Aurelia Butler

Researchers have fabricated a magnetically driven rotary microfilter that can be used to filter particles inside a microfluidic device. They made the tiny turning filter by creating a magnetic material that could be used with a very precise 3D printing technique known as two-photon polymerization.
Microfluidic devices, also known as lab-on-a-chip devices, can be used to perform multiple laboratory functions inside a chip that usually measures a few square centimeters or less. These devices contain intricate networks of microfluidic channels and are becoming more and more complex. They may be useful for a variety of applications such as screening molecules for therapeutic potential or performing blood tests that detect disease.
“By changing the direction of external magnetic field, the microfilter we made can be remotely manipulated on demand to either filter certain-sized particles or to allow them all to pass,” said Dong Wu, a member of the research team from the University of Science and Technology of China. “This functionality could be used for many types of chemical and biological studies performed in lab-on-a-chip devices and, importantly, makes it possible for the chips to be reused.”
In The Optical Society (OSA) journal Optics Letters, Wu together with colleagues from the Hefei University of Technology and RIKEN Center for Advanced Photonics in Japan show that their new rotary microfilter filters can sort particles in a microfluidic device with high performance.
“This filter could eventually be used to sort cells of different sizes for applications such as isolating circulating tumor cells for analysis or detecting abnormally large cells that may indicate disease,” said Chaowei Wang from University of Science and Technology of China. “With further development it might even be possible to use it in devices placed inside the body for cancer detection.”
A more versatile filter
Filters with micrometer-sized holes are often used in microfluidic chips as a passive way to sort particles or cells based on sizes of the holes. However, because the number and shape of holes in the filter cannot be dynamically changed, available devices lack the flexibility to sort different types of particles or cells on demand. To expand the usefulness of microfluidic devices, the researchers developed a filter that can freely switch between modes such as selective filtering and passing.
They created the new filter using two-photon polymerization, which uses a focused femtosecond laser beam to solidify, or polymerize, a liquid light-sensitive material known as photoresist. Thanks to two-photon absorption, the polymerization can be done in a very precise manner, enabling fabrication of complex structures on the micron scale.
To make the microfilter, the researchers synthesized magnetic nanoparticles and mixed them with the photoresist. Fabricating the rotary microfilter required them to optimize the laser power density, number of pulses and scanning intervals used for polymerization. After testing its magnetically driven properties on a glass slide, they integrated the microfilter into a microfluidic device.
Multiple filtering modes
To filter larger particles, a magnetic field perpendicular to the microchannel is applied. After the filtering process is complete, the large particles can be released by applying a magnetic field that is parallel to the microchannel, which will rotate the microfilter by 90°. The filtering process can then be repeated as needed.
The researchers verified the filtering performance of the filter using polystyrene particles with diameters of 8.0 and 2.5 microns that were mixed in an alcohol solution. “It was clear that particles smaller than the pore size easily passed through microfilter while bigger ones were filtered out,” said Chenchu Zhang from University of Science and Technology of China. “When in passing mode, any larger particles captured by the filter were washed away with the fluid, which prevents filter clogging and allows reuse of the microfilter.”
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Materials provided by The Optical Society. Note: Content may be edited for style and length. More

Sometimes photos cannot truly capture a scene. How much more epic would that vacation photo of Niagara Falls be if the water were moving?
Researchers at the University of Washington have developed a deep learning method that can do just that: If given a single photo of a waterfall, the system creates a video showing that water cascading down. All that’s missing is the roar of the water and the feeling of the spray on your face.
The team’s method can animate any flowing material, including smoke and clouds. This technique produces a short video that loops seamlessly, giving the impression of endless movement. The researchers will present this approach June 22 at the Conference on Computer Vision and Pattern Recognition.
“A picture captures a moment frozen in time. But a lot of information is lost in a static image. What led to this moment, and how are things changing? Think about the last time you found yourself fixated on something really interesting — chances are, it wasn’t totally static,” said lead author Aleksander Holynski, a doctoral student in the Paul G. Allen School of Computer Science & Engineering.
“What’s special about our method is that it doesn’t require any user input or extra information,” Holynski said. “All you need is a picture. And it produces as output a high-resolution, seamlessly looping video that quite often looks like a real video.”
Developing a method that turns a single photo into a believable video has been a challenge for the field. More

