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Medical sensing technology has taken great strides in recent years, with the development of wearable devices that can track pulse, brain function, biomarkers in sweat and more. However, there is one big problem with existing wearable pressure sensors: even the slightest amount of pressure, something as light as a tight long sleeve shirt over a sensor, can throw them off track.
Texas Engineers have solved this problem, which has been vexing the field for years now. And they did it by innovating a first-ever hybrid sensing approach that allows the device to possess properties of the two predominant types of sensors in use today.
“The field of flexible pressure sensors is extremely crowded, and after two decades we hit a bottleneck because no one could solve the tradeoff between pressure and sensitivity,” said Nanshu Lu, an associate professor in the Department of Aerospace Engineering and Engineering Mechanics and the corresponding author of the new research published today in Advanced Materials. “This is the first sensor able to leverage a new hybrid mode to withstand pressure without a significant decay in sensitivity.”
Soft pressure sensors today are generally made of three layers — a deformable sensing layer sandwiched in between a pair of electrodes. These sensors generally fall into one of two categories — piezo-capacitive and piezo-resistive.
Lu’s team utilized an electrically conductive and highly porous nanocomposite as the sensing layer and added an extra insulating layer to the sensor, which gave it capabilities of both types of sensors. This new hybrid sensing is what allows it to better withstand pressure.
Typical sensors experience a 10-fold decline in sensitivity when experiencing any pressure beyond a slight touch. This sensor, applied to a test subject’s forehead, was able to withstand the pressure of a tight-fitting virtual reality headset on top of it with only a minimal loss in sensitivity. Pressure can not only cause a loss of accuracy in many sensors, but it can blunt the ability to deliver a reading at all.
“As we apply external pressure, the sensitivity drops, but is still on par with other sensors at zero pressure,” said Lu, who also has appointments in the Department of Electrical and Computer Engineering, Walker Department of Mechanical Engineering, Department of Biomedical Engineering and UT Austin’s Texas Materials Institute.
Lu has long been a pioneer in this sensing field, primarily through her electronic tattoo technology — a series of devices that are so lightweight and stretchable that they can be placed over the heart, the brain, or the muscle for extended periods with little or no discomfort.
But, Lu has even grander visions for these sensors and e-tattoos. She is working on ways to allow the sensor material to be wrapped around almost any object and give it the sensitivity of human skin. The most obvious application is wrapping it around robotic hands and fingers to give them the ability to recognize objects by touching them. But there are many other things it could do.
“The applications could be unlimited,” Lu said. “Stretchable, e-skin could be wrapped around almost any object.”
Video of Soft Pressure Sensor Breakthrough: https://www.youtube.com/watch?v=AXcGxeOYLkY
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When Kamlendra Singh flew back to Missouri from India in April, he developed a cough and fever on the plane, despite being vaccinated for COVID-19 and testing negative for the virus right before departure.
Still, Singh tested positive for COVID-19, most likely due to infection from the Delta variant, upon his arrival home in Boone County — a diagnosis other fully vaccinated people and those who have already tested positive for the contagious virus were experiencing. He wanted to know why.
Following his recovery at home, Singh, a professor in the MU College of Veterinary Medicine and Bond Life Sciences Center, teamed up with MU undergraduate student Austin Spratt, Saathvik Kannan, a freshman at Hickman High School, and Siddappa Byrareddy, a professor at the University of Nebraska Medical Center, to analyze protein sequences for more than 300,000 COVID-19 samples of two emerging variants around the world, known as Delta and Delta Plus.
Using bioinformatics tools and programming, the team identified five specific mutations that are far more prevalent in Delta Plus infections compared to Delta infections, including one mutation, K417N, that is present in all Delta Plus infections but not present in nearly any Delta infections. The findings provide important clues to researchers about the structural changes to the virus recently and highlight the need to expand the toolbox in the fight against COVID-19.
