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Blog – Page 90

Criegee intermediates (CIs)—highly reactive species formed when ozone reacts with alkenes in the atmosphere—play a crucial role in generating hydroxyl radicals (the atmosphere’s “cleansing agents”) and aerosols that impact climate and air quality. The syn-CH3CHOO is particularly important among these intermediates, accounting for 25%–79% of all CIs depending on the season.

Until now, scientists have believed that syn-CH3CHOO primarily disappeared through self-decomposition. However, in a study published in Nature Chemistry, a team led by Profs. Yang Xueming, Zhang Donghui, Dong Wenrui and Fu Bina from the Dalian Institute of Chemical Physics (DICP) of the Chinese Academy of Sciences has uncovered a surprising new pathway: syn-CH3CHOO’s reaction with is approximately 100 times faster than previously predicted by theoretical models.

Using advanced laser techniques, the researchers experimentally measured the reaction rate between syn-CH3CHOO and water vapor, and discovered the faster reaction time. To uncover the reason behind this acceleration, they constructed a high-accuracy full-dimensional (27D) potential energy surface using the fundamental invariant-neural network approach and performed full-dimensional dynamical calculations.

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An atomic clock research team from the National Time Service Center of the Chinese Academy of Sciences has proposed and implemented a compact optical clock based on quantum interference enhanced absorption spectroscopy, which is expected to play an important role in micro-positioning, navigation, timing (μPNT) and other systems.

Inspired by the successful history of the coherent population trapping (CPT)-based chip-scale microwave atomic clock and the booming of optical microcombs, a chip-scale optical clock was also proposed and demonstrated with better frequency stability and accuracy, which is mainly based on two-photon transition of Rubidium atom ensemble.

However, the typically required high cell temperatures (~100 ℃) and laser powers (~10 mW) in such a configuration are not compliant with the advent of a fully miniaturized and optical clock.

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He Qinglin’s group at the Center for Quantum Materials Science, School of Physics, has reported the first observation of non-reciprocal Coulomb drag in Chern insulators. This breakthrough opens new pathways for exploring Coulomb interactions in magnetic topological systems and enhances our understanding of quantum states in such materials. The work was published in Nature Communications.

Coulomb arises when a current in one conductor induces a measurable voltage in a nearby, electrically insulated conductor via long-range Coulomb interactions.

Chern insulators are magnetic topological materials that show a quantized Hall effect without , due to intrinsic magnetization and chiral edge states.

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Clocks on Earth are ticking a bit more regularly thanks to NIST-F4, a new atomic clock at the National Institute of Standards and Technology (NIST) campus in Boulder, Colorado.

This month, NIST researchers published an article in Metrologia establishing NIST-F4 as one of the world’s most accurate timekeepers. NIST has also submitted the clock for acceptance as a primary standard by the International Bureau of Weights and Measures (BIPM), the body that oversees the world’s time.

NIST-F4 measures an unchanging frequency in the heart of cesium atoms, the internationally agreed-upon basis for defining the second since 1967. The clock is based on a “fountain” design that represents the gold standard of accuracy in timekeeping. NIST-F4 ticks at such a steady rate that if it had started running 100 million years ago, when dinosaurs roamed, it would be off by less than a second today.

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A squishy, layered material that dramatically transforms under pressure could someday help computers store more data with less energy.

That’s according to a new study by researchers at Washington State University and the University of North Carolina at Charlotte that shows a hybrid zinc telluride-based material can undergo surprising structural changes when squeezed together like a molecular sandwich. Those changes could make it a strong candidate for , a type of ultra-fast, long-lasting data storage that works differently than the memory found in today’s devices and doesn’t need a constant power source.

The research was made possible by a X-ray diffraction system that was acquired in 2022. This specialized equipment lets researchers observe tiny structural changes in the material as they happened—all from WSU’s Pullman campus. Usually, these kinds of experiments require time at massive national facilities like the Advanced Light Source at Berkeley National Laboratory in California.

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Many atomic nuclei have a magnetic field similar to that of Earth. However, directly at the surface of a heavy nucleus such as lead or bismuth, it is trillions of times stronger than Earth’s field and more comparable to that of a neutron star. Whether we understand the behavior of an electron in such strong fields is still an open question.

A research team led by TU Darmstadt at the GSI Helmholtz Center for Heavy Ion Research has now taken an important step toward clarifying this question. Their findings have been published in Nature Physics. The results confirm the .

Hydrogen-like ions, i.e., to which only a is bound, are theoretically particularly easy to describe. In the case of heavy nuclei with a high proton number—bismuth, for example, has 83 positively charged protons in its nucleus—the strong electrical attraction binds the electron close to the nucleus and thus within this extreme . There, the electron aligns its own magnetic field with that of the nucleus like a compass needle.

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Researchers, students and science-lovers across the world now have access to the design of the globally significant SABRE South dark matter experiment in the lead up to its installation in the Stawell Underground Physics Laboratory.

“The SABRE South Technical Design Report Executive Summary” was published in the Journal of Instrumentation in April.

The paper, published by the SABRE Collaboration, details the aims of the SABRE South experiment, which will provide data from the Southern Hemisphere to corroborate results seen in the DAMA/LIBRA Collaboration in Italy.

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It would be difficult to understand the inner workings of a complex machine without ever opening it up, but this is the challenge scientists face when exploring quantum systems. Traditional methods of looking into these systems often require immense resources, making them impractical for large-scale applications.

Researchers at UC San Diego, in collaboration with colleagues from IBM Quantum, Harvard and UC Berkeley, have developed a novel approach to this problem called “robust shallow shadows.” This technique allows scientists to extract essential information from more efficiently and accurately, even in the presence of real-world noise and imperfections. The research is published in the journal Nature Communications.

Imagine casting shadows of an object from various angles and then using those shadows to reconstruct the object. By using algorithms, researchers can enhance sample efficiency and incorporate noise-mitigation techniques to produce clearer, more detailed “shadows” to characterize quantum states.

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Researchers at Rice University have developed a new machine learning (ML) algorithm that excels at interpreting the “light signatures” (optical spectra) of molecules, materials and disease biomarkers, potentially enabling faster and more precise medical diagnoses and sample analysis.

“Imagine being able to detect early signs of diseases like Alzheimer’s or COVID-19 just by shining a light on a drop of fluid or a ,” said Ziyang Wang, an electrical and computer engineering doctoral student at Rice who is a first author on a study published in ACS Nano. “Our work makes this possible by teaching computers how to better ‘read’ the signal of light scattered from tiny molecules.”

Every material or molecule interacts with light in a unique way, producing a distinct pattern, like a fingerprint. Optical spectroscopy, which entails shining a laser on a material to observe how light interacts with it, is widely used in chemistry, materials science and medicine. However, interpreting spectral data can be difficult and time-consuming, especially when differences between samples are subtle. The new algorithm, called Peak-Sensitive Elastic-net Logistic Regression (PSE-LR), is specially designed to analyze light-based data.

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Researchers at the University of Pittsburgh have created a groundbreaking tissue engineering platform using 3D-printed collagen scaffolds called CHIPS.

By mimicking natural cellular environments, they enable cells to grow, interact, and form functional tissues — a major step beyond traditional silicone-based microfluidic models. The platform not only models diseases like diabetes but could also replace animal testing in the future. Plus, their designs are freely available to fuel broader scientific innovation.

3D bioprinting: turning science fiction into science reality.

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