A team of scientists at Nanyang Technological University, Singapore (NTU Singapore) has developed millimetre-sized robots that can be controlled using magnetic fields to perform highly manoeuvrable and dexterous manipulations. This could pave the way to possible future applications in biomedicine and manufacturing.
The research team created the miniature robots by embedding magnetic microparticles into biocompatible polymers — non-toxic materials that are harmless to humans. The robots are ‘programmed’ to execute their desired functionalities when magnetic fields are applied.
The made-in-NTU robots improve on many existing small-scale robots by optimizing their ability to move in six degrees-of-freedom (DoF) — that is, translational movement along the three spatial axes, and rotational movement about those three axes, commonly known as roll, pitch and yaw angles.
While researchers have previously created six DoF miniature robots, the new NTU miniature robots can rotate 43 times faster than them in the critical sixth DoF when their orientation is precisely controlled. They can also be made with ‘soft’ materials and thus can replicate important mechanical qualities — one type can ‘swim’ like a jellyfish, and another has a gripping ability that can precisely pick and place miniature objects.
The research by the NTU team was published in the peer-reviewed scientific journal Advanced Materials in May 2021 and is featured as the front cover of the June 10 issue.
Lead author of the study, Assistant Professor Lum Guo Zhan from the School of Mechanical and Aerospace Engineering said the crucial factor that led to the team’s achievement lie in the discovery of the ‘elusive’ third and final principal vector of these magnetic fields, which is critical for controlling such machines. More

Optical cloaking allows objects to be hidden in plain sight or to become invisible by guiding light around anything placed inside the cloak. While cloaking has been popularized in fiction, like in the “Harry Potter” books, researchers in recent years have started realizing cloaks that shield objects from view by controlling the flow of electromagnetic radiation around them.
In the Journal of Applied Physics, by AIP Publishing, researchers from the Toyota Research Institute of North America examined recent progress of developing invisibility cloaks that function in natural incoherent light and can be realized using standard optical components, part of ongoing research over the last two decades.
Invisibility cloaks potentially have a broad array of applications in sensing and display devices in warfare, surveillance, blind spot removal in vehicles, spacecraft, and highly efficient solar cells. The researchers examined blind spots that occur in vehicles, such as the windshield pillars, the stanchions that frame windshields.
“We are always looking for ways to keep drivers and passengers safe while driving,” said author Debasish Banerjee. “We started exploring whether we could make the light go around the pillar so it appeared transparent.”
Advances in metamaterials, engineered complexes of metals and dielectrics for manipulating electromagnetic waves, have opened up the possibility for realizing optical cloaks around an object by making incoming light bypass it.
Perfect optical cloaking requires the total scattering of electromagnetic waves around an object at all angles and all polarizations and over a wide frequency range, irrespective of the medium. This has not yet been achieved.
However, by simplifying the invisibility requirements, innovative work with spherical transformation cloaks, carpet cloaks, plasmonic cloaks, and mantle cloaks in narrowband microwave, infrared, and optical wavelengths has been accomplished over the last two decades.
“One of the real challenges is that we have to optimize optical elements around an object so that phase relationships are preserved,” said Banerjee.
For optimization, artificial intelligence and machine learning may help resolve certain challenges. Algortihms can help solve the necessary inverse design problem in the context of practical cloaking devices.
These can be powerful tools to predict and analyze the optical responses of these devices or detectors without time-consuming and expensive simulations, which may raise the possibility of intelligent invisibility that is adaptive to movements, shapes, and the environment.
With the fast development of both AI-aided design and additive manufacturing capabilities, it is foreseeable that flexible cloaks that could function effectively at all incident angles with a high cloaking ratio and a wide field of view could be realized and mass-produced at low cost and high efficiency.
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Materials provided by American Institute of Physics. Note: Content may be edited for style and length. More

Artificial intelligence (AI) may offer a way to accurately determine that a person is not infected with COVID-19. An international retrospective study finds that infection with SARS-CoV-2, the virus that causes COVID-19, creates subtle electrical changes in the heart. An AI-enhanced EKG can detect these changes and potentially be used as a rapid, reliable COVID-19 screening test to rule out COVID-19 infection.
The AI-enhanced EKG was able to detect COVID-19 infection in the test with a positive predictive value — people infected — of 37% and a negative predictive value — people not infected — of 91%. When additional normal control subjects were added to reflect a 5% prevalence of COVID-19 — similar to a real-world population — the negative predictive value jumped to 99.2%. The findings are published in Mayo Clinic Proceedings.
COVID-19 has a 10- to 14-day incubation period, which is long compared to other common viruses. Many people do not show symptoms of infection, and they could unknowingly put others at risk. Also, the turnaround time and clinical resources needed for current testing methods are substantial, and access can be a problem.
“If validated prospectively using smartphone electrodes, this will make it even simpler to diagnose COVID infection, highlighting what might be done with international collaborations,” says Paul Friedman, M.D., chair of Mayo Clinic’s Department of Cardiovascular Medicine in Rochester. Dr. Friedman is senior author of the study.
The realization of a global health crisis brought together stakeholders around the world to develop a tool that could address the need to rapidly, noninvasively and cost-effectively rule out the presence of acute COVID-19 infection. The study, which included data from racially diverse populations, was conducted through a global volunteer consortium spanning four continents and 14 countries.
“The lessons from this global working group showed what is feasible, and the need pushed members in industry and academia to partner in solving the complex questions of how to gather and transfer data from multiple centers with their own EKG systems, electronic health records and variable access to their own data,” says Suraj Kapa, M.D., a cardiac electrophysiologist at Mayo Clinic. “The relationships and data processing frameworks refined through this collaboration can support the development and validation of new algorithms in the future.”
The researchers selected patients with EKG data from around the time their COVID-19 diagnosis was confirmed by a genetic test for the SARS-Co-V-2 virus. These data were control-matched with similar EKG data from patients who were not infected with COVID-19. More

