Aurelia Butler

An international research group has engineered a new energy-generating device by combining piezoelectric composites with carbon fiber-reinforced polymer (CFRP), a commonly used material that is both light and strong. The new device transforms vibrations from the surrounding environment into electricity, providing an efficient and reliable means for self-powered sensors.
Details of the group’s research were published in the journal Nano Energy on June 13, 2023.
Energy harvesting involves converting energy from the environment into usable electrical energy and is something crucial for ensuring a sustainable future.
“Everyday items, from fridges to street lamps, are connected to the internet as part of the Internet of Things (IoT), and many of them are equipped with sensors that collect data,” says Fumio Narita, co-author of the study and professor at Tohoku University’s Graduate School of Environmental Studies. “But these IoT devices need power to function, which is challenging if they are in remote places, or if there are lots of them.”
The sun’s rays, heat, and vibration all can generate electrical power. Vibrational energy can be utilized thanks to piezoelectric materials’ ability to generate electricity when physically stressed. Meanwhile, CFRP lends itself to applications in the aerospace and automotive industries, sports equipment, and medical equipment because of its durability and lightness.
“We pondered whether a piezoelectric vibration energy harvester (PVEH), harnessing the robustness of CFRP together with a piezoelectric composite, could be a more efficient and durable means of harvesting energy,” says Narita.
The group fabricated the device using a combination of CFRP and potassium sodium niobate (KNN) nanoparticles mixed with epoxy resin. The CFRP served as both an electrode and a reinforcement substrate.
The so-called C-PVEH device lived up to its expectations. Tests and simulations revealed that it could maintain high performance even after being bent more than 100,000 times. It proved capable of storing the generated electricity and powering LED lights. Additionally, it outperformed other KNN-based polymer composites in terms of energy output density.
The C-PVEH will help propel the development of self-powered IoT sensors, leading to more energy-efficient IoT devices.
Narita and his colleagues are also excited about the technological advancements of their breakthrough. “As well as the societal benefits of our C-PVEH device, we are thrilled with the contributions we have made to the field of energy harvesting and sensor technology. The blend of excellent energy output density and high resilience can guide future research into other composite materials for diverse applications.” More

A study carried out by a research team from the Helmholtz-Zentrum Dresden-Rossendorf (HZDR), the Catalan Institute of Nanoscience and Nanotechnology (ICN2), University of Exeter Centre for Graphene Science, and TU Eindhoven demonstrates that graphene-based materials can be used to efficiently convert high-frequency signals into visible light, and that this mechanism is ultrafast and tunable, as the team presents its findings in Nano Letters. These outcomes open the path to exciting applications in near-future information and communication technologies.
The ability to convert signals from one frequency regime to another is key to various technologies, in particular in telecommunications, where, for example, data processed by electronic devices are often transmitted as optical signals through glass fibers. To enable significantly higher data transmission rates future 6G wireless communication systems will need to extend the carrier frequency above 100 gigahertz up to the terahertz range. Terahertz waves are a part of the electromagnetic spectrum that lies between microwaves and infrared light. However, terahertz waves can only be used to transport data wirelessly over very limited distances. “Therefore, a fast and controllable mechanism to convert terahertz waves into visible or infrared light will be required, which can be transported via optical fibers. Imaging and sensing technologies could also benefit from such a mechanism,” says Dr. Igor Ilyakov of the Institute of Radiation Physics at HZDR.
What is missing so far is a material that is capable of upconverting photon energies by a factor of about 1000. The team has only recently identified the strong nonlinear response of so-called Dirac quantum materials, e.g. graphene and topological insulators, to terahertz light pulses. “This manifests in the highly efficient generation of high harmonics, that is, light with a multiple of the original laser frequency. These harmonics are still within the terahertz range, however, there were also first observations of visible light emission from graphene upon infrared and terahertz excitation,” recalls Dr. Sergey Kovalev of the Institute of Radiation Physics at HZDR. “Until now, this effect has been extremely inefficient, and the underlying physical mechanism unknown.”
The mechanism behind
The new results provide a physical explanation for this mechanism and show how the light emission can be strongly enhanced by using highly doped graphene or by using a grating-graphene metamaterial — a material with a tailored structure characterized by special optical, electrical or magnetic properties. The team also observed that the conversion occurs very rapidly — on the sub-nanosecond time scale, and that it can be controlled by electrostatic gating.
“We ascribe the light frequency conversion in graphene to a terahertz-induced thermal radiation mechanism, that is, the charge carriers absorb electromagnetic energy from the incident terahertz field. The absorbed energy rapidly distributes in the material, leading to carrier heating; and finally this leads to emission of photons in the visible spectrum, quite like light emitted by any heated object,” explains Prof. Klaas-Jan Tielrooij of ICN2’s Ultrafast Dynamics in Nanoscale Systems group and Eindhoven University of Technology.
The tunability and speed of the terahertz-to-visible light conversion achieved in graphene-based materials has great potential for application in information and communication technologies. The underlying ultrafast thermodynamic mechanism could certainly produce an impact on terahertz-to-telecom interconnects, as well as in any technology that requires ultrafast frequency conversion of signals. More

