Aurelia Butler

Marvel at the tiny nanoscale structures emerging from research labs at Duke University and Arizona State University, and it’s easy to imagine you’re browsing a catalog of the world’s smallest pottery.
A new paper reveals some of the teams’ creations: itty-bitty vases, bowls, and hollow spheres, one hidden inside the other, like housewares for a Russian nesting doll.
But instead of making them from wood or clay, the researchers designed these objects out of threadlike molecules of DNA, bent and folded into complex three-dimensional objects with nanometer precision.
These creations demonstrate the possibilities of a new open-source software program developed by Duke Ph.D. student Dan Fu with his adviser John Reif. Described December 23 in the journal Science Advances, the software lets users take drawings or digital models of rounded shapes and turn them into 3D structures made of DNA.
The DNA nanostructures were assembled and imaged by co-authors Raghu Pradeep Narayanan and Abhay Prasad in professor Hao Yan’s lab at Arizona State. Each tiny hollow object is no more than two millionths of an inch across. More than 50,000 of them could fit on the head of a pin.
But the researchers say these are more than mere nano-sculptures. The software could allow researchers to create tiny containers to deliver drugs, or molds for casting metal nanoparticles with specific shapes for solar cells, medical imaging and other applications. More

A magical display that projects holographic images that change when in contact with water has been developed. This new technology increases the possibility of commercialization as it can infinitely imprint holographic images.
A POSTECH research team led by Professor Junsuk Rho (Department of Mechanical Engineering and Department of Chemical Engineering) and Ph.D. candidates Byoungsu Ko, Younghwan Yang, Jaekyung Kim, and Dr. Trevon Badloe has developed a technology for a humidity-responsive display that changes in brightness and color depending on the degree of humidity.
The team first successfully realized holographic images with tunable brightness using polyvinyl alcohol (PVA). This material is so flexible that it is usually used for liquid glue or slime and one of its distinctive properties is that it swells as humidity increases. A holographic image that is clear at a low degree of humidity gradually becomes unclear as humidity increases.
The team additionally developed a display on which structural colors can be discretionally tuned. A blue image at low humidity turns red as humidity increases. If humidity is fine-tuned, all RGB colors may be expressed, in addition to the two colors.
This study also draws attention to the team’s success in using the single-step nanoimprinting technique to print the images. It is notable that images can be vividly expressed even on a flexible substrate. In addition, as a single pixel of this display — which reaches 700 nm (1nm = 1/1 billion m) — is smaller than those of currently commercialized displays, it is anticipated to become the core technology for nanostructured displays.
The findings from the study have received significant attention as the newly developed technology may be employed to security labels for authentication against counterfeits, including food items like whisky, currency bills, or passports. The team has been working with Korea Minting and Security Printing Corporation (KOMSCO) to apply the optics-based future security technology to actual products. Subsequently, this technology is expected to be applied to the development of a hydrogel macromolecule-based display that responds to external stimuli such as heat, acidity (pH), and fine-dust pollution.
These findings on the brightness and color tunability of holographic images were published in the international journals Nature Communications and Advanced Science, respectively.
This research was supported by the Samsung Science & Technology Foundation, the Pioneer Program of Future Technology of the National Research Foundation under the Ministry of Science and ICT and POSCO-POSTECH-RIST Convergence Research Center program funded by POSCO.
Story Source:
Materials provided by Pohang University of Science & Technology (POSTECH). Note: Content may be edited for style and length. More

Ensuring manufactured goods and components have not been copied and replaced illegally by counterfeited goods is a high-priority concern of the manufacturing and defense industries in the U.S. and around the world.
A potential solution would hold wide-reaching impacts and implications in various areas ranging from enhancing biomedical implants to protecting national defense assets.
Texas A&M University researchers have developed a method of imprinting a hidden magnetic tag, encoded with authentication information, within manufactured hardware during the part fabrication process. The revolutionary process holds the potential to expose counterfeit goods more easily by replacing physical tags — such as barcodes or quick response (QR) codes — with these hidden magnetic tags, which serve as permanent and unique identifiers.
The project, titled “Embedded Information in Additively Manufactured Metals via Composition Gradients for Anti-Counterfeiting and Supply Chain Traceability,” is a faculty partner project supported by the SecureAmerica Institute. It includes researchers from the Department of Materials Science and Engineering and the J. Mike Walker ’66 Department of Mechanical Engineering at Texas A&M. The team recently published its research in the journal Additive Manufacturing.
The faculty investigators on the project include Ibrahim Karaman, Chevron Professor I and department head of the materials science and engineering department; Raymundo Arroyave, professor of materials science and engineering and Segers Family Dean’s Excellence Professor; and Richard Malak, associate professor of mechanical engineering and Gulf Oil/Thomas A. Dietz Career Development Professor. In addition to the faculty, Daniel Salas Mula, a researcher with the Texas A&M Engineering Experiment Station, and doctoral student Deniz Ebeperi — both members of Karaman’s research group — have worked on the project. The team has also collaborated with Jitesh Panchal, professor of mechanical engineering at Purdue University.
Ensuring security and reliable authentication in manufacturing is a critical national concern, with the U.S. investing billions of dollars in manufacturing. Without such a method readily available, it can be nearly impossible to differentiate an authentic part or component from its counterfeit copy.”The issue is that when I come up with an idea, device or part, it is very easy for others to copy and even fabricate it much more cheaply — though maybe at a lower quality,” Karaman said. “Sometimes they even put the same brand name, so how do you make sure that item isn’t yours? [The embedded magnetic tag] gives us an opportunity and a new tool to make sure that we can protect our defense and manufacturing industries.”
The team is implementing metal additive manufacturing techniques to accomplish its goal of successfully embedding readable magnetic tags into metal parts without compromising on performance or longevity. Researchers used 3D printing to embed these magnetic tags below the surface into nonmagnetic steel hardware. More

