For years, quantum computers have lived under a huge bubble of hype, promising to revolutionize numerous fields, from medicine and battery design to materials science and cybersecurity. But realizing their potential on any serious practical level will only be possible if large numbers of qubits (the basic units of information) can interact with each other with high precision and flexibility.
One of the main things holding that back is that traditional qubits are fixed in place, meaning they can only talk to their immediate neighbors. But in a new paper published in Nature, scientists describe how they overcame this limitation by using mobile qubits that can be moved around a chip. Lars R. Schreiber at the JARA-FIT Institute for Quantum Information in Germany has also published a News & Views piece in the same journal.
Theories of quantum mechanics predict that some particles can exist in superpositions, which essentially means that they can be in more than one state at once. When a particle’s state is measured, however, this superposition appears to “collapse” into a single outcome; a phenomenon often referred to as the “measurement problem.”
In recent years, various theoretical physicists have tried to explain why and how this collapse happens. This led to the introduction of various models, such as the Continuous Spontaneous Localization (CSL) and Diósi–Penrose models.
Both these models predict that spontaneous quantum collapse would also lead to the emission of faint X-ray radiation. The experimental detection of this radiation would thus provide evidence of these theories’ validity.
A new computational method could dramatically accelerate efforts to map the body’s cells in space, according to a study published in Nature Genetics. Spatial multi-omics technologies—often described as ultra-high-resolution maps of tissues—allow scientists to see not only which genes or proteins are active in a cell, but exactly where that activity occurs. That spatial context is critical for understanding complex organs such as the brain, immune tissues and developing embryos.
Unfortunately, capturing multiple molecular layers at once remains expensive and technically challenging, said David Gate, Ph.D., assistant professor in the Ken and Ruth Davee Department of Neurology’s Division of Behavioral Neurology, who was a co-author of the study.
“In practice, investigators end up with ‘mosaic’ datasets: different slices or batches that each capture only some of the layers, often from different technologies or labs, with batch effects and missing pieces,” said Gate, who also leads the Abrams Research Center on Neurogenomics.
Contemporary artificial intelligence (AI) systems, such as the models underpinning the functioning of ChatGPT, image generators and AI-powered creative tools, draw inspiration from the human brain’s functions and organization. While many of these systems are known to perform remarkably well on specific tasks, they still work independently from the human brain.
Researchers at Princeton University set out to create a flexible electronic system that could be directly embedded with groups of living brain cells to create a hybrid biocomputing platform. The new hybrid device they developed, dubbed 3D-MIND, was introduced in a paper published in Nature Electronics.
“This work started with a growing challenge in modern AI,” Tian-Ming Fu, senior author of the paper, told Tech Xplore. “Today’s systems can do incredible things, but they consume enormous amounts of energy, so much that their power demand is starting to shape real-world infrastructure and raise environmental concerns.
As traditional computer chips reach their physical limits and artificial intelligence demands more energy than ever, University of Missouri researchers are rethinking how computers work by taking cues from the human brain. The timing is critical. Energy use from AI data centers is projected to double by the end of the decade, raising urgent questions about sustainability.
The solution may lie in neuromorphic computing, an approach that reimagines computer hardware to process information more like biological neural networks rather than conventional chips.
“One of the brain’s greatest advantages is its efficiency,” Suchi Guha, a professor of physics in Mizzou’s College of Arts and Science, said. “It performs incredibly complex tasks using about 20 watts of power—roughly the same as an old light bulb. By comparison, today’s computer architecture is extremely energy-intensive.”
In a process analogous to how solids melt into liquids, the electrons in many different metals form crystal-like patterns that can deform and melt, opening new pathways for neuromorphic computing and superconductors, University of Michigan Engineering researchers have found.
“Our work shows that these quantum structures, which are often thought to have a highly ordered structure, actually span a continuum of disorder that could be leveraged to engineer and control these materials,” said Robert Hovden, associate professor of materials science and engineering and corresponding author of the study published in Matter.