“Whether it is natural antibodies produced from previously having COVID-19 or the antibodies produced from the vaccine, we are showing structurally how dangerous and clever the virus is by being able to mutate in a way that the antibodies don’t seem to recognize and defend against these new variants,” Spratt said. “These findings help explain why there have been so many people testing positive for the Delta variants despite being vaccinated or having previously been infected with COVID-19.”
Singh explained that while COVID-19 vaccines have been effective, another possible tool in responding to the pandemic could be the development of antiviral drugs that target specific areas of the virus that remain unchanged by mutations.
“There has not yet been a vaccine for HIV due to the unpredictable variability that often comes with viruses that mutate frequently,” Singh said. “If we can develop small molecule drugs that target the part of the virus that does not mutate, that will be the ultimate solution for combatting the virus.”
“Evolutionary analysis of the Delta and Delta Plus variants of the SARS-CoV-2 viruses” was recently published in the Journal of Autoimmunity. Funding was provided by MU’s Bond Life Sciences Center and the National Strategic Research Institute at the University of Nebraska.
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Most emerging infectious diseases of humans (like COVID-19) are zoonotic — caused by viruses originating from other animal species. Identifying high-risk viruses earlier can improve research and surveillance priorities. A study publishing in PLOS Biology on September 28th by Nardus Mollentze, Simon Babayan, and Daniel Streicker at University of Glasgow, United Kingdom suggests that machine learning (a type of artifical intelligence) using viral genomes may predict the likelihood that any animal-infecting virus will infect humans, given biologically relevant exposure.
Identifying zoonotic diseases prior to emergence is a major challenge because only a small minority of the estimated 1.67 million animal viruses are able to infect humans. To develop machine learning models using viral genome sequences, the researchers first compiled a dataset of 861 virus species from 36 families. They then built machine learning models, which assigned a probability of human infection based on patterns in virus genomes. The authors then applied the best-performing model to analyze patterns in the predicted zoonotic potential of additional virus genomes sampled from a range of species.
The researchers found that viral genomes may have generalizable features that are independent of virus taxonomic relationships and may preadapt viruses to infect humans. They were able to develop machine learning models capable of identifying candidate zoonoses using viral genomes. These models have limitations, as computer models are only a preliminary step of identifying zoonotic viruses with potential to infect humans. Viruses flagged by the models will require confirmatory laboratory testing before pursuing major additional research investments. Further, while these models predict whether viruses might be able to infect humans, the ability to infect is just one part of broader zoonotic risk, which is also influenced by the virus’ virulence in humans, ability to transmit between humans, and the ecological conditions at the time of human exposure.
According to the authors, “Our findings show that the zoonotic potential of viruses can be inferred to a surprisingly large extent from their genome sequence. By highlighting viruses with the greatest potential to become zoonotic, genome-based ranking allows further ecological and virological characterisation to be targeted more effectively.”
“These findings add a crucial piece to the already surprising amount of information that we can extract from the genetic sequence of viruses using AI techniques,” Babayan adds. “A genomic sequence is typically the first, and often only, information we have on newly-discovered viruses, and the more information we can extract from it, the sooner we might identify the virus’ origins and the zoonotic risk it may pose. As more viruses are characterized, the more effective our machine learning models will become at identifying the rare viruses that ought to be closely monitored and prioritized for preemptive vaccine development.”
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A study on how structural economic risk at the occupational level is linked to long-term health outcomes of employees found that individuals in occupations characterized by high routine intensity are likely to become unemployed in the long term and have higher rates of disability and mortality, according to researchers at the Robert N. Butler Columbia Aging Center based at Columbia University Mailman School of Public Health. Until now, there has been a lack of large-scale population level analyses focusing on how one’s job is affected by technology- induced displacement and its health and social effects. The findings are published online in the journalOccupational and Environmental Medicine.
