Researchers have developed a new sub-second volumetric 3D printing technique that eliminates the need to rotate the printed sample, a long-standing mechanical challenge in the field. The system, called Digital Incoherent Synthesis of Holographic Light Fields, or DISH, instead rotates the illumination using a high-speed periscope, allowing millimeter-scale structures to be printed in 0.6 seconds with about 19-micrometer resolution across a 1-centimeter depth range. The advance addresses a persistent trade-off in volumetric additive manufacturing between resolution, stability and printable volume.

Volumetric 3D printing has long hoped to fabricate entire objects simultaneously – rather than layer by layer. But established approaches, such as computed axial lithography, typically rotate the resin container during exposure.

Fast rotation introduces vibration and alignment errors. Slow rotation, meanwhile, requires highly viscous resins, often thousands of centipoise, to prevent features from drifting before polymerization completes.

When it comes to optics, higher resolution demands higher numerical aperture (NA) objectives. Yet higher NA optics come with a shallow depth of field.

The system used in the study has an intrinsic NA of 0.055 at 405 nm, with a native depth-of-field of roughly 0.4 mm. That’s far smaller than the centimetre-scale volumes desirable for practical manufacturing. 

DISH tackles both precision and scale at once.

In their method, instead of moving the resin container the researchers mounted a rotating periscope on a hollow stage to deliver synchronized angular illumination while keeping the sample stationary.

A 405 nm coherent laser is modulated by a Digital Micromirror Device operating at 17 kHz, projecting optimized binary patterns as the periscope rotates at speeds up to 10 revolutions per second.

The demonstrated sub-second fabrication corresponds to the specific exposure timing used in the reported experiments.

The team abandoned conventional ray-based approximations and implemented a wave-optics model that explicitly incorporates diffraction and refraction at the air–material interface.

A coarse-to-fine iterative optimization algorithm generates projection patterns that maintain intensity modulation well beyond the native focal plane.

An adaptive calibration scheme using two orthogonal cameras corrects single-pixel misalignments in the synthesized 3D light field, improving angular registration and exposure fidelity.

Performance tests show that DISH maintains approximately 19 μm feature fidelity across a 1 cm depth range, far exceeding the objective’s intrinsic 0.4 mm depth of field.

Relief-structure experiments demonstrated approximately 11 μm uniform linewidth across the full centimeter span, while the smallest independently resolved positive feature measured 12 μm.

Comparative tests against conventional back-projection approaches showed sharper edges and improved consistency, particularly in off-center regions where optical blur typically increases.

The single-sided illumination geometry does introduce a missing-cone trade-off that slightly affects axial resolution. The authors note that alternative periscope geometries could mitigate this limitation in future implementations.

One of the more practically significant findings is material compatibility. The system printed successfully in aqueous solutions of polyethylene glycol diacrylate with viscosities as low as 4.7 cP. Because polymerization completes within 0.6 seconds, gravitational drift occurs only after solidification.

By contrast, conventional volumetric systems often require viscosities between 6,000 and 10,000 cP to maintain positional stability during slower exposures.

The researchers also demonstrated printing in higher-viscosity resins and bio-derived hydrogels, including gelatin methacrylate (GelMA) and silk fibroin methacrylate (SilMA).

The single-sided geometry further enables in situ fabrication on fixed substrates and within confined environments such as petri dishes.

Integration with a fluidic channel allowed successive fabrication of multiple structures, pointing toward continuous production workflows.

The authors estimate voxel rates on the order of 1.25 × 108/second, calculated for a defined voxel size and build volume. They suggest that higher-power lasers and faster modulation hardware could further increase build rates.

Surface analysis indicates that inclined projection reduces the prominence of stripe-like speckle artefacts compared with perpendicular illumination systems.

However, the hologram optimization process currently requires substantial offline computation. The authors propose GPU acceleration or neural-network-based approaches as pathways to reduce processing time and enable more automated deployment.

By decoupling angular illumination from sample motion and synthesizing holographic light fields through wave-optics modeling, DISH demonstrates a way to extend effective depth performance without sacrificing resolution.

While industrial deployment remains prospective, the work outlines a credible pathway toward faster, continuous volumetric manufacturing using both acrylate-based systems and selected biomaterials.

Future efforts are likely to focus on accelerating hologram computation, refining optical geometries to address missing-cone effects, and scaling projection hardware.