“Metallurgists often control defects, or disorder, in metals to produce specific properties,” Hovden said. “A similar approach might help us harness the potential of quantum materials in future devices. Quantum metallurgy could be the future.”
Scientists at the Department of Energy’s Oak Ridge National Laboratory have shown for the first time that ferroelectricity can be directly written into aluminum nitride using a tightly focused helium ion beam at the Center for Nanophase Materials Sciences (CNMS), a DOE Office of Science user facility at ORNL. Ferroelectric devices don’t need constant power to store data, which allows for devices that are more reliable and less power consuming than what’s currently available.
The study, published in Advanced Materials, represents a new processing approach for wurtzite III-V nitrides, a class of semiconductors already widely used in microelectronics but whose ferroelectric potential has only been recognized since 2019.
“Today, both the material and the processing method are already employed in chip manufacturing: aluminum nitride is widely used in many 5G and Wi-Fi devices, and helium ion beams are common tools to make tiny changes to circuits,” said Bogdan Dryzhakov, an ORNL postdoctoral research associate at CNMS.
A nanocrystal is an extraordinarily tiny piece of material—composed of anywhere from a few to a few thousand atoms—in which atoms are arranged in a precise, ordered structure. Think of it like taking a piece of gold and shrinking it down to the size of a few hundred atoms. It’s still gold, still crystalline, just almost incomprehensibly small.
Nanocrystals are in the transistors inside computers and smartphones, in smartphone displays and TV screens, in the gold-nanoparticle sensors that power COVID and pregnancy tests, and in the pipes of your car exhaust system, among countless other innovations.
Their small size gives them a dramatically higher ratio of surface area to volume, making them especially useful as catalysts—materials that speed up chemical reactions without being consumed in the process.
Researchers at Worcester Polytechnic Institute (WPI) have developed a solid polymer coated with harmless viruses to detect the bacteria Salmonella enterica (S. enterica), an advance that could lead to new ways of finding contamination in the food supply. The work is published in the journal ACS Applied Bio Materials.
The group, led by Yuxiang “Shawn” Liu, an associate professor in the Department of Mechanical and Materials Engineering, reports that the technology can rapidly capture and visualize foodborne bacterial contaminants in tiny fluid samples. With no need for incubation or complicated equipment in research centers, the technology has the potential to be used as a rapid biosensor in field applications and in areas with few resources.
“We have a solid surface that can be used anywhere in the food supply chain, from farm to fridge, to detect foodborne bacteria with minimum human intervention,” Liu says.
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Imagine a civilization reaches something like a Type II level, advanced enough to move through interstellar space and keep large populations alive for generations. At that stage, the challenge is developing ships that can cross the void, and also making sure the people inside them can survive radiation, isolation, and extreme travel times. That could mean heavy genetic engineering before the journey begins, changing bone density, metabolism, resistance to disease, tolerance for low gravity, or even sensory systems and respiration. But when they finally arrive, they may still find that the planet is wrong for them, maybe the air is toxic, the gravity is crushing, the temperatures are extreme, or the native chemistry is incompatible with human biology.
At that point, they face two paths. One is terraforming, which means trying to remake an entire planet into something closer to Earth. That could involve thickening or thinning an atmosphere, warming a frozen world, cooling a hot one, importing water, altering soil chemistry, introducing engineered microbes, building orbital mirrors or shades, and managing the planet for centuries or even millennia. The scale of that project is absurdly expensive, not just in money but in energy, infrastructure, labor, time, and raw materials. You are not changing a city or even a continent, you are trying to rewrite a whole world.
The other option is pantropy. Instead of forcing the planet to become Earth-like, the colonists change themselves to fit the planet. They might alter their lungs to breathe a different atmospheric mix, redesign their skin to handle harsher radiation, reduce their size for lower resource use, strengthen their bodies for higher gravity, or even become something so biologically different that they no longer look fully human. That is the core idea of pantropy, adapting the colonists to the world rather than adapting the world to the colonists.
The term was coined by James Blish, and he used it in connection with the stories collected in The Seedling Stars, especially “Surface Tension.” which was first published in 1952 in Galaxy Science Fiction.