The researchers categorized all Norwegian employees in 2003 aged 33-52 in 335 occupations using the Routine Task Intensity (RTI) index, a weighted sum of selected job characteristics based on an occupation’s routine cognitive or physical tasks that can potentially be automated or outsourced. The sample was composed of 416,003 men and 376,413 women.
“Because we can follow the earnings and social security history of these workers for 15 years, through 2018, we limited the data extract to those aged 33-52 in 2003 — wage earners in their prime earnings age — and observed employment and disability status in 2018 and mortality status in 2019,” noted Vegard Skirbekk, PhD, professor of population and family health at Columbia Mailman School of Public Health, and senior author. “The key findings are robust to controlling for other factors, such as educational attainment, and persist when we compared siblings working in jobs with different levels of routine intensity. ”
A second Index — the Frey-Osborne Index — was also used to more narrowly reflect the probability that expected advances in machine-learning techniques would make it possible to automate the tasks involved in different occupations over the coming decades.
Working in an occupation with an RTI score slightly above the mean in 2003, was associated with a raised probability of being deceased in 2019, corresponding to raised mortality rates of 6.7 percent for men and 5.5 percent for women.
“Our finding matched earlier research that found declining employment in occupations with higher RTI scores,” observed Skirbekk. “While the projected impact of technological changes on labor markets varies across studies, many expect these economic changes to continue or even accelerate and encompass larger shares of the economy.”
According to Skirbekk there are several reasons why technology-induced job loss can relate to health outcomes. Holding an occupation that is being phased out over time increases the risk of employment loss and makes re-employment harder since job openings within the same occupation will tend to become scarce. Having a job where one has a higher risk of being laid off can cause stress and greater risk of anxiety and depression.
“This unique study underscores that we should pay more attention to the types of job people hold — which can have negative implications for their job prospects, health and lifespan. In the face of widespread automation, such effects could well increase in importance in the years ahead,” said Skirbekk. “Governments need to consider individuals holding jobs that are at risk, assess opportunities for retraining and reeducation, give counselling, provide economic support, offer preventive healthcare services and pay more attention to these groups of individuals as a whole.”
Co-authors are Ole Rogeberg and Bernt Bratsberg, University of Oslo.
The research was supported by the Research Council of Norway.
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Scientists from McGill University develop stronger and tougher glass, inspired by the inner layer of mollusk shells. Instead of shattering upon impact, the new material has the resiliency of plastic and could be used to improve cell phone screens in the future, among other applications.
While techniques like tempering and laminating can help reinforce glass, they are costly and no longer work once the surface is damaged. “Until now there were trade-offs between high strength, toughness, and transparency. Our new material is not only three times stronger than the normal glass, but also more than five times more fracture resistant,” says Allen Ehrlicher, an Associate Professor in the Department of Bioengineering at McGill University.
Nature as master of design
Drawing inspiration from nature, the scientist created a new glass and acrylic composite material that mimics nacre or mother of pearl. “Nature is a master of design. Studying the structure of biological materials and understanding how they work offers inspiration, and sometimes blueprints, for new materials,” says Ehrlicher.
“Amazingly, nacre has the rigidity of a stiff material and durability of a soft material, giving it the best of both worlds,” he explains. “It’s made of stiff pieces of chalk-like matter that are layered with soft proteins that are highly elastic. This structure produces exceptional strength, making it 3000 times tougher than the materials that compose it.”
The scientists took the architecture of nacre and replicated it with layers of glass flakes and acrylic, yielding an exceptionally strong yet opaque material that can be produced easily and inexpensively. They then went a step further to make the composite optically transparent. “By tuning the refractive index of the acrylic, we made it seamlessly blend with the glass to make a truly transparent composite,” says lead author Ali Amini, a Postdoctoral Researcher at McGill. As next steps, they plan to improve it by incorporating smart technology allowing the glass to change its properties, such as colour, mechanics, and conductivity.
