NiO-functionalized graphene sensor detects ammonia in real time, offering a powerful tool for monitoring beef freshness and ensuring food safety.
Category: materials – Page 52
The widespread use of artificial intelligence (AI) tools designed to process large amounts of data has increased the need for better performing memory devices. The data storage solutions that could help to meet the computational demands of AI include so-called high-bandwidth memories, technologies that can increase the memory bandwidth of computer processors, speeding up the transfer of data and reducing power consumption.
Currently, flash memories are the most prominent memory solutions capable of storing information when a device is turned off (i.e., non-volatile memories). Despite their widespread use, the speed of most existing flash memories is limited and does not best support the operation of AI.
In recent years, some engineers have thus been trying to develop ultrafast flash memories that could transfer data faster and more efficiently. Two-dimensional (2D) materials have shown promise for fabricating these better performing memory devices.
In the realm of lighting and temperature measurement, advancements in material science are paving the way for significant improvements in technology and safety. Traditional methods, which combine yellow phosphors with blue chips in LEDs, have limitations such as inadequate red light components that affect color rendering and potential hazards from blue light exposure.
A team of researchers from Texas A&M University, Sandia National Lab — Livermore, and Stanford University are taking lessons from the brain to design materials for more efficient computing. The new class of materials discovered is the first of their kind – mimicking the behavior of an axon by spontaneously propagating an electrical signal as it travels along a transmission line. These findings could be critical to the future of computing and artificial intelligence.
This study was published in Nature (“Axon-like active signal transmission”).
Any electrical signal propagating in a metallic conductor loses amplitude due to the metal’s natural resistance. Modern computer processing (CPU) and graphic processing units can contain around 30 miles of fine copper wires moving electrical signals around within the chip. These losses quickly add up, requiring amplifiers to maintain the pulse integrity. These design constraints impact the performance of current interconnect-dense chips.
Orbital currents are the lesser-known cousins of spin currents. Both involve an alignment of angular momentum. But spin currents are carried by spin-polarized electrons, while orbital currents are carried by electrons in orbitals having the same angular momentum. Like their spin counterparts, orbital currents could be useful for transmitting information in so-called orbitronic devices, but researchers had expected that these currents would not travel well across material interfaces. Now Igor Lyalin and Roland Kawakami from Ohio State University have measured the flow of orbital currents across selected materials placed in multilayer structures. They find, surprisingly, that the transport of orbital currents is as good or better than the transport of spin currents for most of the sampled materials.
Orbital currents can be generated via the so-called orbital Hall effect—a surface magnetization effect that was predicted 20 years ago but directly detected only in 2023 (see Synopsis: Detection of the Orbital Hall Effect). Interest in orbital currents is growing, as they could be more effective than spin currents at switching the orientation of magnetic layers in data-storage devices.
To study orbital current transport, Lyalin and Kawakami fabricated structures consisting of chromium and nickel layers, separated by a thin spacer. For the spacer material, they tested nonmagnetic metals, ferromagnetic metals, and antiferromagnetic insulators. The researchers generated an orbital current by applying a voltage to the chromium layer, and they measured how much of this current flowed through the structures by observing a magnetization change in the nickel. They found that 12 of the 15 spacer materials transported orbital currents more efficiently than spin currents—a result that could be good news for developing future orbitronic devices, Kawakami says.
Imaging Antiferromagnetic Domains
Posted in materials
A simple light microscopy setup can map the micrometer-scale domains of a potentially useful class of magnetic materials.
Ultraviolet photons induce potassium niobate to behave like a potent solid-state refrigerant, according to new calculations.
Claudio Cazorla of the Polytechnic University of Catalonia in Spain and his collaborators have used a suite of numerical methods to discover that the archetypal ferroelectric material, potassium niobate (KNO), also exhibits a photocaloric effect: In response to ultraviolet light, KNO reversibly absorbs heat [1]. Because the effect is large and works at a wide range of temperatures, including room temperature, KNO could serve as the working medium for new cooling devices.
KNO owes its ferroelectric and photocaloric effects to its perovskite crystal structure, which features a niobium ion surrounded by an octahedral cage of oxygen ions. At low temperatures, the niobium ion is offset from the cage’s center, which induces an electric polarization (the ferroelectric effect). Above 700 K, KNO adopts a nonpolar configuration as its most stable phase.
Researchers from Monash University, part of the FLEET Center, have revealed a generic approach towards intrinsic magnetic second-order topological insulators. These materials are crucial for advancements in spintronics, an emerging field aiming at using spin degree of freedom to deliver information. Their study is published in Nano Letters.
A new software package developed by researchers at Macquarie University can accurately model the way waves—sound, water or light—are scattered when they meet complex configurations of particles.
In polymers, the competition between the folding and aggregation of chains, both at an individual level and between chains, can determine the mechanical, thermal, and conductive properties of such materials. Understanding the interplay of folding and aggregation presents a significant opportunity for the development and discovery of polymeric materials with tailored properties and functionalities.