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Catalysts unlock pathways for chemical reactions to unfold at faster and more efficient rates, and the development of new catalytic technologies is a critical part of the green energy transition.

The Rice University lab of nanotechnology pioneer Naomi Halas has uncovered a transformative approach to harnessing the catalytic power of aluminum nanoparticles by annealing them in various gas atmospheres at high temperatures.

According to a study published in the Proceedings of the National Academy of Sciences, Rice researchers and collaborators showed that changing the structure of the oxide layer that coats the particles modifies their catalytic properties, making them a versatile tool that can be tailored to suit the needs of different contexts of use from the production of sustainable fuels to water-based reactions.

A group of Tohoku University researchers has developed a theoretical model for a high-performance spin wave reservoir computing (RC) that utilizes spintronics technology. The breakthrough moves scientists closer to realizing energy-efficient, nanoscale computing with unparalleled computational power.

Details of their findings were published in npj Spintronics on March 1, 2024.

The brain is the ultimate computer, and scientists are constantly striving to create neuromorphic devices that mimic the brain’s processing capabilities, low power consumption, and its ability to adapt to neural networks. The development of neuromorphic computing is revolutionary, allowing scientists to explore nanoscale realms, GHz speed, with low energy consumption.

The downscaling of electronic devices, such as transistors, has reached a plateau, posing challenges for semiconductor fabrication. However, a research team led by materials scientists from City University of Hong Kong (CityU) recently discovered a new strategy for developing highly versatile electronics with outstanding performance using transistors made of mixed-dimensional nanowires and nanoflakes.

This innovation paves the way for simplified chip circuit design, offering versatility and low power dissipation in future electronics. The findings, titled “Multifunctional anti-ambipolar electronics enabled by mixed-dimensional 1D GaAsSb/2D MoS₂ heterotransistors,” were published in the journal Device.

In recent decades, as the continuous scaling of transistors and integrated circuits has started to reach physical and economic limits, fabricating semiconductor devices in a controllable and cost-effective manner has become challenging. Further scaling of transistor size increases current leakage and thus power dissipation. Complex wiring networks also have an adverse impact on power consumption.

The challenge of regulating the electronic structures of metal single-atoms (M-SAs) with metal nanoparticles (M-NPs) lies in the synthesis of a definite architecture. Such a structure has strong electronic metal-support interactions and maintains electron transport channels to facilitate carbon dioxide photoreduction (CO₂PR).

In a study published in Advanced Powder Materials, a group of researchers from Zhejiang Normal University, Zhejiang A&F University and Dalian University of Technology, revealed the engineering of the electron density of Pd single atoms with twinned Pd nanoparticles assisted by strong electronic interaction of the atomic metal with the support and unveiled the underlying mechanism for expedited CO₂PR.

“As one of the most promising CO₂PR semiconductors, polymeric graphitic carbon nitride (g-C₃N₄) featured with sp² π-conjugated lamellar structures can offer electronegative nitrogen atoms to anchor M-SAs, forming active metal-nitrogen moieties (M–N_x),” explained Lei Li, lead author of the study. “However, stable M–N_x configurations forbid tunability of electronic structures of M-SA sites.”

‘Opposites charges attract; like charges repel’ is a fundamental principle of basic physics. But a new study from Oxford University, published in Nature Nanotechnology (“A charge-dependent long-ranged force drives tailored assembly of matter in solution”), has demonstrated that similarly charged particles in solution can, in fact, attract each other over long distances. Just as surprisingly, the team found that the effect is different for positively and negatively charged particles, depending on the solvent.

The study found that negatively charged silica microparticles suspended in water attracted each other to form hexagonally arranged clusters. (Image: Zhang Kang)

Besides overturning long-held beliefs, these results have immediate implications for a range of processes that involve interparticle and intermolecular interactions across various length-scales, including self-assembly, crystallisation, and phase separation.

The most popular words of 2023 were recently released, with AI Large Language Model (LLM) unquestionably topping the list. As a front-runner, ChatGPT also emerged as one of the international buzzwords of the year. These disruptive innovations in AI owe much to big data, which has played a pivotal role. Yet, AI has simultaneously presented new opportunities and challenges to the development of big data.

High-capacity data storage is indispensable in today’s digital economy. However, major storage devices like hard disk drives and semiconductor flash devices face limitations in terms of cost-effectiveness, durability, and longevity.

Optical data storage offers a promising green solution for cost-effective and long-term data storage. Nonetheless, optical data storage encounters a fundamental limitation in the spacing of adjacent recorded features, owing to the optical diffraction limit. This physical constraint not only impedes the further development of direct laser writing machines but also affects optical microscopy and storage technology.

Nanoparticles containing immiscible elements can be synthesized under certain experimental conditions.

With six approved drugs, siRNA is now an established therapeutic modality poised for expansion.

Enhancing quantum features compensates for environmental losses, amplifying particle interactions, achieving entanglement at higher scales.

One of the oldest topics of contemporary science is where to draw the line between classical and quantum physics.

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