Lost invention of flexible glass
Flexible glass is supposedly a lost invention from the time of the reign of the Roman Emperor Tiberius Caesar. According to popular historical accounts by Roman authors Gaius Plinius Secundus and Petronius, the inventor brought a drinking bowl made of the material before the Emperor. When the bowl was put to the test to break it, it only dented instead of shattering.
After the inventor swore he was the only person who knew how to produce the material, Tiberius had the man executed, fearing that the glass would devalue gold and silver because it might be more valuable.
“When I think about the story of Tiberius, I’m glad that our material innovation leads to publication rather than execution,” says Ehrlicher.
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Researchers at the University of Bath in the UK have found a way to make ‘single-crystal flake’ devices that are so thin and free of defects, they have the potential to outperform components used today in quantum computer circuits.
The study is published this month in the journal Nano Letters.
The team from the university’s Department of Physics made its discovery while exploring the junction between two layers of the superconductor niobium diselenide (NbSe?) after these layers had been cleaved apart, twisted about 30 degrees with respect to one another, then stamped back together. In cleaving, twisting and recombining the two layers, the researchers were able to build a Superconducting Quantum Interferometer Device (SQUID) — an extremely sensitive sensor used to measure incredibly tiny magnetic fields.
SQUIDs have a wide range of important applications in areas that include healthcare (as seen in cardiology and magnetoencephalography — a test that maps brain function) and mineral exploration.
SQUIDS are also the building blocks of today’s commercial quantum computers — machines that perform certain computational tasks much more rapidly than classical computers. Quantum computing is still in its infancy but in the next decade, it is likely to transform the problem-solving capacity of companies and organisations across many sectors — for instance by fast-tracking the discovery of new drugs and materials.
“Due to their atomically perfect surfaces, which are almost entirely free of defects, we see potential for our crystalline flakes to play a significant role in building quantum computers of the future,” said Professor Simon Bending, who carried out the research together with his PhD student Liam Farrar. “Also, SQUIDs are ideal for studies in biology — for instance, they are now being used to trace the path of magnetically-labelled drugs through the intestine — so we’re very excited to see how our devices could be developed in this field too.”
As Professor Bending is quick to point out, however, his work on SQUIDs made using NbSe? flakes is very much at the start of its journey. “This is a completely new and unexplored approach to making SQUIDs and a lot of research will still have to done before these applications become a reality,” he said.
Extremely thin single crystals
The flakes from which the Bath superconductors are fabricated are extremely thin single crystals (10,000 times thinner than a human hair) that bend easily, which also makes them suitable for incorporation into flexible electronics, as used in computer keyboards, optical displays, solar cells and various automotive components.
Because the bonds between layers of NbSe? are so weak, cleaved flakes — with their perfectly flat, defect-free surfaces — create atomically sharp interfaces when pushed back together again. This makes them excellent candidates for the components used in quantum computing.
While this is not the first time NbSe₂ layers have been stamped together to create a weak superconducting link, this is the first demonstration of quantum interference between two such junctions patterned in a pair of twisted flakes. This quantum interference has allowed the researchers to modulate the maximum supercurrent that can flow through their SQUIDs by applying a small magnetic field, creating an extremely sensitive field sensor. They were also able to show that the properties of their devices could be systematically tuned by varying the twist angle between the two flakes.
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The world is heading towards a trillion-sensor economy where billions of devices using multiple sensors will be connected under the umbrella of Internet-of-things. An important part of this economy is constituted of light/photo sensors, which are tiny semiconductor-based electronic components that detect light and convert them to electrical signals. Light sensors can be found everywhere around us, from household electronic gadgets and health-care equipment to optical communication systems and automobiles.
Over the years, there has been marked progress in research on photosensors. Scientists have endeavored to develop sensors that can detect a high dynamic range of lights and are easy to manufacture and energy efficient. Most light sensors used in cost-effective consumer products are energy efficient but are susceptible to noise — unwanted light information — in the external environment, which adversely affects their performance. To tackle this issue, products have been designed using light-to-frequency conversion circuits (LFCs), which show better signal to noise ratio. However, most LFCs are made of silicon-based photodetectors that can limit the range of light detection. Also, use of LFCs leads to chip area wastage, which becomes a problem when designing multi-functional electronic circuits for compact devices.
