate the interactions between adjacent atoms, the team found that the direction of heat flux strongly depends on the sub-atomic stresses in the structures of the solids or liquids.
“Before, there was no good way to visualize heat flux at atomic scale,” senior author Masahiko Shibahara says. “These findings should allow us to elucidate and modify the thermal transport based on the 3D heat flux configuration.”
This may allow for customized nanoscale manufacturing to be carried out more efficiently.
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Scientists are using cutting-edge artificial intelligence to help extract complex information from large collections of museum specimens.
A team from Cardiff University is using state-of-the-art techniques to automatically segment and capture information from museum specimens and perform important data quality improvement without the need of human input.
They have been working with museums from across Europe, including the Natural History Museum, London, to refine and validate their new methods and contribute to the mammoth task of digitising hundreds of millions of specimens.
With more than 3 billion biological and geological specimens curated in natural history museums around the world, the digitization of museum specimens, in which physical information from a particular specimen is transformed into a digital format, has become an increasingly important task for museums as they adapt to an increasingly digital world.
A treasure trove of digital information is invaluable for scientists trying to model the past, present and future of organisms and our planet, and could be key to tackling some of the biggest societal challenges our world faces today, from conserving biodiversity and tackling climate change to finding new ways to cope with emerging diseases like COVID-19.
The digitization process also helps to reduce the amount of manual handling of specimens, many of which are very delicate and prone to damage. Having suitable data and images available online can reduce the risk to the physical collection and protect specimens for future generations. More

An artificial intelligence (AI)-based computer algorithm accurately predicted a person’s likelihood of suffering heart problems related to clogged arteries based on voice recordings alone, in a study presented at the American College of Cardiology’s 71st Annual Scientific Session.
Researchers found that people with a high voice biomarker score were 2.6 times more likely to suffer major problems associated with coronary artery disease (CAD), a buildup of plaque in the heart’s arteries, and three times more likely to show evidence of plaque buildup in medical tests compared with those who had a low score. While the technology is not yet ready for use in the clinic, the demonstration suggests voice analysis could be a powerful screening tool in identifying patients who may benefit from closer monitoring for CAD-related events. Researchers said this approach could be particularly useful in remote health care delivery and telehealth.
“Telemedicine is non-invasive, cost-effective and efficient and has become increasingly important during the pandemic,” said Jaskanwal Deep Singh Sara, MD, a cardiology fellow at Mayo Clinic and the study’s lead author. “We’re not suggesting that voice analysis technology would replace doctors or replace existing methods of health care delivery, but we think there’s a huge opportunity for voice technology to act as an adjunct to existing strategies. Providing a voice sample is very intuitive and even enjoyable for patients, and it could become a scalable means for us to enhance patient management.
The study represents the first time voice analysis has been used to predict CAD outcomes in patients who were tracked prospectively after an initial screening. Previous studies retrospectively examined voice markers associated with CAD and heart failure. Other research groups have explored the use of similar technology for a range of disorders, including Parkinson’s disease, Alzheimer’s disease and COVID-19.
For the new study, researchers recruited 108 patients who were referred for a coronary angiogram, an X-ray imaging procedure used to assess the condition of the heart’s arteries. Participants were asked to record three 30-second voice samples using the Vocalis Health smartphone application. For the first sample, participants read from a prepared text. For the second sample, they were asked to speak freely about a positive experience, and for the third, they spoke freely about a negative experience.
The Vocalis Health algorithm then analyzed participants’ voice samples. The AI-based system had been trained to analyze more than 80 features of voice recordings, such as frequency, amplitude, pitch and cadence, based on a training set of over 10,000 voice samples collected in Israel. In previous studies, researchers identified six features that were highly correlated with CAD. For the new study, researchers combined these features into a single score, expressed as a number between -1 and 1 for each individual. One-third of patients were categorized as having a high score and two-thirds had a low score.
“We can’t hear these particular features ourselves,” Sara said. “This technology is using machine learning to quantify something that isn’t easily quantifiable for us using our human brains and our human ears.”
Study participants were tracked for two years. Of those with a high voice biomarker score, 58.3% visited the hospital for chest pain or suffered acute coronary syndrome (a type of major heart problem that includes heart attacks), the study’s composite primary endpoint, compared with 30.6% of those with a low voice biomarker score. Participants with a high voice biomarker score were also more likely to have a positive stress test or be diagnosed with CAD during a subsequent angiogram (the composite secondary endpoint).
Scientists have not concluded why certain voice features seem to be indicative of CAD, but Sara said the autonomic nervous system may play a role. This part of the nervous system regulates bodily functions that are not under conscious control, which includes both the voice box and many aspects of the cardiovascular system, such as heart rate and blood pressure. Therefore, it is possible that the voice could provide clues about how the autonomic nervous system is functioning, and by extension, provide insights into cardiovascular health, Sara said.
The study was conducted with English speakers in the Midwestern U.S. using software trained on voice samples collected in Israel. Sara said more tests are needed to determine whether the approach is generalizable and scalable across languages, countries, cultures and health care settings. He added that it will also be important to address security and privacy issues before incorporating such technology into telemedicine or on-site health assessments.
