Hexbyte Glen Cove Creating a less fragile diamond using fullerenes

Hexbyte Glen Cove

Structural comparison: crystalline diamond (left) and paracrystalline diamond (right). On the right, units of carbon atoms arranged in a cube shape are marked in turquoise, units of carbon atoms arranged in a hexagonal shape are marked in yellow. Irregular structures are marked in red. Credit: Hu Tang.

A team of researchers from China, Germany and the U.S. has developed a way to create a less fragile diamond. In their paper published in the journal Nature, the group describes their approach to creating a paracrystalline diamond and possible uses for it.

Prior research has shown that diamond is the hardest known material but it is also fragile—despite their hardness, can be easily cut or even smashed. This is because of their ordered atomic structure. Scientists have tried for years to synthesize diamonds that retain their hardness but are less fragile. The team has now come close to achieving that goal.

Currently, the way to create diamonds is to place a carbon-based material in a vice-like device where it is heated to very high temperatures while it is squeezed very hard. In this new effort, the researchers have used the same approach to create a less ordered type of diamond but have added a new twist—the carbon-based material was a batch of fullerenes, also known as buckyballs ( arranged in a hollow spherical shape). They heated the material to between 900 and 1,300 °C at pressures of 27 to 30 gigapascals. Notably, the pressure exerted was much lower than is used to make commercial diamonds. During processing, the spheres were forced to collapse, and they formed into transparent paracrystalline diamonds which could be extracted at room temperature.

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Hexbyte Glen Cove Creating ultra-diffuse galaxies

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An optical image of the ultra-diffuse galaxy GMP 4348 in the Coma cluster of galaxies; the scale bar shows a distance of thirty-two thousand light-years. In a spectroscopic study of eleven such galaxies, astronomers have concluded that ram-stripping of gas led these galaxies to shut down star formation and expand, turning them into ultra-diffuse galaxies.

Ultra-diffuse galaxies (UDGs) have very low luminosities, comparatively few stars, and little star-formation activity as compared with normal galaxies of similar sizes. Commonly found in galaxy clusters, UDGs come in a wide range of sizes and shapes, many of them being round and smooth like dwarf elliptical galaxies, others showing distorted shapes from having experienced tidal disruptions; some having total masses of as much as one hundred billion solar-masses. In addition to being interesting in their own right, these galaxies are important to astronomers because their diffuse structures are valuable in models trying to recover information about the dark matter halos that help keep them self-contained; indeed most of their mass is thought to be in the form of dark matter.

The origin and evolution of UDGs is poorly understood. They sometimes resemble dwarf elliptical —small, faint elliptical galaxies that may have formed early in cosmic history but (unlike other galaxies) did not merge into larger systems—suggesting some UDGs have primordial roots. Supernovae from an initial phase of star formation may have puffed them up from dwarf-galaxy sizes and inhibited further star formation (some astronomers think UDGs are “failed galaxies”) but tidal interactions may also have played a similar role, or else UDGs may have resulted from peculiar initial properties. CfA astronomers Igor Chilingarian, Dan Fabricant, and Sean Moran and their colleagues used the Binospec instrument on the MMT to study faint diffuse galaxies in the Coma and the Abell 2147 clusters of galaxies. They chose eleven low-luminosity, diffuse objects with little star-formation and with stars whose average age was 1.5 billion years—relatively young, meaning these galaxies are in a post-starburst phase. All of the objects also happen to have suffered recent encounters with another galaxy and host ram-pressure tails with signs of some recent star formation.

The deep optical spectra of these post-starburst galaxies enabled the astronomers to model the stellar history of each object and model its kinematics. The spectra revealed the presence of rotating stellar disks that are inferred to be composed of as much as 95% dark matter. The scientists propose a scenario in which these galaxies formed and began making stars about twelve billion years ago. Then, between about two hundred million to one billion years ago, bursts of star formation triggered by ram pressure from encounters with other galaxies in their clusters shut off most of the star formation. All eleven objects apparently formed in this same way. The fact that the galaxy sample size is statistically significant, at least for the clusters studied, enabled the team to conclude that ram pressure processes led to the galaxies puffing up, ultimately to become UDGs, and that about half of all UDGs today probably arose from similar ram-stripping processes.

The reearch was published in Nature Astronomy.

More information:
Kirill A. Grishin et al, Transforming gas-rich low-mass disky galaxies into ultra-diffuse galaxies by ram pressure, Nature Astronomy (2021). DOI: 10.1038/s41550-021-01470-5

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Hexbyte Glen Cove New platform for creating and characterizing material blends could significantly accelerate development thumbnail

Hexbyte Glen Cove New platform for creating and characterizing material blends could significantly accelerate development

Hexbyte Glen Cove

Yale University PhD student Kristof Toth (pictured above) with the electrospray deposition tool he designed, built, and validated in collaboration with staff scientist Gregory Doerk of Brookhaven Lab’s Center for Functional Nanomaterials (CFN). This CFN tool allows users to blend multiple components–such as polymers, nanoparticles, and small molecules–over a range of compositions in a single sample. Next door to the CFN, at the National Synchrotron Light Source II, users can probe how the structure of the blended material changes across this entire composition space. Credit: Brookhaven National Laboratory

Blending is a powerful strategy for improving the performance of electronics, coatings, separation membranes, and other functional materials. For example, high-efficiency solar cells and light-emitting diodes have been produced by optimizing mixtures of organic and inorganic components.

However, finding the optimal blend composition to produce desired properties has traditionally been a time-consuming and inconsistent process. Scientists synthesize and characterize a large number of individual samples with different compositions one at a time, eventually compiling enough data to create a compositional “library.” An alternative approach is to synthesize a single sample with a compositional gradient so that all possible compositions can be explored at once. Existing combinatorial methods for rapidly exploring compositions have been limited in terms of the types of compatible materials, the size of compositional increments, or number of blendable components (often only two).