Now a team of researchers from Incheon National University, South Korea, led by Prof. Sung Hun Jin, has demonstrated a highly efficient system of photodetectors that can overcome the limitations of conventional LFCs. In their study, which was made available online on 10 June 2021 and subsequently published in volume 17, issue 26 of the journal Small, they report developing complementary photosensitive inverters with p-type single walled carbon nanotubes (SWNT) and n-type amorphous indium-gallium-zinc-oxide (a-IGZO/SWNT) thin film transistors. Prof Jin explains “Our photodetector applies a different approach with regard to the light-to-frequency conversion. We have used components that are light dependent and not voltage dependent, unlike conventional LFCs.”
The new design architecture allowed the team to design LFC with superior chip area efficiency and compact form factor, making it suitable for use in flexible electronic devices. Experiments conducted using the photosensor system indicated excellent optical properties, including high tunability and responsiveness over a broad range of light. The LFC also showed possibility of large area scalability and easy integration into state-of-the-art silicon wafer-based chips.
The LFC system developed in this study can be used to build optical sensor systems that have high-level signal integrity, as well as excellent signal processing and transmitting abilities. These promising properties make it a strong contender for application in future Internet-of-Things sensor scenarios. “LFCs based on low dimensional semiconductors will become one of the core components in the trillion sensors area. Our LFC scheme will find application in medical SpO2 detection, auto-lighting in agriculture, or in advanced displays for virtual and augmented reality” concludes Prof Jin.
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Living or biological systems cannot be easily understood using the standard laws of physics, such as thermodynamics, as scientists would for gases, liquids or solids. Living systems are active, demonstrating fascinating properties such as adapting to their environment or repairing themselves. Exploring the questions posed by living systems using computer simulations, researchers at the University of Göttingen have now discovered a novel type of ordering effect generated and sustained by a simple mechanical deformation, specifically steady shear. The results were published in PNAS.
Understanding living systems, such as tissues formed by cells, poses a significant challenge because of their unique properties, such as adaptation, self-repair and self-propulsion. Nonetheless, they can be studied using models that treat them as just an unusual, “active” form of physical matter. This can reveal extraordinary dynamical or mechanical properties. One of the puzzles is how active materials behave under shear (the deformation produced by moving the top and bottom layers sideways in opposite directions, like sliding microscope cover plates against each other). Researchers at the Institute for Theoretical Physics, University of Göttingen explored this question and discovered a novel type of ordering effect that is generated and sustained by steady shear deformation. The researchers used a computer model of self-propelling particles where each particle is driven by a propulsion force that changes direction slowly and randomly. They found that while the flow of the particles looks similar to that in ordinary liquids, there is a hidden order revealed by looking at the force directions: these tend to point towards the nearest (top or bottom) plate, while particles with sideways forces aggregate in the middle of the system.
“We were exploring the response of a model active material under steady driving, where the system is sandwiched between two walls, one stationary and the other moving to generate shear deformation. What we saw was that at a sufficiently strong driving force, an interesting ordering effect emerges,” comments Dr Rituparno Mandal, Institute for Theoretical Physics at the University of Göttingen. “We now also understand the ordering effect using a simple analytical theory and the predictions from this theory match surprisingly well with the simulation.”
Senior author Professor Peter Sollich, also from the Institute for Theoretical Physics, Universiy of Göttingen, explains, “Often an external force or driving force destroys ordering. But here the driving by shear flow is key in providing mobility to the particles that make up the active material, and they actually need this mobility to achieve the observed order. The results will open up exciting possibilities for researchers investigating the mechanical responses of living matter.”
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