“It’s definitely an exciting field, but there’s still a lot of work to be done,” Sara said. “We have to know the limitations of the data we have, and we need to conduct more studies in more diverse populations, larger trials and more prospective studies like this one.” More

Tiny biological computers made of DNA could revolutionize the way we diagnose and treat a slew of diseases, once the technology is fully fleshed out. However, a major stumbling block for these DNA-based devices, which can operate in both cells and liquid solutions, has been how short-lived they are. Just one use and the computers are spent.
Now, researchers at the National Institute of Standards and Technology (NIST) may have developed long-lived biological computers that could potentially persist inside cells. In a paper published in the journal Science Advances, the authors forgo the traditional DNA-based approach, opting instead to use the nucleic acid RNA to build computers. The results demonstrate that the RNA circuits are as dependable and versatile as their DNA-based counterparts. What’s more, living cells may be able to create these RNA circuits continuously, something that is not readily possible with DNA circuits, further positioning RNA as a promising candidate for powerful, long-lasting biological computers.
Much like the computer or smart device you are likely reading this on, biological computers can be programmed to carry out different kinds of tasks.
“The difference is, instead of coding with ones and zeroes, you write strings of A, T, C and G, which are the four chemical bases that make up DNA,” said Samuel Schaffter, NIST postdoctoral researcher and lead author of the study.
By assembling a specific sequence of bases into a strand of nucleic acid, researchers can dictate what it binds to. A strand could be engineered to attach to specific bits of DNA, RNA or some proteins associated with a disease, then trigger chemical reactions with other strands in the same circuit to process chemical information and eventually produce some sort of useful output.
That output might be a detectable signal that could aid medical diagnostics, or it could be a therapeutic drug to treat a disease. More

Reseachers have analysed samples of NdBi crystals which display interesting magnetic properties. In their experiments including measurements at BESSY II they could find evidence for so called Fermi arcs in the antiferromagnetic state of the sample at low temperatures. This observation is not yet explained by existing theoretical ideas and opens up exciting possibilities to make use of these kind of materials for innovative information technologies based on the electron spin rather than the charge.
Neodymium-Bismuth crystals belong to the wide range of materials with interesting magnetic properties. The Fermi surface which is measured in the experiments contains information on the transport properties of charge carriers in the crystal. While usually the Fermi surface consists of closed contours, disconnected sections known as Fermi arcs are very rare and can be signatures of unusual electronic states.
Unusual magnetic splittings
In a study, published now in Nature, the team presents experimental evidence for such Fermi arcs. They observed an unusual magnetic splitting in the antiferromagnetic state of the samples below a temperature of 24 Kelvin (the Néel-temperature). This splitting creates bands of opposing curvature, which changes with temperature together with the antiferromagnetic order.
These findings are very important because they are fundamentally different from previously theoretically considered and experimentally reported cases of magnetic splittings. In the case of well-known Zeeman and Rashba splittings, the curvature of the bands is always preserved. Since both splittings are important for spintronics, these new findings could lead to novel applications, especially as the focus of spintronics research is currently moving from traditional ferromagnetic to antiferromagnetic materials.
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Researchers have developed a new high-purity single-photon source that can operate at room temperature. The source is an important step toward practical applications of quantum technology, such as highly secure communication based on quantum key distribution (QKD).
“We developed an on-demand way to generate photons with high purity in a scalable and portable system that operates at room temperature,” said Helen Zeng, a member of the research team from the University of Technology Sydney in Australia. “Our single-photon source could advance the development of practical QKD systems and can be integrated into a variety of real-world quantum photonic applications.”
In the Optica Publishing Group journal Optics Letters, Zeng and colleagues from Australia’s University of New South Wales and Macquarie University describe their new single-photon source and show that it can produce over ten million single photons per second at room temperature. They also incorporated the single-photon source into a fully portable device that can perform QKD.
The new single-photon source uniquely combines a 2D material called hexagonal boron nitride with an optical component known as a hemispherical solid immersion lens, which increases the source’s efficiency by a factor of six.
Single photons at room temperature
QKD offers impenetrable encryption for data communication by using the quantum properties of light to generate secure random keys for encrypting and decrypting data. QKD systems require robust and bright sources that emit light as a string of single photons. However, most of today’s single-photon sources don’t perform well unless operated at cryogenic temperatures hundreds of degrees below zero, which limits their practicality. More

Atomic clocks are the best sensors humankind has ever built. Today, they can be found in national standards institutes or satellites of navigation systems. Scientists all over the world are working to further optimize the precision of these clocks. Now, a research group led by Peter Zoller, a theorist from Innsbruck, Austria, has developed a new concept that can be used to operate sensors with even greater precision irrespective of which technical platform is used to make the sensor. “We answer the question of how precise a sensor can be with existing control capabilities, and give a recipe for how this can be achieved,” explain Denis Vasilyev and Raphael Kaubrügger from Peter Zoller’s group at the Institute of Quantum Optics and Quantum Information at the Austrian Academy of Sciences in Innsbruck.