Much of modern electronic and computing technology is based on one idea: add chemical impurities, or defects, to semiconductors to change their ability to conduct electricity. These altered materials are then combined in different ways to produce the devices that form the basis for digital computing, transistors, and diodes. Indeed, some quantum information technologies are based on a similar principle: adding defects and specific atoms within materials can produce qubits, the fundamental information storage units of quantum computing.
Gaurav Bahl, professor of mechanical science and engineering at the University of Illinois Urbana-Champaign and member of the Illinois Quantum Information Sciences and Technology Center, is exploring how special non-linear properties in engineered materials can achieve similar functionalities without the need to add intentional defects. As his research group reports in their article “Self-Induced Dirac Boundary State and Digitization in a Nonlinear Resonator Chain” published in Physical Review Letters, a metamaterial can change its functionality on its own depending on the power level of the input.
A metamaterial is an artificial system that replicates the behavior of real materials made of natural atoms. The researchers constructed a whose behavior is analogous to a special kind of semiconductor called a Dirac material. It consisted of a chain of magnetic-mechanical resonators, where the magnetic interactions acted like bonds between atoms in a one-dimensional crystal. When any of these “atoms” was mechanically excited, that is, was made to move periodically, the excitation spread to the rest of the crystal, just like electrons injected into a semiconductor.
After demonstrating that a completely uniform Dirac metamaterial does not allow mechanical excitations to pass through (just like electrons are forbidden from flowing through insulating semiconductor), the researchers introduced a specific set of nonlinearities into the system. This new property added sensitivity to the level of the mechanical excitation and could subtly change the resonance energy of the magneto-mechanical atoms. With the right choice of nonlinearity, the researchers observed a sharp transition from insulating to conducting behavior depending on how strong an input was provided.
This intriguing behavior resulted from the spontaneous appearance of a new boundary where the effective mass of the mechanical excitation, an invisible internal property of Dirac materials, underwent a change of sign depending on the level of the excitation. The researchers were surprised to find that this boundary was accompanied by a new state that “popped in” at the boundary and allowed input energy to transmit through the material. This effect was very similar to how a defect atom acts within a semiconductor
“In photonics and electronics,” Bahl said, “nonlinear properties like this could be engineered to form the foundation of new computational systems that don’t rely on the conventional semiconductor approach.”
Whenever we add defect states and special atoms, we interrupt the uniformity of the material, which can lead to other undesirable effects. However, materials in which a defect state can be formed on demand through an invisible property, such as the Dirac mass used in this work, has profound implications for quantum information systems where it promises qubits that can be produced dynamically where they are needed. The next challenge is finding or synthesizing real materials based on natural atoms that can replicate this effect.
The experiments were performed by Physics graduate student Gengming Liu in collaboration with postdoc Dr. Jiho Noh and MechSE graduate student Jianing Zhao
Story Source:
Materials provided by University of Illinois Grainger College of Engineering. Original written by Michael O’Boyle. Note: Content may be edited for style and length. More

Carnegie Mellon University’s Yongxin (Leon) Zhao and the Chinese University of Hong Kong’s Shih-Chi Chen have a big idea for manufacturing nanodevices.
Zhao’s Biophotonics Lab develops novel techniques to study biological and pathological processes in cells and tissues. Through a process called expansion microscopy, the lab works to advance techniques to proportionally enlarge microscopic samples embedded in a hydrogel, allowing researchers to be able to view fine details without upgrading their microscopes.
In 2019, an inspiring conversation with Shih-Chi Chen, who was visiting Carnegie Mellon as an invited speaker and is a professor at the Chinese University of Hong Kong’s Department of Mechanical and Automation Engineering, sparked a collaboration between the two researchers. They thought they could use their combined expertise to find novel solutions for the long-standing challenge in microfabrication: developing ways to reduce the size of printable nanodevices to as small as 10s of nanometers or several atoms thick.
Their solution is the opposite of expansion microscopy: create the 3D pattern of a material in hydrogel and shrink it for nanoscale resolution.
“Shih-Chi is known for inventing the ultrafast two-photon lithography system,” said Zhao, the Eberly Family Career Development Associate Professor of Biological Sciences. “We met during his visit to Carnegie Mellon and decided to combine our techniques and expertise to pursue this radical idea.”
The results of the collaboration open new doors for designing sophisticated nanodevices and are published in the journal Science. More

