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    AI breakthrough finds life-saving insights in everyday bloodwork

    Routine blood samples, such as those taken daily at any hospital and tracked over time, could help predict the severity of an injury and even provide insights into mortality after spinal cord damage, according to a recent University of Waterloo study.
    The research team utilized advanced analytics and machine learning, a type of artificial intelligence, to assess whether routine blood tests could serve as early warning signs for spinal cord injury patient outcomes.
    More than 20 million people worldwide were affected by spinal cord injury in 2019, with 930,000 new cases each year, according to the World Health Organization. Traumatic spinal cord injury often requires intensive care and is characterized by variable clinical presentations and recovery trajectories, complicating diagnosis and prognosis, especially in emergency departments and intensive care units.
    “Routine blood tests could offer doctors important and affordable information to help predict risk of death, the presence of an injury and how severe it might be,” said Dr. Abel Torres Espín, a professor in Waterloo’s School of Public Health Sciences.
    The researchers sampled hospital data from more than 2,600 patients in the U.S. They used machine learning to analyze millions of data points and discover hidden patterns in common blood measurements, such as electrolytes and immune cells, taken during the first three weeks after a spinal cord injury.
    They found that these patterns could help forecast recovery and injury severity, even without early neurological exams, which are not always reliable as they depend on a patient’s responsiveness.
    “While a single biomarker measured at a single time point can have predictive power, the broader story lies in multiple biomarkers and the changes they show over time,” said Dr. Marzieh Mussavi Rizi, a postdoctoral scholar in Torres Espín’s lab at Waterloo.

    The models, which do not rely on early neurological assessment, were accurate in predicting mortality and the severity of injury as early as one to three days after admission to the hospital, compared to standard non-specific severity measures that are often performed during the first day of arrival to intensive care.
    The research also found that accuracy increased over time as more blood tests became available. Although other measures, such as MRI and fluid omics-based biomarkers, can also provide objective data, they are not always readily accessible across medical settings. Routine blood tests, on the other hand, are economical, easy to obtain, and available in every hospital.
    “Prediction of injury severity in the first days is clinically relevant for decision-making, yet it is a challenging task through neurological assessment alone,” Torres Espín said. “We show the potential to predict whether an injury is motor complete or incomplete with routine blood data early after injury, and an increase in prediction performance as time progresses.
    “This foundational work can open new possibilities in clinical practice, allowing for better-informed decisions about treatment priorities and resource allocation in critical care settings for many physical injuries.”
    The study, Modeling trajectories of routine blood tests as dynamic biomarkers for outcome in spinal cord injury, was published in Nature’s NPJ Digital Medicine Magazine. More

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    Can meditation apps really reduce stress, anxiety, and insomnia?

    Do you have a meditation app on your smartphone, computer or wearable device? Well, you’re not alone.
    There are now thousands of meditation apps available worldwide, the top 10 of which have been collectively downloaded more than 300 million times. What’s more, early work on these digital meditation platforms shows that even relatively brief usage can lead to benefits, from reduced depression, anxiety, and stress to improved insomnia symptoms.
    “Meditation apps, such as Calm and Headspace, have been enormously popular in the commercial market,” said J. David Creswell, a health psychologist at Carnegie Mellon University and lead author of a review paper on meditation apps, published today in the journal American Psychologist. “What they’re doing now is not only engaging millions of users every day, but they’re also creating new scientific opportunities and challenges.”
    One huge boon provided by meditation apps for users is access.
    “You can imagine a farmer in rural Nebraska not having many available opportunities to go to traditional group-based meditation programs, and now they have an app in their pocket which is available 24/7,” said Creswell, who is the William S. Dietrich II Professor in Psychology and Neuroscience.
    Meditation apps also provide scientists with opportunities to scale up their research.
    “Historically, I might bring 300 irritable bowel syndrome patients into my lab and study the impacts of meditation on pain management,” said Creswell. “But now I’m thinking, how do we harness the capacity of meditation apps and wearable health sensors to study 30,000 irritable bowel syndrome patients across the world?”
    Combined with products that measure heart rate and sleep patterns, such as Fitbit and the Apple Watch, meditation apps now also have the capacity to incorporate biometrics into meditation practices like never before.