Researchers have discovered a new and more efficient computing method for pairing the reliability of a classical computer with the strength of a quantum system.
This new computing method opens the door to different algorithms and experiments that bring quantum researchers closer to near-term applications and discoveries of the technology.
“In the future, quantum computers could be used in a wide variety of applications including helping to remove carbon dioxide from the atmosphere, developing artificial limbs and designing more efficient pharmaceuticals,” said Christine Muschik, a principal investigator at the Institute for Quantum Computing (IQC) and a faculty member in physics and astronomy at the University of Waterloo.
The research team from IQC in partnership with the University of Innsbruck is the first to propose the measurement-based approach in a feedback loop with a regular computer, inventing a new way to tackle hard computing problems. Their method is resource-efficient and therefore can use small quantum states because they are custom-tailored to specific types of problems.
Hybrid computing, where a regular computer’s processor and a quantum co-processor are paired into a feedback loop, gives researchers a more robust and flexible approach than trying to use a quantum computer alone.
While researchers are currently building hybrid, computers based on quantum gates, Muschik’s research team was interested in the quantum computations that could be done without gates. They designed an algorithm in which a hybrid quantum-classical computation is carried out by performing a sequence of measurements on an entangled quantum state.
The team’s theoretical research is good news for quantum software developers and experimentalists because it provides a new way of thinking about optimization algorithms. The algorithm offers high error tolerance, often an issue in quantum systems, and works for a wide range of quantum systems, including photonic quantum co-processors.
Hybrid computing is a novel frontier in near-term quantum applications. By removing the reliance on quantum gates, Muschik and her team have removed the struggle with finicky and delicate resources and instead, by using entangled quantum states, they believe they will be able to design feedback loops that can be tailored to the datasets that the computers are researching in a more efficient manner.
“Quantum computers have the potential to solve problems that supercomputers can’t, but they are still experimental and fragile,” said Muschik.
This project is funded by CIFAR.
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Materials provided by University of Waterloo. Note: Content may be edited for style and length. More

Researchers from The Australian National University (ANU) have developed new technology that allows people to see clearly in the dark, revolutionising night-vision.
The first-of-its-kind thin film, described in a new article published in Advanced Photonics, is ultra-compact and one day could work on standard glasses.
The researchers say the new prototype tech, based on nanoscale crystals, could be used for defence, as well as making it safer to drive at night and walking home after dark.
The team also say the work of police and security guards — who regularly employ night vision — will be easier and safer, reducing chronic neck injuries from currently bulk night-vision devices.
“We have made the invisible visible,” lead researcher Dr Rocio Camacho Morales said.
“Our technology is able to transform infrared light, normally invisible to the human eye, and turn this into images people can clearly see — even at distance. More

Research led by the University of Kent and the STFC Rutherford Appleton Laboratory has resulted in the discovery of a new rare topological superconductor, LaPt3P. This discovery may be of huge importance to the future operations of quantum computers.
Superconductors are vital materials able to conduct electricity without any resistance when cooled below a certain temperature, making them highly desirable in a society needing to reduce its energy consumption.
Superconductors manifest quantum properties on the scale of everyday objects, making them highly attractive candidates for building computers which use quantum physics to store data and perform computing operations, and can vastly outperform even the best supercomputers in certain tasks. As a result, there is an increasing demand from leading tech companies like Google, IBM and Microsoft to make quantum computers on an industrial scale using superconductors.
However, the elementary units of quantum computers (qubits) are extremely sensitive and lose their quantum properties due to electromagnetic fields, heat and collisions with air molecules. Protection from these can be achieved by making more resilient qubits using a special class of superconductors called topological superconductors which in addition to being superconductors also host protected metallic states on their boundaries or surfaces.
Topological superconductors, such as LaPt3P, newly discovered through muon spin relaxation experiments and extensive theoretical analysis, are exceptionally rare and are of tremendous value to the future industry of quantum computing.
To ensure its properties are sample and instrument independent, two different sets of samples were prepared in the University of Warwick and in ETH Zurich. Muon experiments were then performed in two different types of muon facilities: in the ISIS Pulsed Neutron and Muon Source in the STFC Rutherford Appleton Laboratory and in PSI, Switzerland.
Dr Sudeep Kumar Ghosh, Leverhulme Early Career Fellow at Kent and Principle Investigator said: ‘This discovery of the topological superconductor LaPt3P has tremendous potential in the field of quantum computing. Discovery of such a rare and desired component demonstrates the importance of muon research for the everyday world around us.’
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Materials provided by University of Kent. Original written by Sam Wood. Note: Content may be edited for style and length. More