For more information: Nature

Researchers have long sought to make semiconductors—essential for computer chips and solar cells—function as superconductors, which can carry electricity without resistance for faster, more efficient performance. This has been difficult because it requires a precise atomic structure that enables free electron movement. Now, an international team has achieved a breakthrough by creating a form of germanium that exhibits superconductivity, allowing electric currents to flow indefinitely without energy loss. This advancement could significantly enhance electronic and quantum devices while reducing power consumption.

“Establishing superconductivity in germanium, which is already widely used in computer chips and fiber optics, can potentially revolutionize scores of consumer products and industrial technologies,” explains Javad Shabani, a physicist at New York University and director of its Center of Quantum Information Physics and Quantum Institute.

Peter Jacobson, a physicist at the University of Queensland, adds that the findings could accelerate progress in building practical quantum systems. “These materials could underpin future quantum circuits, sensors, and low-power cryogenic electronics, all of which need clean interfaces between superconducting and semiconducting regions,” he says. “Germanium is already a workhorse material for advanced semiconductor technologies, so by showing it can also become superconducting under controlled growth conditions there’s now potential for scalable, foundry-ready quantum devices.”

Germanium and silicon, both group IV elements with diamond-like crystal structures, occupy a unique position between metals and insulators. Their versatility and durability make them central to modern manufacturing. To induce superconductivity in such elements, scientists must carefully alter their atomic structure to increase the number of electrons available for conduction. These electrons then pair up and move through the material without resistance — a process that is notoriously difficult to fine-tune on the atomic scale.

In the new study, researchers developed germanium films heavily infused with gallium, a softer element commonly used in electronics. This technique, known as “doping,” has long been used to modify a semiconductor’s electrical behavior. Normally, high levels of gallium destabilize the crystal, preventing superconductivity.

The team overcame this limitation using advanced X-ray methods to guide a refined process that encourages gallium atoms to take the place of germanium atoms in the crystal lattice. Although this substitution slightly distorts the crystal, it preserves its overall stability and allows it to carry current with zero resistance at 3.5 Kelvin (about -453 degrees Fahrenheit), confirming that it had become superconducting.

“Rather than ion implantation, molecular beam epitaxy was used to precisely incorporate gallium atoms into the germanium’s crystal lattice,” says Julian Steele, a physicist at the University of Queensland and a co-author of the study. “Using epitaxy — growing thin crystal layers — means we can finally achieve the structural precision needed to understand and control how superconductivity emerges in these materials.”

As Shabani notes, “This works because group IV elements don’t naturally superconduct under normal conditions, but modifying their crystal structure enables the formation of electron pairings that allow superconductivity.”

For more information: Nature Nanotechnology

Image: Josephson junction structures—quantum devices made of two superconductors and a thin non-superconducting barrier—using different forms of germanium (Ge): super-Ge (in gold), semiconducting Ge (in blue), and super-Ge on wafer-level scale. Millions of Josephson junction pixels (10 micrometer square) can be created with this new material stack on wafer scale. Inset shows crystalline form of Super-Ge on the same matrix of semiconductor Ge, a key for crystalline Josephson junction. Credit: Patrick Strohbeen/NYU

Scientists have created an ultra-thin, paper-like LED that emits a warm, sunlike glow by precisely blending red, yellow-green, and blue quantum dots to mimic natural sunlight. This breakthrough offers improved color accuracy and reduced eye strain, with potential applications in home lighting, electronic displays, and workspaces. Unlike traditional bulky bulbs, this slender design could transform how we light our environments while helping minimize sleep disruption from harsh artificial light.

“This work demonstrates the feasibility of ultra-thin, large-area quantum dot LEDs that closely match the solar spectrum,” says Xianghua Wang, a corresponding author of the study. “These devices could enable next-generation eye-friendly displays, adaptive indoor lighting, and even wavelength-tunable sources for horticulture or well-being applications.”

Many people prefer indoor lighting that feels natural and soothing. Earlier approaches achieved this effect with flexible LEDs that used red and yellow phosphorescent dyes to create a candle-like warmth. A newer alternative relies on quantum dots—tiny semiconductor particles that transform electrical energy into colored light. Some research teams have already used quantum dots to make white LEDs, but replicating the complete spectrum of sunlight has remained difficult, particularly in the yellow and green regions where sunlight is strongest. To address this challenge, Lei Chen and colleagues developed quantum dots that could recreate that balanced, sunlike glow in a thin, white quantum dot LED (QLED). Meanwhile, Wang’s group proposed an efficient conductive material design that could operate effectively at relatively low voltages.