The artificial intelligence algorithms behind the chatbot program ChatGPT — which has drawn attention for its ability to generate humanlike written responses to some of the most creative queries — might one day be able to help doctors detect Alzheimer’s Disease in its early stages. Research from Drexel University’s School of Biomedical Engineering, Science and Health Systems recently demonstrated that OpenAI’s GPT-3 program can identify clues from spontaneous speech that are 80% accurate in predicting the early stages of dementia.
Reported in the journal PLOS Digital Health, the Drexel study is the latest in a series of efforts to show the effectiveness of natural language processing programs for early prediction of Alzheimer’s — leveraging current research suggesting that language impairment can be an early indicator of neurodegenerative disorders.
Finding an Early Sign
The current practice for diagnosing Alzheimer’s Disease typically involves a medical history review and lengthy set of physical and neurological evaluations and tests. While there is still no cure for the disease, spotting it early can give patients more options for therapeutics and support. Because language impairment is a symptom in 60-80% of dementia patients, researchers have been focusing on programs that can pick up on subtle clues — such as hesitation, making grammar and pronunciation mistakes and forgetting the meaning of words — as a quick test that could indicate whether or not a patient should undergo a full examination.
“We know from ongoing research that the cognitive effects of Alzheimer’s Disease can manifest themselves in language production,” said Hualou Liang, PhD, a professor in Drexel’s School of Biomedical Engineering, Science and Health Systems and a coauthor of the research. “The most commonly used tests for early detection of Alzheimer’s look at acoustic features, such as pausing, articulation and vocal quality, in addition to tests of cognition. But we believe the improvement of natural language processing programs provide another path to support early identification of Alzheimer’s.”
A Program that Listens and Learns
GPT-3, officially the third generation of OpenAI’s General Pretrained Transformer (GPT), uses a deep learning algorithm — trained by processing vast swaths of information from the internet, with a particular focus on how words are used, and how language is constructed. This training allows it to produce a human-like response to any task that involves language, from responses to simple questions, to writing poems or essays. More

The use of light to produce transient phases in quantum materials is fast becoming a novel way to engineer new properties in them, such as the generation of superconductivity or nanoscale topological defects. However, visualizing the growth of a new phase in a solid is not easy, due in-part to the wide range of spatial and time scales involved in the process.
Although in the last two decades scientists have explained light-induced phase transitions by invoking nanoscale dynamics, real space images have not yet been produced and, thus, no one has seen them.
In the new study published in Nature Physics, ICFO researchers Allan S. Johnson and Daniel Pérez-Salinas, led by former ICFO Prof. Simon Wall, in collaboration with colleagues from Aarhus University, Sogang University, Vanderbilt University, the Max Born Institute, the Diamond Light Source, ALBA Synchrotron, Utrecht University, and the Pohang Accelerator Laboratory, have pioneered a new imaging method that allows the capture of the light-induced phase transition in vanadium oxide (VO2) with high spatial and temporal resolution.
The new technique implemented by the researchers is based on coherent X-ray hyperspectral imaging at a free electron laser, which has allowed them to visualize and better understand, at the nanoscale, the insulator-to-metal phase transition in this very well-known quantum material.
The crystal VO2 has been widely used in to study light-induced phase transitions. It was the first material to have its solid-solid transition tracked by time-resolved X-ray diffraction and its electronic nature was studied by using for the first time ultrafast X-ray absorption techniques. At room temperature, VO2 is in the insulating phase. However, if light is applied to the material, it is possible to break the dimers of the vanadium ion pairs and drive the transition from an insulating to a metallic phase.
In their experiment, the authors of the study prepared thin samples of VO2 with a gold mask to define the field of view. Then, the samples were taken to the X-ray Free Electron Laser facility at the Pohang Accelerator Laboratory, where an optical laser pulse induced the transient phase, before being probed by an ultrafast X-ray laser pulse. A camera captured the scattered X-rays, and the coherent scattering patterns were converted into images by using two different approaches: Fourier Transform Holography (FTH) and Coherent Diffractive Imaging (CDI). Images were taken at a range of time delays and X-ray wavelengths to build up a movie of the process with 150 femtosecond time resolution and 50 nm spatial resolution, but also with full hyperspectral information. More