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Category: nanotechnology

To design their improved materials, Serles and Filleter worked with Professor Seunghwa Ryu and PhD student Jinwook Yeo at the Korea Advanced Institute of Science & Technology (KAIST) in Daejeon, South Korea. This partnership was initiated through U of T’s International Doctoral Clusters program, which supports doctoral training through research engagement with international collaborators.

The KAIST team employed the multi-objective Bayesian optimization machine learning algorithm. This algorithm learned from simulated geometries to predict the best possible geometries for enhancing stress distribution and improving the strength-to-weight ratio of nano-architected designs.

Serles then used a two-photon polymerization 3D printer housed in the Centre for Research and Application in Fluidic Technologies (CRAFT) to create prototypes for experimental validation. This additive manufacturing technology enables 3D printing at the micro and nano scale, creating optimized carbon nanolattices.

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In a monumental stride toward the realization of practical quantum computing and advanced quantum networks, researchers at the prestigious Cavendish Laboratory of the University of Cambridge have successfully crafted a fully operational quantum register utilizing the atomic properties within a semiconductor quantum dot. This innovative development could pave the way for pivotal advancements in quantum information technology, crucial for the anticipated future where quantum networking integrates into everyday digital communications.

This breakthrough is detailed in a publication in Nature Physics, where it reveals the introduction of an entirely new category of qubits that are optically interconnected. As the field of quantum networking progresses, the need for stable, scalable, and adaptable quantum nodes has become increasingly evident. The research team’s focus on quantum dots is particularly advantageous, as these nanoscale entities possess unique optical and electronic attributes intrinsic to quantum mechanical phenomena.

Quantum dots have demonstrated considerable potential in existing technologies, such as medical imaging and display screens, primarily due to their efficacy as bright single-photon sources. However, to create functional quantum networks, it is essential not only to emit single photons but also to establish reliable qubits that can effectively interact with these emitted photons. Moreover, these qubits must be capable of locally storing quantum information over extended periods. The researchers’ development enhances the inherent spins of the nuclear atoms within the quantum dots, optimizing them into a cohesive many-body quantum register.

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Attosecond science, honored with the 2023 Nobel Prize in Physics, is transforming our understanding of how electrons move in atoms, molecules, and solids. An attosecond—equivalent to a billionth of a billionth of a second—enables “slow-motion” visualization of natural processes occurring at extraordinary speeds.

However, until now, most attosecond experiments have been limited to spectroscopic measurements due to the constraints of attosecond light pulse sources.

Using the powerful X-ray Free Electron Laser (FEL) at SLAC National Laboratory in California, the Hamburg team studied how interact with nanoparticles. They uncovered a previously unexplored phenomenon: transient ion resonances that enhance image brightness.

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Ultrawide-bandgap semiconductors—such as diamond—are promising for next-generation electronics due to a larger energy gap between the valence and conduction bands, allowing them to handle higher voltages, operate at higher frequencies, and provide greater efficiency compared to traditional materials like silicon.

However, their make it challenging to probe and understand how charge and heat move on nanometer-to-micron scales. Visible light has a very limited ability to probe nanoscale properties, and moreover, it is not absorbed by diamond, so it cannot be used to launch currents or rapid heating.

Now, researchers at JILA, led by JILA Fellows and University of Colorado physics professors Margaret Murnane and Henry Kapteyn, along with graduate students Emma Nelson, Theodore Culman, Brendan McBennett, and former JILA postdoctoral researchers Albert Beardo and Joshua Knobloch, have developed a novel microscope that makes examining these materials possible on an unprecedented scale.

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Researchers at the University of Toronto’s Faculty of Applied Science & Engineering have used machine learning to design nano-architected materials that have the strength of carbon steel but the lightness of Styrofoam.

In a new paper published in Advanced Materials, a team led by Professor Tobin Filleter describes how they made nanomaterials with properties that offer a conflicting combination of exceptional strength, light weight and customizability. The approach could benefit a wide range of industries, from automotive to aerospace.

“Nano-architected materials combine high performance shapes, like making a bridge out of triangles, at nanoscale sizes, which takes advantage of the ‘smaller is stronger’ effect, to achieve some of the highest strength-to-weight and stiffness-to-weight ratios, of any material,” says Peter Serles, the first author of the new paper.

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The chemical composition of a material alone sometimes reveals little about its properties. The decisive factor is often the arrangement of the molecules in the atomic lattice structure or on the surface of the material. Materials science utilizes this factor to create certain properties by applying individual atoms and molecules to surfaces with the aid of high-performance microscopes. This is still extremely time-consuming and the constructed nanostructures are comparatively simple.

Using , a research group at TU Graz now wants to take the construction of nanostructures to a new level. Their paper is published in the journal Computer Physics Communications.

“We want to develop a self-learning AI system that positions individual molecules quickly, specifically and in the right orientation, and all this completely autonomously,” says Oliver Hofmann from the Institute of Solid State Physics, who heads the research group. This should make it possible to build highly complex molecular structures, including logic circuits in the nanometer range.

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Scientists have built an artificial motor capable of mimicking the natural mechanisms that power life.

The finding, from The University of Manchester and the University of Strasbourg, published in the journal Nature, provides new insights into the fundamental processes that drive life at the molecular level and could open doors for applications in medicine, energy storage, and nanotechnology.

Professor David Leigh, lead researcher from The University of Manchester, said: Biology uses chemically powered molecular machines for every biological process, such as transporting chemicals around the cell, information processing or reproduction.

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Researchers leverage their understanding of molecular motors to improve nanoscale.

The term “nanoscale” refers to dimensions that are measured in nanometers (nm), with one nanometer equaling one-billionth of a meter. This scale encompasses sizes from approximately 1 to 100 nanometers, where unique physical, chemical, and biological properties emerge that are not present in bulk materials. At the nanoscale, materials exhibit phenomena such as quantum effects and increased surface area to volume ratios, which can significantly alter their optical, electrical, and magnetic behaviors. These characteristics make nanoscale materials highly valuable for a wide range of applications, including electronics, medicine, and materials science.

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A research team led by scientists at Northwestern University has developed the first-ever two-dimensional mechanically interlocked material with high flexibility and strength. In the future, this could be used to develop lightweight yet high-performance body armor and other such tough materials, a press release said.

It was in the 1980s that Fraser Stoddart, then a chemist at Northwestern University, first introduced the concept of mechanical bonds. Stoddart then expanded the role of these bonds into molecular machines by enabling functions like switching, rotating, contracting, and expanding in multiple ways and using them to develop interlocked structures, which also won him the Nobel Prize in 2016.

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