The team began by synthesizing red, yellow-green, and blue quantum dots coated with zinc-sulfur shells. They determined the precise color ratio needed to match the spectrum of natural sunlight as closely as possible. Next, they assembled the QLED on an indium tin oxide glass substrate, layering conductive polymers, the quantum dot blend, metal oxide particles, and finally a top coating of aluminum or silver. The quantum dot layer measured only a few dozen nanometers in thickness—much thinner than standard color conversion layers—resulting in a white QLED with an overall profile comparable to wallpaper.

In initial tests, the thin QLED performed best under a 11.5-volt (V) power supply, giving off the maxmium bright, warm white light. The emitted light had more intensity in red wavelengths and less intensity in blue wavelengths, which is better for sleep and eye health, according to the researchers. Objects illuminated by the QLED should appear close to their true colors, scoring over 92% on the color rendering index.

In further experiments, the researchers made 26 white QLED devices, using the same quantum dots but different electrically conductive materials to optimize the operating voltage. These light sources required only 8 V to reach maximum light output, and about 80% exceeded the target brightness for computer monitors.

For more information: ACS Applied Materials

Image: A paper-thin device uses quantum dots, similar to those described in this work, to light up LEDs. Credit: Lin Zhou, Xianghua Wang

Scientists have directly imaged a rare atomic vibration known as a phason—a phenomenon long theorized but never observed—within a twisted two-dimensional material called tungsten diselenide. These ultra-thin materials, just a few atoms thick, can be stacked in unusual configurations that produce entirely new physical behaviors. Using a cutting-edge technique called electron ptychography, researchers captured the most precise images of individual atoms to date, revealing how phasons vary with atomic arrangement and opening new possibilities for future electronic technologies.

They are only a special case of a broader category of moiré phonons, the result of when two layers of 2D material are shifted slightly one from the other. That fold between the two creates a moiré superlattice—a larger periodic structure that gives rise to unique thermal and electronic behavior. Phasons are an extremely soft, low-frequency variety of these phonons.

Even though phonons and phasons are not seen, their effect is widespread. Heat is atomic vibration in itself, and an understanding of such patterns is required if one expects to have any control over heat transfer in electronics. Greater control could imply materials that cool faster or suck heat off sensitive parts.

You can’t just get rid of phasons; that’s the blessing and curse,” said Pinshane Huang, a professor of materials science and engineering at the University of Illinois at Urbana-Champaign and lead author of the paper. “They’ve always been hiding in plain sight, changing the properties of 2D moiré materials.”

Phasons had mystified scientists for decades. They were thought to belong in theoretical models only, but no one had concrete proof. Not until Huang teamed up with Yichao Zhang, a postdoctoral researcher of nanoscale heat conduction. Their task: to freeze the blur of atomic movement created by heat.

What our primary goal was, was to see heat when looking at an atom,” Huang explained. “What this does is get so fantastic spatial resolution that vibrations of the atoms have something to do with how fuzzy the atoms appear,” she said. “These are tiny movements, and we can basically look at one atom at a time and see its heat-related motion.”.

To do this, the team utilized electron ptychography, a new imaging method with a resolution of less than 15 picometers. That is about one-thousandth the width of an individual atom. It allowed the team to see the width, shape, and movement of atoms in twisted bilayer tungsten diselenide, or WSe₂.

“Back when I started out, we figured the highest resolution you could get was maybe a little bit less than an angstrom,” Huang said. “But once ptychography arrived on the scene, we were starting to see resolution numbers as low as 0.2 angstroms,” she continued. “That put us thinking, ‘Well, heat gets atoms jigged around about 0.05 angstroms,’ she said. “Now that we can actually see heat, it shows what a giant jump in resolution can do for what microscopes can do,” she continued.

Twisted structures are important because they alter the local atomic environment in strong and unexpected manners. When one layer is twisted against another in bilayer materials such as WSe₂, there is a mismatch in the grids of atoms. That mismatch creates new areas—some with atoms close together and others not so close.

When researchers mapped these helical regions, they found more vibrations in some areas. Vibrations were especially strong around solitons, where solitons are borders between different stacking modes. AA-stacked regions, in which atoms lie atop each other, also showed more intense vibrations.

By integrating electron ptychography with lattice dynamics and molecular dynamics simulations, the scientists made a robust conclusion. Phasons were discovered by them as the main culprit behind thermal vibration in low-angle twisted bilayers. This tells us that the moiré pattern is not just an illusion—it plays a pivotal role in determining how heat traverses through the material. These findings provide new doors to investigate and even control heat in 2D materials at the atomic level.