    The biggest takeaway, though, is that meditation apps are fundamentally changing the way these practices are distributed to the general public. Scientific studies of use patterns show that meditation apps account for 96 percent of overall users in the mental health app marketplace.
    “Meditation apps dominate the mental health app market,” said Creswell. “And this paper is really the first to lay out the new normal and challenge researchers and tech developers to think in new ways about the disruptive nature of these apps and their reach.”
    Meditation apps challenge users to train their minds, in small initial training doses
    As with in-person meditation training, meditation apps start by meeting users where they are. Introductory courses may focus on breathing or mindfulness, but they tend to do so in small doses, the merits of which are still being debated.
    According to the data, just 10 to 21 minutes of meditation app exercises done three times a week is enough to see measurable results.
    “Of course, that looks really different from the daily meditation practice you might get within an in-person group-based meditation program, which might be 30 to 45 minutes a day,” said Creswell.

    The a la carte nature of meditation through a smartphone app may appeal to those pressed for time or without the budget for in-person coaching sessions. Users may also find it comforting to know that they have access to guided meditation on-demand, rather than at scheduled places, days, and times.
    “Maybe you’re waiting in line at Starbucks, and you’ve got three minutes to do a brief check-in mindfulness training practice,” said Creswell.
    Finally, as meditation apps continue to evolve, Creswell believes integration of AI, such as meditation-guiding chat-bots, will only become more common, and this will offer the option of even more personalization. This could mark an important development for meditation adoption at large, as offerings go from one-size-fits all group classes to training sessions tailored to the individual.
    “People use meditation for different things, and there’s a big difference between someone looking to optimize their free-throw shooting performance and someone trying to alleviate chronic pain,” said Creswell, who has trained Olympic athletes in the past.
    The elephant in the room
    Of course, with new technology comes new challenges, and for meditation apps, continued engagement remains a huge problem.
    “The engagement problem is not specific to meditation apps,” said Creswell. “But the numbers are really sobering. Ninety-five percent of participants who download a meditation app aren’t using it after 30 days.”
    If the meditation app industry is going to succeed, it will need to find ways to keep its users engaged, as apps like Duolingo have. But overall, Creswell said the market demand is clearly there.
    “People are suffering right now. There are just unbelievably high levels of stress and loneliness in the world, and these tools have tremendous potential to help,” he said.
    “I don’t think there is ever going to be a complete replacement for a good, in-person meditation group or teacher,” said Creswell. “But I think meditation apps are a great first step for anyone who wants to dip their toes in and start training up their mindfulness skills. The initial studies show that these meditation apps help with symptom relief and even reduce stress biomarkers.” More

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    Tiny new lenses, smaller than a hair, could transform phone and drone cameras

    A new approach to manufacturing multicolor lenses could inspire a new generation of tiny, cheap, and powerful optics for portable devices such as phones and drones.
    The design uses layers of metamaterials to simultaneously focus a range of wavelengths from an unpolarized source and over a large diameter, overcoming a major limitation of metalenses, said the first author of the paper reporting the design, Mr Joshua Jordaan, from the Research School of Physics at the Australian National University and the ARC Centre of Excellence for Transformative Meta-Optical Systems (TMOS).
    “Our design has a lot of nice features that make it applicable to practical devices.”
    “It’s easy to manufacture because it has a low aspect ratio and each layer can be fabricated individually and then packaged together, it’s also polarisation insensitive, and is potentially scalable through mature semiconductor nanofabrication platforms,” Mr Jordaan said.
    The project was led by researchers from the Friedrich Schiller University Jena in Germany as part of the International Research Training Group Meta-ACTIVE. The paper reporting their design is published in Optics Express.
    Metalenses have thickness mere fractions of the width of a hair, which is orders of magnitude thinner than conventional lenses. They can be designed to have properties such as focal lengths that would be impossibly short for conventional optics.
    Initially the team attempted to focus multiple wavelengths with a single layer, but they hit up against some fundamental constraints, Mr Jordaan said.

