A newly devised cylindrical metamaterial could protect sensitive engineering equipment by isolating vibrations.
Category: materials – Page 6
Twisting sound: Scientists discover a new way to control mechanical vibrations in metamaterial
Scientists at the Advanced Science Research Center at the CUNY Graduate Center (CUNY ASRC) have discovered a way to control sound and vibrations using a concept inspired by “twistronics,” a phenomenon originally developed for electronics.
Their research, published in the journal PNAS, introduces “twistelastics”—a technique that uses tiny rotations between layers of engineered surfaces to manipulate how mechanical waves travel.
Sound and vibration control are essential for technologies like ultrasound imaging, microelectronics, and advanced sensors. Traditionally, these systems rely on fixed designs, limiting flexibility. The new approach allows engineers to reconfigure wave behavior by twisting two layers of engineered surfaces, enabling unprecedented adaptability.
Physics-informed AI excels at large-scale discovery of new materials
One of the key steps in developing new materials is property identification, which has long relied on massive amounts of experimental data and expensive equipment, limiting research efficiency. A KAIST research team has introduced a new technique that combines physical laws, which govern deformation and interaction of materials and energy, with artificial intelligence. This approach allows for rapid exploration of new materials even under data-scarce conditions and provides a foundation for accelerating design and verification across multiple engineering fields, including materials, mechanics, energy, and electronics.
Professor Seunghwa Ryu’s research group in the Department of Mechanical Engineering, in collaboration with Professor Jae Hyuk Lim’s group at Kyung Hee University and Dr. Byungki Ryu at the Korea Electrotechnology Research Institute, proposed a new method that can accurately determine material properties with only limited data. The method uses physics-informed machine learning (PIML), which directly incorporates physical laws into the AI learning process.
In the first study, the researchers focused on hyperelastic materials, such as rubber. They presented a physics-informed neural network (PINN) method that can identify both the deformation behavior and the properties of materials using only a small amount of data obtained from a single experiment. Whereas previous approaches required large, complex datasets, this research demonstrated that material characteristics can be reliably reproduced even when data is scarce, limited, or noisy.
Stable ferroaxial states offer a new type of light-controlled non-volatile memory
Ferroic materials such as ferromagnets and ferroelectrics underpin modern data storage, yet face limits: They switch slowly, or suffer from unstable polarization due to depolarizing fields respectively. A new class, ferroaxials, avoids these issues by hosting vortices of dipoles with clockwise or anticlockwise textures, but are hard to control.
Researchers at the Max-Planck-Institute for the Structure and Dynamics of Matter (MPSD) and the University of Oxford now show that bi-stable ferroaxial states can be switched with single flashes of polarized terahertz light. This enables ultrafast, light-controlled and stable switching, a platform for next-generation non-volatile data storage. The work is published in the journal Science.
Modern society relies on digital technologies, where all information is fundamentally encoded in a binary system of 0s and 1s. Consequently, any physical system capable of reliably switching between two stable states can, in principle, serve as a medium for digital data storage.
Bandages Made From Living Fungi Could Be The Future of Wound Healing
Fungi are best known for returning dead, organic matter to the Earth, but materials scientists are exploring whether they could someday help our bodies repair, in the form of special hydrogels.
To play a role in biomedical settings, a hydrogel needs a multilayered structure like our own skin, cartilage and muscles. While some engineers are working on synthetic versions that mimic biology, University of Utah scientists have found a hydrogel that literally has a life of its own.
Marquandomyces marquandii is a common species of soil mold, and a promising candidate for the job. This fungus has had a bit of an identity crisis, being misclassified as Paecilomyces marquandii until it was reassigned to its own genus in 2020. Soon, it may be able to add the role of ‘bio-integrated hydrogel’ to its resume.
Next-generation memory: Tungsten-based SOT-MRAM achieves nanosecond switching and low-power data storage
The ability to reliably switch the direction of magnetic alignment in materials, a process known as magnetization switching, is known to be central to the functioning of most memory devices. One known strategy to achieve entails the creation of a rotational force (i.e., torque) on electron spins via an electric current; a physical effect known as spin-orbit torque (SOT).
Information storage devices that rely on this effect are called spin-orbit torque magnetic random-access memories (SOT-MRAMs). These memory systems have been found to have various notable advantages, such as the ability to retain data even when their electrical power is turned off, fast switching compared to other various existing memory solutions and low power consumption.
Researchers at National Yang Ming Chiao Tung University, the Taiwan Semiconductor Manufacturing Company, the Industrial Technology Research Institute and other institutes recently developed a new SOT-MRAM based on composite materials that contain the heavy metal tungsten, which is known for its strong spin-orbit coupling. Their memory device, introduced in a paper published in Nature Electronics, could be fabricated via existing processes for the large-scale production of semiconductors.
Event Horizon Telescope images reveal new dark matter detection method
According to a new Physical Review Letters study, black holes could help solve the dark matter mystery. The shadowy regions in black hole images captured by the Event Horizon Telescope can act as ultra-sensitive detectors for the invisible material that makes up most of the universe’s matter.
Dark matter makes up roughly 85% of the universe’s matter, but scientists still don’t know what it actually is. While researchers have proposed countless ways to detect it, this study introduces black hole imaging as a fresh detection method—one that comes with some distinct benefits.
The Event Horizon Telescope’s stunning images of supermassive black holes have revealed more than just the geometry of spacetime; they’ve opened an unexpected window into the search for dark matter.