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Sustainable AI: Physical neural networks exploit light to train more efficiently

Artificial intelligence is now part of our daily lives, with the subsequent pressing need for larger, more complex models. However, the demand for ever-increasing power and computing capacity is rising faster than the performance traditional computers can provide.

To overcome these limitations, research is moving towards innovative technologies such as physical neural networks, analog circuits that directly exploit the laws of physics (properties of light beams, quantum phenomena) to process information. Their potential is at the heart of the study published in the journal Nature. It is the outcome of collaboration between several international institutes, including the Politecnico di Milano, the École Polytechnique Fédérale in Lausanne, Stanford University, the University of Cambridge, and the Max Planck Institute.

The article entitled “Training of Physical Neural Networks” discusses the steps of research on training physical neural networks, carried out with the collaboration of Francesco Morichetti, professor at DEIB—Department of Electronics, Information and Bioengineering, and head of the university’s Photonic Devices Lab.

Cracks in flexible electronics run deeper than expected: Study points to potential fix

From health monitors and smartwatches to foldable phones and portable solar panels, demand for flexible electronics is growing rapidly. But the durability of those devices—their ability to stand up to thousands of folds, flexes and rolls—is a significant concern.

New research by engineers from Brown University has revealed surprising details about how cracks form in multilayer flexible electronic devices. The team shows that small cracks in a device’s fragile electrode layer can drive deeper, more destructive cracks into the tougher polymer substrate layer on which the electrodes sit. The work overturns a long-held assumption that polymer substrates usually resist cracking.

“The substrate in is a bit like the foundation in your house,” said Nitin Padture, a professor of engineering at Brown and corresponding author of the study published in npj Flexible Electronics. “If it’s cracked, it compromises the mechanical integrity of the entire device. This is the first clear evidence of cracking in a device substrate caused by a brittle film on top of it.”

High-entropy alloys: How chaos takes over in layered carbides as metal diversity increases

In the tug-of-war between order and chaos within multielemental carbides, entropy eventually claims victory over enthalpy by pushing the system toward complete disorder as the diversity of elements in the material increases, as revealed in a study published in Science.

Researchers synthesized 40 layered carbide phases with composition MAlX materials (M is a transition metal, Al is for aluminum, and X is either C or N), where the number of M was between 2 and 9.

Their goal was to uncover the trends in short-range ordering and compositional disorder in so-called high– systems. They found that in carbides with fewer constituent elements, short-range order driven by enthalpy dominated. However, as the number of elements increased, entropy took control, randomizing the metal configurations.

Rolling soft electronics yields 3D brain probes for precise neuron mapping

To shed new light on the contribution of different brain regions and neural circuits to specific mental functions, neuroscientists and medical researchers rely on advanced imaging techniques and neural probes. These are electronic devices embedding electrodes, components that can measure the electrical impulses produced by neurons, which are known as spikes.

While existing probes have helped to map various networks of neurons and understand their functions, most of them have two-dimensional (2D) layouts. This is because they are made employing conventional semiconductor-based devices and fabrication strategies.

Researchers at Dartmouth College, University of Pittsburgh, Oklahoma State University and other institutes have developed a new approach that could enable the fabrication of soft three-dimensional (3D) neural probes on a large scale. Their proposed method, outlined in a paper published in Nature Electronics, entails the rolling of flat into cylindrical 3D structures.

Physicists achieve record precision in measuring proton-to-electron mass ratio with H₂⁺

The molecular hydrogen ion H₂⁺ is the simplest molecule. This simplicity makes it a perfect study object for physicists, as its properties—for example, its energy levels—can be calculated precisely. In turn, this enables theoretical predictions to be compared with experimental measurements to determine whether the theories reflect reality correctly.

Quantum calculations provide a sharper image of subatomic stress

Stress is a very real factor in the structure of our universe. Not the kind of stress that students experience when taking a test, but rather the physical stresses that affect everyday objects. Consider the stress that heavy vehicles exert on a bridge as they cross over it—it’s essential that engineers understand and consider this factor when designing new trestles. Or consider the stresses that a star experiences—this internal factor influences everything from its shine to its lifetime.

Tiny metamaterial lenses could transform imaging for smartphones, drones and satellites

A new approach to manufacturing multicolor lenses could inspire a new generation of tiny, cheap, and powerful optics for portable devices such as phones and drones.

The design uses layers of metamaterials to simultaneously focus a range of wavelengths from an unpolarized source and over a large diameter, overcoming a major limitation of metalenses, said the first author of the paper reporting the design, Joshua Jordaan, from the Research School of Physics at the Australian National University and the ARC Center of Excellence for Transformative Meta-Optical Systems (TMOS).

“Our design has a lot of nice features that make it applicable to practical devices.”

System guides light through a tiny crystal, undeterred by bumps, bends and back-reflections

Relaying a message from point A to B can be as simple as flashing a thumbs-up at a stranger in an intersection, signaling them to proceed—nonverbal, clear, and universally understood. But light-based communication is rarely that straightforward.

Photons, tiny particles of light, are fragile and unpredictable. Unlike electrons, which must be conserved in circuits, photons can scatter, split, merge into different colors, or be absorbed, meaning that the number of photons in a system isn’t fixed, even while the energy they carry remains the same. This makes guiding them through or —optical mazes—far trickier than steering electrons through copper wires, because can scatter into dead ends or vanish before reaching their destination.

Engineers often respond by obsessively refining every imperfection, polishing the maze to perfection. However, this approach can be exhausting and never fully addresses these limitations.

Achieving low resistance and high performance in magnetic tunnel junctions using high-entropy oxides

A NIMS research team has developed a magnetic tunnel junction (MTJ) featuring a tunnel barrier made of a high-entropy oxide composed of multiple metallic elements. This MTJ simultaneously demonstrated stronger perpendicular magnetization, a higher tunnel magnetoresistance (TMR) ratio (i.e., the relative change in electrical resistance when the magnetization directions of the two ferromagnetic layers switch between parallel and antiparallel alignments) and lower electrical resistance.

These properties may contribute to the development of smaller, higher-capacity and higher-performance (HDDs) and magnetoresistive random access memory (MRAM).

This research is published in Materials Today.

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