    “It turns out the maximum group-delay attainable in a single-layer metasurface has physical limitations, and these in turn set upper bounds on the product of the numerical aperture, physical diameter and operating bandwidth.”
    “To work at the wavelength range we needed, a single layer would either have to have a very small diameter, which would defeat the purpose of the design, or basically have such a low numerical aperture that it’s hardly focusing the light at all,” he said.
    “We realized we needed a more complex structure, which then led to a multi-layer approach.”
    With the design shifted to incorporating several metalens layers, the team approached the problem with an inverse design algorithm based on shape optimization, with parameterization that meant a lot of degrees of freedom.
    They guided the software to search for metasurface shapes that, for a single wavelength, created simple resonances in both the electric and magnetic dipole, known as Huygens resonances. By employing resonances, the team were able to improve on previous designs by other groups, and develop metalens designs that were polarization independent, and had greater tolerances in manufacturing specifications – crucial in the quest to scale fabrication to industrial quantities.
    The optimization routine came up with a library of metamaterial elements in a surprising range of shapes, such as rounded squares, four-leaf clovers and propellers.

    These tiny shapes, around 300 nm tall and 1000 nm wide, spanned the full range of phase shifts, from zero to two pi, enabling the team to create a phase gradient map to achieve any arbitrary focusing pattern – although they were initially just aiming for a simple ring structure of a conventional lens.
    “We could, for example, focus different wavelengths into different locations to create a colour router,” Mr Jordaan said.
    However, the multilayer approach is limited to a maximum of around five different wavelengths, Mr Jordaan said.
    “The problem is you need structures large enough to be resonant at the longest wavelength, without getting diffraction from the shorter wavelengths,” he said.
    Within these constraints, Mr Jordaan said the ability to make metalenses to collect a lot of light will be a boon for future portable imaging systems.
    “The metalenses we have designed would be ideal for drones or earth-observation satellites, as we’ve tried to make them as small and light as possible,” he said. More

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    Scientists just made atoms talk to each other inside silicon chips

    UNSW engineers have made a significant advance in quantum computing: they created ‘quantum entangled states’ – where two separate particles become so deeply linked they no longer behave independently – using the spins of two atomic nuclei. Such states of entanglement are the key resource that gives quantum computers their edge over conventional ones.
    The research was published on Sept. 18 in the journal Science, and is an important step towards building large-scale quantum computers – one of the most exciting scientific and technological challenges of the 21st century.
    Lead author Dr Holly Stemp says the achievement unlocks the potential to build the future microchips needed for quantum computing using existing technology and manufacturing processes.
    “We succeeded in making the cleanest, most isolated quantum objects talk to each other, at the scale at which standard silicon electronic devices are currently fabricated,” she says.
    The challenge facing quantum computer engineers has been to balance two opposing needs: shielding the computing elements from external interference and noise, while still enabling them to interact to perform meaningful computations. This is why there are so many different types of hardware still in the race to be the first operating quantum computer: some are very good for performing fast operations, but suffer from noise; others are well shielded from noise, but difficult to operate and scale up.
    The UNSW team has invested on a platform that – until today – could be placed in the second camp. They have used the nuclear spin of phosphorus atoms, implanted in a silicon chip, to encode quantum information.
    “The spin of an atomic nucleus is the cleanest, most isolated quantum object one can find in the solid state,” says Scientia Professor Andrea Morello, UNSW School of Electrical Engineering & Telecommunications.

