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Category: nanotechnology

Archimedean screw inspires new way to encode chirality into magnetic materials

In physics and materials science, the term “spin chirality” refers to an asymmetry in the arrangement of spins (i.e., the intrinsic angular momentum of particles) in magnetic materials. This asymmetry can give rise to unique electronic and magnetic behaviors that are desirable for the development of spintronics, devices that leverage the spin of electrons and electric charge to process or store information.

The creation of materials that exhibit desired spin chirality and associated physical effects on a large scale has so far proved challenging. In a recent paper published in Nature Nanotechnology, researchers at École Polytechnique Fédérale de Lausanne (EPFL), the Max Planck Institute for Chemical Physics of Solids and other institutes introduced a new approach to encode chirality directly into materials by engineering their geometry at a nanoscale.

“Dirk and myself were initially inspired by the elegance of the Archimedean screw and began wondering whether we could build a magnonic analog, something that could ‘pump’ magnons (i.e., collective electron spin excitations) in a similarly directional way,” Dr. Mingran Xu, first author of the paper, told Tech Xplore.

Cancer Cells Light Up With a Breakthrough Imaging System

A new ultra-sensitive imaging system can make cancer cells light up, paving the way for faster and earlier detection.

Researchers have created a compact Raman imaging system that can reliably tell tumor tissue apart from normal tissue. The goal is to support earlier cancer detection and make molecular imaging easier to use beyond specialized research labs.

How SERS nanoparticles help tumors stand out.

Machine learning model predicts protein binding on gold nanoclusters

Researchers in the Nanoscience Center at the University of Jyväskylä, Finland, have developed a pioneering computational model that could expedite the use of nanomaterials in biomedical applications. The study presented the first generalizable machine-learning framework capable of predicting how proteins interact with ligand-stabilized gold nanoclusters, materials widely employed in bioimaging, biosensing, and targeted drug delivery.

The adsorption of proteins onto nanomaterial surfaces is fundamental to many biological applications, including bioimaging and biosensing to targeted drug delivery. Gold nanoclusters, in particular, have attracted attention thanks to their biocompatibility and tunable optical properties. Yet existing studies that predict how proteins interact with these ligand-protected nanostructures often focus on isolated cases, leaving researchers without a unified model to guide design.

“This gap has created a clear need for general, scalable models capable of capturing the underlying rules of protein–nanocluster binding,” specifies Postdoctoral Researcher Brenda Ferrari from the University of Jyväskylä

Aluminum nitride transistor advances next-gen RF electronics

Cornell researchers have developed a new transistor architecture that could reshape how high-power wireless electronics are engineered, while also addressing supply chain vulnerabilities for a critical semiconductor material.

The device, called an XHEMT, includes an ultra-thin layer of gallium nitride built on bulk single-crystal aluminum nitride, a semiconductor material with low defect densities and an ultrawide bandgap—properties that allow it to withstand higher temperatures and voltages while reducing electrical losses.

The device was detailed in the journal Advanced Electronic Materials and the research was co-led by Huili Grace Xing, the William L. Quackenbush Professor, Debdeep Jena, the David E. Burr Professor—both in the School of Electrical and Computer Engineering, the Department of Materials Science and Engineering, and the Kavli Institute at Cornell for Nanoscale Science—and doctoral student Eungkyun Kim.

Quality control: Neatly arranging crystal growth to make fine thin films

Table salt and refined sugar look white to our eyes, but that is only because their individual colorless crystals scatter visible light. This feature of crystals is not always desirable when it comes to materials for optical and electrical devices, however.

Metal-organic frameworks are one such material. Crystalline with micropores, thin films of these nanomaterials have been attracting attention as a next-generation material that could also have an impact on environmental issues such as hydrogen storage and carbon dioxide capture.

An Osaka Metropolitan University Graduate School of Engineering team has found a way to control the growth of crystals on such thin films so that light scattering is reduced significantly.

New 1.4nm nanoimprint lithography template could reduce the need for EUV steps in advanced process nodes — questions linger as no foundry has yet committed to nanoimprint lithography for high-volume manufacturing

Questions remain over whether nanoimprint can shoulder even a slice of next-generation logic.

The hidden physics of knot formation in fluids

Knots are everywhere—from tangled headphones to DNA strands packed inside viruses—but how an isolated filament can knot itself without collisions or external agitation has remained a longstanding puzzle in soft-matter physics.

Now, a team of researchers at Rice University, Georgetown University and the University of Trento in Italy has uncovered a surprising physical mechanism that explains how a single filament, even one too short or too stiff to easily wrap around itself, can form a knot while sinking through a fluid under strong gravitational forces.

The discovery, published in Physical Review Letters, provides new insight into the physics of polymer dynamics, with implications ranging from understanding how DNA behaves under confinement to designing next-generation soft materials and nanostructures.

New agentic AI platform accelerates advanced optics design

Stanford engineers debuted a new framework introducing computational tools and self-reflective AI assistants, potentially advancing fields like optical computing and astronomy.

Hyper-realistic holograms, next-generation sensors for autonomous robots, and slim augmented reality glasses are among the applications of metasurfaces, emerging photonic devices constructed from nanoscale building blocks.

Now, Stanford engineers have developed an AI framework that rapidly accelerates metasurface design, with potential widespread technological applications. The framework, called MetaChat, introduces new computational tools and self-reflective AI assistants, enabling rapid solving of optics-related problems. The findings were reported recently in the journal Science Advances.

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