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International Iberian Nanotechnology Laboratory (INL) researchers have developed a neuromorphic photonic semiconductor neuron capable of processing optical information through self-sustained oscillations. Exploring the use of light to control negative differential resistance (NDR) in a micropillar quantum resonant tunneling diode (RTD), the research indicates that this approach could lead to highly efficient light-driven neuromorphic computing systems.

Neuromorphic computing seeks to replicate the information-processing capabilities of biological neural networks. Neurons in rely on rhythmic burst firing for sensory encoding, , and network synchronization, functions that depend on oscillatory activity for signal transmission and processing.

Existing neuromorphic approaches replicate these processes using electrical, mechanical, or thermal stimuli, but optical-based systems offer advantages in speed, energy efficiency, and miniaturization. While previous research has demonstrated photonic synapses and artificial afferent nerves, these implementations require additional circuits that increase power consumption and complexity.

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For decades, atomic clocks have been the pinnacle of precision timekeeping, enabling GPS navigation, cutting-edge physics research, and tests of fundamental theories. But researchers at JILA, led by JILA and NIST Fellow and University of Colorado Boulder physics professor Jun Ye, in collaboration with the Technical University of Vienna, are pushing beyond atomic transitions to something potentially even more stable: a nuclear clock.

This clock could revolutionize timekeeping by using a uniquely low-energy transition within the nucleus of a thorium-229 atom. This transition is less sensitive to environmental disturbances than modern atomic clocks and has been proposed for tests of fundamental physics beyond the Standard Model.

This idea isn’t new in Ye’s laboratory. In fact, work in the lab on nuclear clocks began with a landmark experiment, the results of which were published as a cover article of Nature last year, where the team made the first frequency-based, quantum-state-resolved measurement of the thorium-229 nuclear transition in a thorium-doped host crystal. This achievement confirmed that thorium’s nuclear transition could be measured with enough precision to be used as a timekeeping reference.

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The use of artificial intelligence (AI) scares many people as neural networks, modeled after the human brain, are so complex that even experts do not understand them. However, the risk to society of applying opaque algorithms varies depending on the application.

While AI can cause great damage in democratic elections through the manipulation of social media, in astrophysics it at worst leads to an incorrect view of the cosmos, says Dr. Jonas Glombitza from the Erlangen Center for Astroparticle Physics (ECAP) at Friedrich-Alexander Universität Erlangen-Nürnberg (FAU).

The astrophysicist uses AI to accelerate the analysis of data from an observatory that researches cosmic radiation.

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Researchers at Ruhr University Bochum, Germany, have shed light on the structure of supercritical water. In this state, which exists at extreme temperatures and pressures, water has the properties of both a liquid and a gas at the same time. According to one theory, the water molecules form clusters, within which they are then connected by hydrogen bonds.

The Bochum-based team has now disproven this hypothesis using a combination of terahertz spectroscopy and molecular dynamics simulations. The results are published in the journal Science Advances.

The experimentalists Dr. Katja Mauelshagen, Dr. Gerhard Schwaab and Professor Martina Havenith from the Chair of Physical Chemistry II collaborated with Dr. Philipp Schienbein and Professor Dominik Marx from the Chair of Theoretical Chemistry.

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About 100 million metric tons of high-density polyethylene (HDPE), one of the world’s most commonly used plastics, are produced annually, using more than 15 times the energy needed to power New York City for a year and adding enormous amounts of plastic waste to landfills and oceans.

Cornell chemistry researchers have found ways to reduce the environmental impact of this ubiquitous —found in milk jugs, shampoo bottles, playground equipment and many other things—by developing a machine-learning model that enables manufacturers to customize and improve HDPE materials, decreasing the amount of material needed for various applications. It can also be used to boost the quality of recycled HDPE to rival new, making recycling a more practical process.

“Implementation of this approach will facilitate the design of next-generation commodity materials and enable more efficient polymer recycling, lowering the overall impact of HDPE on the environment,” said Robert DiStasio Jr., associate professor of chemistry and chemical biology in the College of Arts and Sciences (A&S).

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Interconnected materials containing networks are ubiquitous in the world around us— rubber, car tires, human and engineered tissues, woven sheets and chain mail armor. Engineers often want these networks to be as strong as possible and to resist mechanical fracture and failure.