    “Over the last 15 years, our group has pioneered all the breakthroughs that made this technology a real contender in the quantum computing race. We already demonstrated that we could hold quantum information for over 30 seconds – an eternity, in the quantum world – and perform quantum logic operations with less than 1% errors.
    “We were the first in the world to achieve this in a silicon device, but it all came at a price: the same isolation that makes atomic nuclei so clean, makes it hard to connect them together in a large-scale quantum processor.”
    Until now, the only way to operate multiple atomic nuclei was for them to be placed very close together inside a solid, and to be surrounded by one and the same electron.
    “Most people think of an electron as the tiniest subatomic particle, but quantum physics tells us that it has the ability to ‘spread out’ in space, so that it can interact with multiple atomic nuclei,” says Dr Holly Stemp, who conducted this research at UNSW and is now a postdoctoral researcher at MIT in Boston.
    “Even so, the range over which the electron can spread is quite limited. Moreover, adding more nuclei to the same electron makes it very challenging to control each nucleus individually.”
    Making atomic nuclei talk through electronic ‘telephones’
    “By way of metaphor one could say that, until now, nuclei were like people placed in a sound-proof room,” Dr Stemp says.

    “They can talk to each other as long as they are all in the same room, and the conversations are really clear. But they can’t hear anything from the outside, and there’s only so many people who can fit inside the room. This mode of conversation doesn’t ‘scale’.
    “With this breakthrough, it’s as if we gave people telephones to communicate to other rooms. All the rooms are still nice and quiet on the inside, but now we can have conversations between many more people, even if they are far away.”
    The ‘telephones’ are, in fact, electrons. Mark van Blankenstein, another author on the paper, explains what’s really going on at the sub-atomic level.
    “By their ability to spread out in space, two electrons can ‘touch’ each other at quite some distance. And if each electron is directly coupled to an atomic nucleus, the nuclei can communicate through that.”
    So how far apart were the nuclei involved in the experiments?
    “The distance between our nuclei was about 20 nanometers – one thousandth of the width of a human hair,” says Dr Stemp.
    “That doesn’t sound like much, but consider this: if we scaled each nucleus to the size of a person, the distance between the nuclei would be about the same as that between Sydney and Boston!”
    She adds that 20 nanometers is the scale at which modern silicon computer chips are routinely manufactured to work in personal computers and mobile phones.
    “You have billions of silicon transistors in your pocket or in your bag right now, each one about 20 nanometers in size. This is our real technological breakthrough: getting our cleanest and most isolated quantum objects talking to each other at the same scale as existing electronic devices. This means we can adapt the manufacturing processes developed by the trillion-dollar semiconductor industry, to the construction of quantum computers based on the spins of atomic nuclei.”
    A scalable way forward
    Despite the exotic nature of the experiments, the researchers say these devices remain fundamentally compatible with the way all current computer chips are built. The phosphorus atoms were introduced in the chip by the team of Professor David Jamieson at the University of Melbourne, using an ultra-pure silicon slab supplied by Professor Kohei Itoh at Keio University in Japan.
    By removing the need for the atomic nuclei to be attached to the same electron, the UNSW team has swept aside the biggest roadblock to the scale-up of silicon quantum computers based on atomic nuclei.
    “Our method is remarkably robust and scalable. Here we just used two electrons, but in the future we can even add more electrons, and force them in an elongated shape, to spread out the nuclei even further,” Prof. Morello says.
    “Electrons are easy to move around and to ‘massage’ into shape, which means the interactions can be switched on and off quickly and precisely. That’s exactly what is needed for a scalable quantum computer.” More

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    Shocking study exposes widespread math research fraud

