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Light-powered nano-motor winds molecular strands into chain-like structures

Threads or ropes can easily be used for braiding, knotting, and weaving. In chemistry, however, processing molecular strands in this way is an almost impossible task. This is because molecules are not only tiny, they are also constantly in motion and therefore cannot be easily touched, held or precisely shaped.

A research group at the Institute of Chemistry at Humboldt-Universität zu Berlin (HU) led by Dr. Michael Kathan has now succeeded in precisely winding two molecular strands around each other using an artificial, light-driven molecular motor, thereby creating a particularly complex structure: a catenane (from Latin “catena” = chain). Catenanes consist of two ring-shaped molecules that are intertwined like the links of a chain—without being chemically bonded to each other. The research results are published in the journal Science.

“What we have developed is basically a mini-machine that is powered by light and rotates in one direction,” says Kathan.

When space becomes time: A new look inside the BTZ black hole

Exploring the BTZ black hole in (2+1)-dimensional gravity took me down a fascinating rabbit hole, connecting ideas I never expected—like black holes and topological phases in quantum matter! When I swapped the roles of space and time in the equations (it felt like turning my map upside down when I was lost in a new city), I discovered an interior version of the solution existing alongside the familiar exterior, each with its own thermofield double state.

Particle pattern reveals how desert dust facilitates ice formation in clouds

A new study shows that natural dust particles swirling in from faraway deserts can trigger freezing of clouds in Earth’s Northern Hemisphere. This subtle mechanism influences how much sunlight clouds reflect and how they produce rain and snow—with major implications for climate projections.

A thermodynamic approach to machine learning: How optimal transport theory can improve generative models

Joint research led by Sosuke Ito of the University of Tokyo has shown that nonequilibrium thermodynamics, a branch of physics that deals with constantly changing systems, explains why optimal transport theory, a mathematical framework for the optimal change of distribution to reduce cost, makes generative models optimal. As nonequilibrium thermodynamics has yet to be fully leveraged in designing generative models, the discovery offers a novel thermodynamic approach to machine learning research. The findings were published in the journal Physical Review X.

Image generation has been improving in leaps and bounds over recent years: a video of a celebrity eating a bowl of spaghetti that represented the state of the art a couple of years ago would not even qualify as good today. The algorithms that power image generation are called diffusion models, and they contain randomness called “noise.”

During the training process, noise is introduced to the original data through diffusion dynamics. During the generation process, the model must eliminate the noise to generate new content from the noisy data. This is achieved by considering the time-reversed dynamics, as if playing the video in reverse. One piece of the art and science of building a model that produces high-quality content is specifying when and how much noise is added to the data.

Computational musicology: Tracking the changing sound of bands

Coldplay, Radiohead or R.E.M.—which band has changed their music the most over the years? Professor Nick Collins from Durham University Department of Music has used a computer to try and find the answer to this by analyzing rhythm, harmony, and sound quality (known as timbre).

New imaging method reveals how light and heat generate electricity in nanomaterials

UC Riverside researchers have unveiled a powerful new imaging technique that exposes how cutting-edge materials used in solar panels and light sensors convert light into electricity—offering a path to better, faster, and more efficient devices.

The breakthrough, published in the journal Science Advances, could lead to improvements in solar energy systems and optical communications technology. The study title is “Deciphering photocurrent mechanisms at the nanoscale in van der Waals interfaces for enhanced optoelectronic applications.”

The research team, led by associate professors Ming Liu and Ruoxue Yan of UCR’s Bourns College of Engineering, developed a three-dimensional imaging method that distinguishes between two fundamental processes by which light is transformed into electric current in quantum materials.

New quantum state of matter found at interface of exotic materials

Scientists have discovered a new way that matter can exist—one that is different from the usual states of solid, liquid, gas or plasma—at the interface of two exotic materials made into a sandwich.

The new quantum state, called quantum liquid crystal, appears to follow its own rules and offers characteristics that could pave the way for advanced technological applications, the scientists said.

In an article published in the journal Science Advances, a Rutgers-led team of researchers described an experiment that focused on the interaction between a conducting material called the Weyl semimetal and an insulating magnetic material known as spin ice when both are subjected to an extremely high magnetic field. Both materials individually are known for their unique and complex properties.

Light-based listening: Researchers develop a low-cost visual microphone

Researchers have created a microphone that listens with light instead of sound. Unlike traditional microphones, this visual microphone captures tiny vibrations on the surfaces of objects caused by sound waves and turns them into audible signals.

“Our method simplifies and reduces the cost of using light to capture sound while also enabling applications in scenarios where traditional microphones are ineffective, such as conversing through a glass window,” said research team leader Xu-Ri Yao from Beijing Institute of Technology in China. “As long as there is a way for light to pass through, sound transmission isn’t necessary.”

In the journal Optics Express, the researchers describe the new approach, which applies single-pixel imaging to sound detection for the first time. Using an optical setup without any expensive components, they demonstrate that the technique can recover sound by using the vibrations on the surfaces of everyday objects such as leaves and pieces of paper.

Measuring three-nucleon interactions to better understand nuclear data and neutron stars

Though atomic nuclei are often depicted as static clusters of protons and neutrons (nucleons), the particles are actually bustling with movement. Thus, the nucleons carry a range of momenta. Sometimes, these nucleons may even briefly engage through the strong interaction. This interaction between two nucleons can boost the momentum of both and form high-momentum nucleon pairs. This effect yields two-nucleon short-range correlations.

Experiments at the U.S. Department of Energy’s Thomas Jefferson National Accelerator Facility have studied these pairs to learn how protons and neutrons preferentially pair up at short distances. However, short-range correlations involving three or more nucleons haven’t been detected yet.

Now, in a study published in Physics Letters B, researchers used data from a 2018 experiment in Jefferson Lab’s Hall A to measure the signature of three– short-range correlations for the first time.

Controlling polymer shapes: A new generation of shape-adaptive materials

What if a complex material could reshape itself in response to a simple chemical signal? A team of physicists from the University of Vienna and the University of Edinburgh has shown that even small changes in pH value and thus in electric charge can shift the spatial arrangement of closed ring-shaped polymers (molecular chains)—by altering the balance between twist and writhe, two distinct modes of spatial deformation.

Their findings, published in Physical Review Letters, demonstrate how electric charge can be used to reshape polymers in a reversible and controllable way—opening up new possibilities for programmable, responsive materials.

With such materials, permeability and such as elasticity, yield stress and viscosity could be better controlled and precisely “programmed.”

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