For this purpose, the physicists use a method from quantum information processing: variational quantum algorithms describe a circuit of quantum gates that depends on free parameters. Through optimization routines, the sensor autonomously finds the best settings for an optimal result. “We applied this technique to a problem from metrology — the science of measurement,” Vasilyev and Kaubrügger explain. “This is exciting because historically advances in atomic physics were motivated by metrology, and in turn quantum information processing emerged from that. So, we’ve come full circle here,” Peter Zoller enthuses. With the new approach, scientists can optimize quantum sensors to the point where they achieve the best possible precision technically permissible.
Better measurements with little extra effort
For some time, it has been understood that atomic clocks could run even more accurately by exploiting quantum mechanical entanglement. However, there has been a lack of methods to realize robust entanglement for such applications. The Innsbruck physicists are now using tailor-made entanglement that is precisely tuned to real-world requirements. With their method, they generate exactly the combination consisting of quantum state and measurements that is optimal for each individual quantum sensor. This allows the precision of the sensor to be brought close to the optimum possible according to the laws of nature, with only a slight increase in overhead. “In the development of quantum computers, we have learned to create tailored entangled states,” says Christian Marciniak from the Department of Experimental Physics at the University of Innsbruck. “We are now using this knowledge to build better sensors.”
Demonstrating quantum advantage with sensors
This theoretical concept was now implemented in practice for the first time at the University of Innsbruck, as the research group led by Thomas Monz and Rainer Blatt now reported in Nature. The physicists performed frequency measurements based on variational quantum calculations on their ion trap quantum computer. Because the interactions used in linear ion traps are still relatively easy to simulate on classical computers, the theory colleagues were able to check the necessary parameters on a supercomputer at the University of Innsbruck. Although the experimental setup is by no means perfect, the results agree surprisingly well with the theoretically predicted values. Since such simulations are not feasible for all sensors, the scientists demonstrated a second approach: They used methods to automatically optimize the parameters without prior knowledge. “Similar to machine learning, the programmable quantum computer finds its optimal mode autonomously as a high-precision sensor,” says experimental physicist Thomas Feldker, describing the underlying mechanism.
“Our concept makes it possible to demonstrate the advantage of quantum technologies over classical computers on a problem of practical relevance,” emphasizes Peter Zoller. “We have demonstrated a crucial component of quantum-enhanced atomic clocks with our variational Ramsey interferometry. Running this in a dedicated atomic clock is the next step. What has so far only been shown for calculations of questionable practical relevance could now be demonstrated with a programmable quantum sensor in the near future — quantum advantage.”
The research was financially supported by the Austrian Science Fund FWF, the Research Promotion Agency FFG, the European Union within the framework of the Quantum Flagship and the Federation of Austrian Industries Tyrol, among others.
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Lay some graphene down on a wavy surface, and you’ll get a guide to one possible future of two-dimensional electronics.
Rice University scientists put forth the idea that growing atom-thick graphene on a gently textured surface creates peaks and valleys in the sheets that turn them into “pseudo-electromagnetic” devices.
The channels create their own minute but detectable magnetic fields. According to a study by materials theorist Boris Yakobson, alumnus Henry Yu and research scientist Alex Kutana at Rice’s George R. Brown School of Engineering, these could facilitate nanoscale optical devices like converging lenses or collimators.
Their study appears in the American Chemical Society’s Nano Letters.
They also promise a way to achieve a Hall effect — a voltage difference across the strongly conducting graphene — that could facilitate valleytronics applications that manipulate how electrons are trapped in “valleys” in an electronic band structure.
Valleytronics are related to spintronics, in which a device’s memory bits are defined by an electron’s quantum spin state. But in valleytronics, electrons have degrees of freedom in the multiple momentum states (or valleys) they occupy. These can also be read as bits.
This is all possible because graphene, while it may be one of the strongest known structures, is pliable enough as it adheres to a surface during chemical vapor deposition.
“Substrate sculpting imparts deformation, which in turn alters the material electronic structure and changes its optical response or electric conductivity,” said Yu, now a postdoctoral researcher at Lawrence Livermore National Laboratory. “For sharper substrate features beyond the pliability of the material, one can engineer defect placements in the materials, which creates even more drastic changes in material properties.”
Yakobson compared the process to depositing a sheet of graphene on an egg crate. The bumps in the crate deform the graphene, stressing it in a way that creates an electromagnetic field even without electrical or magnetic input.
“The endless designs of substrate shapes allow for countless optical devices that can be created, making possible 2D electron optics,” Yakobson said. “This technology is a precise and efficient way of transmitting material carriers in 2D electronic devices, compared to traditional methods.”
Yakobson is the Karl F. Hasselmann Professor of Materials Science and NanoEngineering and a professor of chemistry.
The Office of Naval Research (N00014-18-1-2182) and the Army Research Office (W911NF-16-1-0255) supported the research.
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Materials provided by Rice University. Original written by Mike Williams. Note: Content may be edited for style and length. More