    An international team of authors led by Ilka Agricola, professor of mathematics at the University of Marburg, Germany, has investigated fraudulent practices in the publication of research results in mathematics on behalf of the German Mathematical Society (DMV) and the International Mathematical Union (IMU), documenting systematic fraud over many years. The results of the study were recently published on the preprint server arxiv.org and in the Notices of the American Mathematical Society (AMS) and have since caused a stir among mathematicians.
    To solve the problem, the study also provides recommendations for the publication of research results in mathematics.
    Nowadays, research quality is often no longer measured directly by the content of publications, but increasingly by commercial indicators such as the number of publications/citations by authors or the “reputation” (impact factor) of journals. These indicators are calculated in a non-transparent manner and without the involvement of the scientific community by commercial providers, who use them to boost sales of their databases worldwide. Fraudulent companies offer their services specifically to optimize these metrics. This is worthwhile for both individuals and institutions, because a higher ranking, e.g., in a university ranking, means better access to funding and (in an international context) the possibility of charging higher tuition fees and attracting more applicants. The collateral damage is a high percentage of publications whose sole purpose is to boost the indicators, but which no one reads because they contain no new scientific findings or are even flawed.
    The study cites some striking examples. For example, based on its database, the market leader for metrics, Clarivate Inc., calculated in 2019 that the university with the most world-class researchers in mathematics is a university in Taiwan — where mathematics is not even offered as a subject. Megajournals, which print anything as long as the authors pay for it, now publish more articles per year than all reputable mathematics journals (which do not require payment) combined. Fraudsters anonymously offer everything that influences key figures for sale, from articles to citations, in exchange for payment.
    “‘Fake science’ is not only annoying, it is a danger to science and society,” emphasizes IMU Secretary General Prof. Christoph Sorger. “Because you don’t know what is valid and what is not. Targeted disinformation undermines trust in science and also makes it difficult for us mathematicians to decide which results can be used as a basis for further research.” DMV President Prof. Jürg Kramer added: “The recommendations developed by the commission are a call to all of us to work toward a system change.” More

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    Cosmic simulations that once needed supercomputers now run on a laptop

    If you think a galaxy is big, compare it to the size of the Universe: it’s just a tiny dot which, together with a huge number of other tiny dots, forms clusters that aggregate into superclusters, which in turn weave into filaments threaded with voids — an immense 3D skeleton of our Universe.
    If that gives you vertigo and you’re wondering how one can understand or even “see” something so vast, the answer is: it isn’t easy. Scientists combine the physics of the Universe with data from astronomical instruments and build theoretical models, such as EFTofLSS (Effective Field Theory of Large-Scale Structure). Fed with observations, these models describe the “cosmic web” statistically and allow its key parameters to be estimated.
    Models like EFTofLSS, however, demand a lot of time and computing resources. Since the astronomical datasets at our disposal are growing exponentially, we need ways to lighten the analysis without losing precision. This is why emulators exist: they “imitate” how the models respond, but operate much faster.
    Since this is a kind of “shortcut,” what’s the risk of losing accuracy? An international team including, among others, INAF (Italy), The University of Parma (Italy) and the University of Waterloo (Canada) has published in the Journal of Cosmology and Astroparticle Physics (JCAP) a study testing the emulator Effort.jl, which they designed. It shows that Effort.jl delivers essentially the same correctness as the model it imitates — sometimes even finer detail — while running in minutes on a standard laptop instead of a supercomputer.
    “Imagine wanting to study the contents of a glass of water at the level of its microscopic components, the individual atoms, or even smaller: in theory you can. But if we wanted to describe in detail what happens when the water moves, the explosive growth of the required calculations makes it practically impossible,” explains Marco Bonici, a researcher at the University of Waterloo and first author of the study. “However, you can encode certain properties at the microscopic level and see their effect at the macroscopic level, namely the movement of the fluid in the glass. This is what an effective field theory does, that is, a model like EFTofLSS, where the water in my example is the Universe on very large scales and the microscopic components are small-scale physical processes.”
    The theoretical model statistically explains the structure that gives rise to the data collected: the astronomical observations are fed to the code, which computes a “prediction.” But this requires time and substantial compute. Given today’s data volume — and what is expected from surveys just begun or coming soon (such as DESI, which has already released its first batch of data, and Euclid) — it’s not practical to do this exhaustively every time.
    “This is why we now turn to emulators like ours, which can drastically cut time and resources,” Bonici continues. An emulator essentially mimics what the model does: its core is a neural network that learns to associate the input parameters with the model’s already-computed predictions. The network is trained on the model’s outputs and, after training, can generalize to combinations of parameters it hasn’t seen. The emulator doesn’t “understand” the physics itself: it knows the theoretical model’s responses very well and can anticipate what it would output for a new input. Effort.jl’s originality is that it further reduces the training phase by building into the algorithm knowledge we already have about how predictions change when parameters change: instead of making the network “re-learn” these, it uses them from the start. Effort.jl also uses gradients — i.e., “how much and in which direction” predictions change if you tweak a parameter by a tiny amount — another element that helps the emulator learn from far fewer examples, cutting compute needs and allowing it to run on smaller machines.
    A tool like this needs extensive validation: if the emulator doesn’t know the physics, how sure are we that its shortcut yields correct answers (i.e., the same ones the model would give)? The newly published study answers exactly this, showing that Effort.jl’s accuracy — on both simulated and real data — is in close agreement with the model. “And in some cases, where with the model you have to trim part of the analysis to speed things up, with Effort.jl we were able to include those missing pieces as well,” Bonici concludes. Effort.jl thus emerges as a valuable ally for analyzing upcoming data releases from experiments like DESI and Euclid, which promise to greatly deepen our knowledge of the Universe on large scales.
    The study “Effort.jl: a fast and differentiable emulator for the Effective Field Theory of the Large Scale Structure of the Universe” by Marco Bonici, Guido D’Amico, Julien Bel and Carmelita Carbone is available in the Journal of Cosmology and Astroparticle Physics (JCAP). More