To overcome these limitations, a team from the U.S. Department of Energy’s (DOE) Brookhaven National Laboratory, Yale University, and University of Pennsylvania recently built a first-of-its-kind automated tool for depositing films with finely controlled blend compositions made of up to three components onto single samples. Solutions of each component are loaded into syringe pumps, mixed according to a programmable “recipe,” and sprayed as tiny electrically charged droplets onto the surface of a heated base material called a substrate. By programming the flow rates of the pumps as a stage underneath the substrate changes position, users can obtain continuous gradients in composition.

Now, the team has combined this electrospray deposition tool with the structural characterization technique of X-ray scattering. Together, these capabilities form a platform to probe how material structure changes across an entire composition space. The scientists demonstrated this platform for a thin-film blend of three polymers—chains made of linked together by chemical bonds—designed to spontaneously arrange, or “self-assemble,” into nanometer-scale (billionths of a meter) patterns. Their platform and demonstration are described in a paper published today in RSC Advances, a journal of the Royal Society of Chemistry (RSC).

“Our platform reduces the time to explore complex compositional dependencies of blended material systems from months or weeks to a few days,” said corresponding author Gregory Doerk, a staff scientist in the Electronic Nanomaterials Group at Brookhaven Lab’s Center for Functional Nanomaterials (CFN).

A schematic of the electrospray deposition tool (a), with zoomed-in (b) and aerial (c) views. Credit: Brookhaven National Laboratory

“We constructed a morphology diagram with more than 200 measurements on a single sample, which is like making 200 samples the conventional way,” said first author Kristof Toth, a Ph.D. student in the Department of Chemical and Environmental Engineering at Yale University. “Our approach not only reduces sample preparation time but also sample-to-sample error.”

This diagram mapped how the morphologies, or shapes, of the blended polymer system changed along a compositional gradient of 0 to 100 percent. In this case, the system contained a widely studied self-assembling polymer made of two distinct blocks (PS-b-PMMA) and this block copolymer’s individual block constituents, or homopolymers (PS and PMMA). The scientists programmed the electrospray deposition tool to consecutively create one-dimensional gradient “strips” with all block copolymer at one end and all homopolymer blend at the other end.

To characterize the structure, the team performed grazing-incidence small-angle X-ray scattering experiments at the Complex Materials Scattering (CMS) beamline, which is operated at Brookhaven’s National Synchrotron Light Source II (NSLS-II) in partnership with the CFN. In this technique, a high-intensity X-ray beam is directed toward the surface of a sample at a very low angle. The beam reflects off the sample in a characteristic pattern, providing snapshots of nanoscale structures at different compositions along each five-millimeter-long strip. From these images, the shape, size, and ordering of these structures can be determined.

“The synchrotron’s high intensity X-rays allow us to take snapshots at each composition in a matter of seconds, reducing the overall time to map the morphology diagram,” said co-author Kevin Yager, leader of the CFN Electronic Nanomaterials Group.

The X-ray scattering data revealed the emergence of highly ordered morphologies of different kinds as the blend composition changed. Normally, the block copolymers self-assemble into cylinders. However, blending in very short homopolymers resulted in well-ordered spheres (increasing amount of PS) and vertical sheets (more PMMA). The addition of these homopolymers also tripled or quadrupled the speed of the self-assembly process, depending on the ratio of PS to PMMA homopolymer. To further support their results, the scientists performed imaging studies with a scanning electron microscope at the CFN Materials Synthesis and Characterization Facility.

The morphology diagram derived from the x-ray scattering data shows where in the composition space the cylinders, lamellae (vertical sheets), spheres, and disorder occur. Pure PS-PMMA block copolymer is located at the top of the triangle, and pure PMMA and PS homopolymers are at the lower left and right of the triangle, respectively. Each colored point represents a single x-ray measurement (the numbered points correspond to measurements described in detail in the paper). Credit: Brookhaven National Laboratory

Though the team focused on a self-assembling polymer system for their demonstration, the platform can be used to explore blends of a variety of materials such as polymers, nanoparticles, and small molecules. Users can also study the effects of different substrate materials, film thicknesses, X-ray beam focal spot sizes, and other processing and characterization conditions.

“This capability to survey a broad range of compositional and processing parameters will inform the creation of complex nanostructured systems with enhanced or entirely new properties and functionalities,” said co-author Chinedum Osuji, the Eduardo D. Glandt Presidential Professor of Chemical and Biomolecular Engineering at the University of Pennsylvania.

In the future, the scientists hope to create a second generation of the instrument that can create samples with mixtures of more than three components and which is compatible with a range of characterization methods—including in situ methods to capture morphology changes during the electrospray deposition process.

“Our platform represents a huge advance in the amount of information you can get across a composition space,” said Doerk. “In a few days, users can work with me at the CFN and the beamline staff next door at NSLS-II to create and characterize their blended systems.”

“In many ways, this platform complements autonomous methods developed by CFN and NSLS-II scientists to identify trends in experimental data,” added Yager. “Pairing them together has the potential to dramatically accelerate soft matter research.”

More information:
Kristof Toth et al, High-throughput morphology mapping of self-assembling ternary polymer blends, RSC Advances (2020). DOI: 10.1039/d0ra08491c

New platform for creating and characterizing material blends could significantly accelerate development (2020, November 24)
retrieved 25 November 2020
from https://phys.org/news/2020-11-platform-characterizing-material-blends-significantly.html

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part may be reproduced without the written permission. The content is provided for information purposes only.