Children who receive high-quality child care as babies, toddlers and preschoolers do better in science, technology, engineering and math through high school, and that link is stronger among children from low-income backgrounds, according to research published by the American Psychological Association.
“Our results suggest that caregiving quality in early childhood can build a strong foundation for a trajectory of STEM success,” said study author Andres S. Bustamante, PhD, of the University of California Irvine. “Investing in quality child care and early childhood education could help remedy the underrepresentation of racially and ethnically diverse populations in STEM fields.”
The research was published in the journal Developmental Psychology.
Many studies have demonstrated that higher quality caregiving in early childhood is associated with better school readiness for young children from low-income families. But not as many have looked at how the effects of early child care extend into high school, and even fewer have focused specifically on STEM subjects, according to Bustamante.
To investigate those questions, Bustamante and his colleagues examined data from 979 families who participated in the National Institute of Child Health and Human Development Study of Early Child Care and Youth Development, from the time of the child’s birth in 1991 until 2006.
As part of the study, trained observers visited the day cares and preschools of all the children who were enrolled for 10 or more hours per week. The observers visited when the children were 6, 15, 24, 36 and 54 months old, and rated two aspects of the child care: the extent to which the caregivers provided a warm and supportive environment and responded to children’s interests and emotions, and the amount of cognitive stimulation they provided through using rich language, asking questions to probe the children’s thinking, and providing feedback to deepen the children’s understanding of concepts.
The researchers then looked at how the students performed in STEM subjects in elementary and high school. To measure STEM success, they examined the children’s scores on the math and reasoning portions of a standardized test in grades three to five. To measure high school achievement, the researchers looked at standardized test scores and the students’ most advanced science course completed, the most advanced math course completed, GPA in science courses and GPA in math courses.
Overall, they found that both aspects of caregiving quality (more cognitive stimulation and better caregiver sensitivity-responsivity) predicted greater STEM achievement in late elementary school (third, fourth and fifth grade), which in turn predicted greater STEM achievement in high school at age 15. Sensitive and responsive caregiving in early childhood was a stronger predictor of high school STEM performance for children from low-income families compared with children from higher income families.
“Our hypothesis was that cognitive stimulation would be more strongly related to STEM outcomes because those kinds of interactions provide the foundation for exploration and inquiry, which are key in STEM learning,” Bustamante said. “However, what we saw was that the caregiver sensitivity and responsiveness was just as predictive of later STEM outcomes, highlighting the importance of children’s social emotional development and settings that support cognitive and social emotional skills.”
Overall, Bustamante said, research and theory suggest that high-quality early care practices support a strong foundation for science learning. “Together, these results highlight caregiver cognitive stimulation and sensitivity and responsiveness in early childhood as an area for investment to strengthen the STEM pipeline, particularly for children from low-income households.” More

University of Queensland researchers have used an algorithm from a video game to gain insights into the behaviour of molecules within live brain cells.
Dr Tristan Wallis and Professor Frederic Meunier from UQ’s Queensland Brain Institute came up with the idea while in lockdown during the COVID-19 pandemic.
“Combat video games use a very fast algorithm to track the trajectory of bullets, to ensure the correct target is hit on the battlefield at the right time,” Dr Wallis said.
“The technology has been optimised to be highly accurate, so the experience feels as realistic as possible.
“We thought a similar algorithm could be used to analyse tracked molecules moving within a brain cell.”
Until now, technology has only been able to detect and analyse molecules in space, and not how they behave in space and time.

“Scientists use super-resolution microscopy to look into live brain cells and record how tiny molecules within them cluster to perform specific functions,” Dr Wallis said.
“Individual proteins bounce and move in a seemingly chaotic environment, but when you observe these molecules in space and time, you start to see order within the chaos.
“It was an exciting idea — and it worked.”
Dr Wallis used coding tools to build an algorithm that is now used by several labs to gather rich data about brain cell activity.
“Rather than tracking bullets to the bad guys in video games, we applied the algorithm to observe molecules clustering together — which ones, when, where, for how long and how often,” Dr Wallis said.