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    Lasers just made atoms dance, unlocking the future of electronics

    Researchers at Michigan State University have figured out how to use a fast laser to wiggle atoms in a way that temporarily changes the behavior of their host material. Their novel approach could lead to smaller, and more efficient electronics — like smartphones — in the future.
    Tyler Cocker, an associate professor in the College of Natural Science, and Jose L. Mendoza-Cortes, an assistant professor in the colleges of Engineering and Natural Science, have combined the experimental and theoretical sides of quantum mechanics — the study of the strange ways atoms behave at a very small scale — to push the boundaries of what materials can do to improve electronic technologies we use every day.
    “This experience has been a reminder of what science is really like because we found materials that are working in ways that we didn’t expect,” said Cocker. “Now, we want to look at something that is going to be technologically interesting for people in the future.”
    Using a material called tungsten ditelluride, or WTe2,which is made up of a layer of tungsten, or W atoms, sandwiched between two layers of tellurium, or Te atoms, Cocker’s team conducted a series of experiments where they placed this material under a specialized microscope they built. While microscopes are typically used to look at things that are hard for the human eye to see, like individual cells, Cocker’s scanning tunneling microscope can show individual atoms on the surface of a material. It does this by moving an extremely sharp metal tip over the surface, “feeling” atoms through an electrical signal, like reading braille. While looking at the atoms on the surface of WTe2, Cocker and his team used a super-fast laser to create terahertz pulses of light that were moving at speeds of hundreds of trillions of times per second. These terahertz pulses were focused onto the tip. At the tip, the strength of the pulses was increased enormously, allowing the researchers to wiggle the top layer of atoms directly beneath the tip and gently nudge that layer out of alignment from the remaining layers underneath it. Think of it like a stack of papers with the top sheet slightly crooked.
    While the laser pulses illuminated the tip and WTe2,the top layer of the material behaved differently, exhibiting new electronic properties not observed when the laser was turned off. Cocker and his team realized the terahertz pulses together with the tip could be used like a nanoscale switch to temporarily change the electrical properties of WTe2 to upscale the next generation of devices. Cocker’s microscope could even see the atoms moving during this process and photograph the unique “on” and “off” states of the switch they had created.
    When Cocker and Mendoza-Cortes realized that they were working on similar projects from different perspectives, Cocker’s experimental side joined with Mendoza’s theoretical side of quantum mechanics. Mendoza-Cortes’ research focuses on creating computer simulations. By comparing the results of Mendoza’s quantum calculations to Cocker’s experiments, both labs yielded the same results — independently and by using different tools.
    “Our research is complementary; it’s the same observations but through different lenses,” said Mendoza-Cortes. “When our model matched the same answers and conclusions they found in their experiments, we have a better picture of what is going on.”
    The Mendoza lab computationally found that the layers of WTe2 shift by 7 picometers while they are wiggling, which is hard to observe by the specialized microscope alone. Also, they were able to confirm that the frequencies at which the atoms wiggle match between the experiment and theory, but the quantum calculations can tell which way they wiggle and by how much.