Phasons are tiny, but their potential effect could be huge. Controlling the skill of sensing and studying these vibrations could change the way electronics are designed in the future. “One potential application of this technique is creating materials that are better heat conductors,” said Zhang. “We can look at one atom and find a defect that keeps the material from cooling more efficiently,” he said.

This could result in better means of atomic-level thermal control,” he added. “To watch individual atoms and see how they react to heat will tell us some very important things,” he said.

Twisted 2D materials are already being researched for use in transistors, sensors, and quantum computing hardware. Adding heat behavior to that research means engineers can create entire devices at the atomic level. Such devices would be able to be made smaller, faster, and much more efficient than today’s electronics.

Perhaps most exciting is the manner in which this finding reconciles theory with direct observation. Phasons were previously hypothetical, known by equations and models alone. Now, they are observable in real time.

Using equipment like electron ptychography, even the slightest motion of the atoms can be watched and measured. Science no longer needs to speculate about what atoms do—it’s watching them in plain sight, one vibration at a time.

For more information: Science

Image: (left) atoms present in the 2D material. (right) photos of single atoms. (CREDIT: The Grainger College of Engineering)

Lightweight cellular materials are essential to the performance of many industrial products, but defects during fabrication can compromise their effectiveness. To address this, a UC Berkeley-led team has developed GraphMetaMat, an AI-powered framework that uses deep learning to efficiently design 3D truss metamaterials with exceptional mechanical and acoustic properties, while reducing their vulnerability to manufacturing flaws and improving their overall usability.

“Until now, most of the work done in AI and materials design has been in the theoretical and computational domain, where they give you the design that performs well under ideal conditions,” said Xiaoyu (Rayne) Zheng, associate professor of materials science and engineering and the study’s principal investigator. “GraphMetaMat shows that AI can give you a realistic design tailored for a specific manufacturing method, like 3D printing, and optimized to withstand various manufacturing related defects. It sets the stage for the automatic design of manufacturable, defect-tolerant materials with on-demand functionalities.”

While advances in data-driven design and additive manufacturing have significantly accelerated the development of truss metamaterials, Zheng explained that existing inverse design approaches have inherent limitations. They can generate metamaterials with target linear properties, such as elasticity, but struggle to capture more complex nonlinear behaviors, such as energy absorption, needed for items like car bumpers and protective athletic gear.

“Design methods like topology optimization or an intuition-guided iterative approach are good at predicting simple responses,” said Zheng. “But for many real-world problems, these approaches cannot efficiently design materials with the required functionality, manufacturability and tolerance to defects introduced during manufacturing.”

Recently, researchers considered using graph neural networks for metamaterials design, since this has proved to be a powerful tool in drug discovery. But there was little to no training data available for designing metamaterials.

Zheng and his fellow researchers solved this problem by integrating multiple deep learning techniques — reinforcement learning, imitation learning, a surrogate model, and Monte Carlo tree search — into GraphMetaMat.

“Users can create metamaterial designs, represented as graphs, entirely from scratch based on custom inputs — such as a desired stress–strain curve or specific vibration attenuation gaps where mechanical waves are blocked at certain frequencies,” said Marco Maurizi, postdoctoral researcher in the Department of Materials Science and Engineering and lead author of the study. “Our AI system then iteratively adds graph nodes and edges to define the material’s geometry and topology.”

Most importantly, according to Zheng, GraphMetaMat can also integrate engineering constraints into the graphs — including manufacturing and defect constraints.

“GraphMetaMat has the unique ability to account for fabrication-induced imperfections,” he said. “This innovation is a game-changer because it ensures that the generated metamaterials will not fail if they develop a small defect during manufacturing.”

In their proof of concept, the researchers used GraphMetaMat to design lightweight truss metamaterials optimized for energy absorption and vibration mitigation at various frequencies. For each use case, the generated metamaterial consistently outperformed traditional materials, including polymeric foams and phononic crystals.

“Based on our findings, GraphMetaMat has the potential to redefine the design paradigm,” said Zheng. “This opens the door to exciting new possibilities in creating realistic, high-performance metamaterials.”

This work was conducted in collaboration with UCLA researchers led by Wei Wang and Yizhou Sun, and Penn State University researchers led by Yun Jing. In addition, co-lead authors of this study include Derek Xu of UCLA and Yu-Tong Wang of Penn State University.

For more information: Nature Machine Intelligence

Image: GraphMetaMat, an inverse design framework, enables users to create metamaterial designs, represented as graphs, entirely from scratch based on custom inputs. Its AI system then iteratively adds graph nodes and edges to define the material’s geometry and topology and integrates manufacturing and defect constraints. (Illustration courtesy of the researchers)