“This gives us new information about how molecules perform critical functions within brain cells and how these functions can be disrupted during ageing and disease.”
Professor Meunier said the potential impact of the approach was exponential.
“Our team is already using the technology to gather valuable evidence about proteins such as Syntaxin-1A, essential for communication within brain cells,” Professor Meunier said.
“Other researchers are also applying it to different research questions.
“And we are collaborating with UQ mathematicians and statisticians to expand how we use this technology to accelerate scientific discoveries.”
Professor Meunier said it was gratifying to see the effect of a simple idea.
“We used our creativity to solve a research challenge by merging two unrelated high-tech worlds, video games and super-resolution microscopy,” he said.
“It has brought us to a new frontier in neuroscience.”
The research was published in Nature Communications. More

For many technology enthusiasts, the metaverse has the potential to transform almost every facet of human life, from work to education to entertainment. Now, new Cornell University research shows it could have environmental benefits, too.
Researchers find the metaverse could lower global surface temperature by up to 0.02 degrees Celsius before the end of the century.
The team’s paper, “Growing Metaverse Sector Can Reduce Greenhouse Gas Emissions by 10 Gt CO2e in the United States by 2050,” published June 14 in Energy and Environmental Science.
They used AI-based modeling to analyze data from key sectors — technology, energy, environment and business — to anticipate the growth of metaverse usage and the impact of its most promising applications: remote work, virtual traveling, distance learning, gaming and non-fungible tokens (NFTs).
The researchers projected metaverse expansion through 2050 along three different trajectories — slow, nominal and fast — and they looked to previous technologies, such as television, the internet and the iPhone, for insight into how quickly that adoption might occur. They also factored in the amount of energy that increasing usage would consume. The modeling suggested that within 30 years, the technology would be adopted by more than 90% of the population.
“One thing that did surprise us is that this metaverse is going to grow much quicker than what we expected,” said Fengqi You, professor in energy systems engineering and the paper’s senior author. “Look at earlier technologies — TV, for instance. It took decades to be eventually adopted by everyone. Now we are really in an age of technology explosion. Think of our smartphones. They grew very fast.”
Currently, two of the biggest industry drivers of metaverse development are Meta and Microsoft, both of which contributed to the study. Meta has been focusing on individual experiences, such as gaming, while Microsoft specializes in business solutions, including remote conferencing and distance learning.

Limiting business travel would generate the largest environmental benefit, according to You.
“Think about the decarbonization of our transportation sector,” he said. “Electric vehicles work, but you can’t drive a car to London or Tokyo. Do I really have to fly to Singapore for a conference tomorrow? That will be an interesting decision-making point for some stakeholders to consider as we move forward with these technologies with human-machine interface in a 3D virtual world.”
The paper notes that by 2050 the metaverse industry could potentially lower greenhouse gas emissions by 10 gigatons; lower atmospheric carbon dioxide concentration by 4.0 parts per million; decrease effective radiative forcing by 0.035 watts per square meter; and lower total domestic energy consumption by 92 EJ, a reduction that surpasses the annual nationwide energy consumption of all end-use sectors in previous years.
These findings could help policymakers understand how metaverse industry growth can accelerate progress towards achieving net-zero emissions targets and spur more flexible decarbonization strategies. Metaverse-based remote working, distance learning and virtual tourism could be promoted to improve air quality. In addition to alleviating air pollutant emissions, the reduction of transportation and commercial energy usage could help transform the way energy is distributed, with more energy supply going towards the residential sector.
“This mechanism is going to help, but in the end, it is going to help lower the global surface temperature by up to 0.02 degrees,” You said. “There are so many sectors in this economy. You cannot count on the metaverse to do everything. But it could do a little bit if we leverage it in a reasonable way.”
The research was supported by the National Science Foundation. More

A new artificial intelligence-based technique for measuring fluid flow around the brain’s blood vessels could have big implications for developing treatments for diseases such as Alzheimer’s.
The perivascular spaces that surround cerebral blood vessels transport water-like fluids around the brain and help sweep away waste. Alterations in the fluid flow are linked to neurological conditions, including Alzheimer’s, small vessel disease, strokes, and traumatic brain injuries but are difficult to measure in vivo.
A multidisciplinary team of mechanical engineers, neuroscientists, and computer scientists led by University of Rochester Associate Professor Douglas Kelley developed novel AI velocimetry measurements to accurately calculate brain fluid flow. The results are outlined in a study published by Proceedings of the National Academy of Sciences.
“In this study, we combined some measurements from inside the animal models with a novel AI technique that allowed us to effectively measure things that nobody’s ever been able to measure before,” says Kelley, a faculty member in Rochester’s Department of Mechanical Engineering.
The work builds upon years of experiments led by study coauthor Maiken Nedergaard, the codirector of Rochester’s Center for Translational Neuromedicine. The group has previously been able to conduct two-dimensional studies on the fluid flow in perivascular spaces by injecting tiny particles into the fluid and measuring their position and velocity over time. But scientists needed more complex measurements to understand the full intricacy of the system — and exploring such a vital, fluid system is a challenge.
To address that challenge, the team collaborated with George Karniadakis from Brown University to leverage artificial intelligence. They integrated the existing 2D data with physics-informed neural networks to create unprecedented high-resolution looks at the system.
“This is a way to reveal pressures, forces, and the three-dimensional flow rate with much more accuracy than we can otherwise do,” says Kelley. “The pressure is important because nobody knows for sure quite what pumping mechanism drives all these flows around the brain yet. This is a new field.”
The scientists conducted the research with support from the Collaborative Research in Computational Neuroscience program, the National Institutes of Health Brain Initiative, and the Army Research Office’s Multidisciplinary University Research Initiatives program. More