    “The movement only occurs on the topmost layer, so it is very localized,” said Daniel Maldonado-Lopez, a fourth-year graduate student in Mendoza’s lab. “This can potentially be applied in building faster and smaller electronics.”
    Cocker and Mendoza-Cortes hope this research will lead to the use of new materials, lower costs, faster speeds and greater energy efficiency for future phones and computer technology.
    “When you think about your smartphone or your laptop, all of the components that are in there are made out of a material,” said Stefanie Adams, a fourth-year graduate student in Cocker’s lab. “At some point, someone decided that’s the material we’re going use.”
    The research appeared in Nature Photonics and was supported in part through computational resources and services provided by the Institute for Cyber-Enabled Research at Michigan State University.
    Why this matters: Wiggling atoms in new quantum materials could lead to more efficient electronics that are smaller and faster. These new materials have surprising properties and could be key elements for next-generation quantum computers. More

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    Scientists build micromotors smaller than a human hair

    Researchers at the University of Gothenburg have made light-powered gears on a micrometer scale. This paves the way for the smallest on-chip motors in history, which can fit inside a strand of hair.
    Gears are everywhere – from clocks and cars to robots and wind turbines. For more than 30 years, researchers have been trying to create even smaller gears in order to construct micro-engines. But progress stalled at 0.1 millimeters, as it was not possible to build the drive trains needed to make them move any smaller.
    Researchers from Gothenburg University, among others, have now broken through this barrier by ditching traditional mechanical drive trains and instead using laser light to set the gears in motion directly.
    Gears powered by light
    In their new study, the researchers shows that microscopic machines can be driven by optical metamaterials – small, patterned structures that can capture and control light on a nanoscale. Using traditional lithography, gears with an optical metamaterial are manufactured with silicon directly on a microchip, with the gear having a diameter of a few tens of micrometers. By shining a laser on the metamaterial, the researchers can make the gear wheel spin. The intensity of the laser light controls the speed, and it is also possible to change the direction of the gear wheel by changing the polarization of the light.
    The researchers are thus close to creating micromotors.
    A new way of thinking
    “We have built a gear train in which a light-driven gear sets the entire chain in motion. The gears can also convert rotation into linear motion, perform periodic movements and control microscopic mirrors to deflect light,” says the study’s first author, Gan Wang, a researcher in soft matter physics at the University of Gothenburg.

    The ability to integrate such machines directly onto a chip and drive them with light opens up entirely new possibilities. Since laser light does not require any fixed contact with the machine and is easy to control, the micromotor can be scaled up to complex microsystems.
    “This is a fundamentally new way of thinking about mechanics on a microscale. By replacing bulky couplings with light, we can finally overcome the size barrier,” says Gan Wang.
    Cell size
    With these advances, researchers are beginning to imagine micro- and nanomachines that can control light, manipulate small particles or be integrated into future lab-on-a-chip systems. A gear wheel can be as small as 16-20 micrometers, and there are human cells of that size. Medicine is a field that is within reach, believes Gan Wang.
    “We can use the new micromotors as pumps inside the human body, for example to regulate various flows. I am also looking at how they function as valves that open and close.” More