The key property that determines the strength of a network is its intrinsic fracture energy, the lowest energy required to propagate a crack through a unit area of the surface, with the bulk of the network falling apart. As examples, the intrinsic fracture energy of polymer networks is about 10 to 100 joules per square meter, 50–500 J/m2 for elastomers used in car tires, while spider silk has an intrinsic fracture energy of 150–200 J/m2.

Until now, there has been no way to calculate the intrinsic fracture energy (IFE) for a networked material, given the mechanical behavior and connectivity of its constituents.

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“Our hope with this kind of research is to understand our own solar system, life, and ourselves in comparison to other exoplanetary systems, so we can contextualize our existence,” said William Balmer.

What can carbon dioxide in an exoplanet’s atmosphere teach us about its formation and evolution? This is what a recent study published in The Astrophysical Journal hopes to address as an international team of researchers made the first direct images of carbon dioxide in the atmospheres of two exoplanetary systems. This study has the potential to help researchers better understand the formation and evolution of exoplanet atmospheres and how this could lead to finding life as we know it, or even as we don’t know it.

For the study, the researchers used NASA’s James Webb Space Telescope (JWST) to analyze the atmospheres of exoplanets residing in the systems HR 8799 and 51 Eridani (51 Eri) with the direct imaging method. The HR 8,799 system is located approximately 135 light-years from Earth and hosts four known exoplanets whose masses range from five to nine times of Jupiter, and the 51 Eridani system is located approximately 97 light-years from Earth and hosts one known exoplanet whose mass is approximately four times of Jupiter. Both systems are very young compared to our solar system at approximately 4.6 billion years old, with HR 8,799 and 51 Eridani being approximately 30 million and 23 million years old, respectively.

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“We can hardly wait for the flyby because, as of now, Donaldjohanson’s characteristics appear very distinct from Bennu and Ryugu. Yet, we may uncover unexpected connections,” said Dr. Simone Marchi.

How old is asteroid (52246) Donaldjohanson (DJ), which is about to be studied by NASA’s Lucy spacecraft in an upcoming flyby on April 20, 2025? This is what a recent study published in The Planetary Science Journal hopes to address as an international team of researchers conducted a pre-flyby analysis of DJ with the goal of ascertaining the asteroid’s potential age. This study has the potential to help scientists better understand the formation and evolution of asteroids throughout the solar system, and specifically the main asteroid belt, which is where DJ orbits.

For the study, the researchers used ground-based telescopes and instruments to analyze the size, shape, and composition of DJ with the goal of ascertaining its relative age. For context, relative age indicates an object’s approximate age based on observational and data analysis, which contrasts an object’s absolute age that is determined from laboratory analysis with samples. Lucy will only be conducting a flyby and will not be returning samples to Earth.

In the end, the researchers not only discovered that DJ has elongated shape with estimates putting its approximate age at 150 million years old and formed when a larger asteroid broke apart. This upcoming flyby comes after the Hayabusa2 and OSIRIS-REX missions visited asteroids Ryugu and Bennu, respectively, with DJ hypothesized to orbit in the approximate regions where both Ryugu and Bennu formed.

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Imagine a world where you can have private conversations in public spaces without headphones! Researchers at Penn State have developed a way to use ultrasonic beams and 3D-printed metasurfaces to create pockets of sound that are inaudible to others.

S the vision behind a new audio technology that creates “audible enclaves” using ultrasonic beams. ‘ + s how it works: Traditional sound waves, especially low-frequency ones, tend to spread out and can t just a neat trick. The technology covers a wide range of sounds, from deep bass tones (125 Hz) to higher frequencies (up to 4 kHz), ensuring clear audio across six octave bands. It s a futuristic approach to making sound personal, targeted, and unobtrusive.”

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A new study probing quantum phenomena in neurons as they transmit messages in the brain could provide fresh insight into how our brains function.

In this project, described in the Computational and Structural Biotechnology Journal, theoretical physicist Partha Ghose from the Tagore Centre for Natural Sciences and Philosophy in India, together with theoretical neuroscientist Dimitris Pinotsis from City St George’s, University of London and the MillerLab of MIT, proved that established equations describing the classical physics of brain responses are mathematically equivalent to equations describing quantum mechanics. Ghose and Pinotsis then derived a Schrödinger-like equation specifically for neurons.

Our brains process information via a vast network containing many millions of neurons, which can each send and receive chemical and electrical signals. Information is transmitted by nerve impulses that pass from one neuron to the next, thanks to a flow of ions across the neuron’s cell membrane. This results in an experimentally detectable change in electrical potential difference across the membrane known as the “action potential” or “spike”

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