Researchers from the UvA Institute of Physics and ENS de Lyon have discovered how to design materials that necessarily have a point or line where the material doesn’t deform under stress, and that even remember how they have been poked or squeezed in the past. These results could be used in robotics and mechanical computers, while similar design principles could be used in quantum computers.
The outcome is a breakthrough in the field of metamaterials: designer materials whose responses are determined by their structure rather than their chemical composition. To construct a metamaterial with mechanical memory, physicists Xiaofei Guo, Marcelo Guzmán, David Carpentier, Denis Bartolo and Corentin Coulais realised that its design needs to be ‘frustrated’, and that this frustration corresponds to a new type of order, which they call non-orientable order.
Physics with a twist
A simple example of a non-orientable object is a Möbius strip, made by taking a strip of material, adding half a twist to it and then gluing its ends together. You can try this at home with a strip of paper. Following the surface of a Möbius strip with your finger, you’ll find that when you get back to your starting point, your finger will be on the other side of the paper.
A Möbius strip is non-orientable because there is no way to label the two sides of the strip in a consistent manner; the twist makes the entire surface one and the same. This is in contrast to a simple cylinder (a strip without any twists whose ends are glued together), which has a distinct inner and outer surface.
Guo and her colleagues realised that this non-orientability strongly affects how an object or metamaterial responds to being pushed or squeezed. If you place a simple cylinder and a Möbius strip on a flat surface and press down on them from above, you’ll find that the sides of the cylinder will all bulge out (or in), while the sides of the Möbius strip cannot do the same. Instead, the non-orientability of the latter ensures that there is always a point along the strip where it does not deform under pressure.

Frustration is not always a bad thing
Excitingly, this behaviour extends far beyond Möbius strips. ‘We discovered that the behaviour of non-orientable objects such as Möbius strips allows us to describe any material that is globally frustrated. These materials naturally want to be ordered, but something in their structure forbids the order to span the whole system and forces the ordered pattern to vanish at one point or line in space. There is no way to get rid of that vanishing point without cutting the structure, so it has to be there no matter what,’ explains Coulais, who leads the Machine Materials Laboratory at the University of Amsterdam.
The research team designed and 3D-printed their own mechanical metamaterial structures which exhibit the same frustrated and non-orientable behaviour as Möbius strips. Their designs are based on rings of squares connected by hinges at their corners. When these rings are squeezed, neighbouring squares will rotate in opposite directions so that their edges move closer together. The opposite rotation of neighbours makes the system’s response analogous to the anti-ferromagnetic ordering that occurs in certain magnetic materials.
Rings composed of an odd number of squares are frustrated, because there is no way for all neighbouring squares to rotate in opposite directions. Squeezed odd-numbered rings therefore exhibit non-orientable order, in which the rotation angle at one point along the ring must go to zero.
Being a feature of the overall shape of the material makes this a robust topological property. By connecting multiple metarings together, it is even possible to emulate the mechanics of higher-dimensional topological structures such as the Klein bottle.

Mechanical memory
Having an enforced point or line of zero deformation is key to endowing materials with mechanical memory. Instead of squeezing a metamaterial ring from all sides, you can press the ring at distinct points. Doing so, the order in which you press different points determines where the zero deformation point or line ends up.
This is a form of storing information. It can even be used to execute certain types of logic gates, the basis of any computer algorithm. A simple metamaterial ring can thus function as a mechanical computer.
Beyond mechanics, the results of the study suggest that non-orientability could be a robust design principle for metamaterials that can effectively store information across scales, in fields as diverse as colloidal science, photonics, magnetism, and atomic physics. It could even be useful for new types of quantum computers.
Coulais concludes: ‘Next, we want to exploit the robustness of the vanishing deformations for robotics. We believe the vanishing deformations could be used to create robotic arms and wheels with predictable bending and locomotion mechanisms.’ More