Graphene Is Strongest Material in the World Even with Defects

Graphene remains the strongest material ever measured and, as Professor Hone once put it, so strong that "it would take an elephant, balanced on a pencil, to break through a sheet of graphene the thickness of Saran Wrap.” —Illustration by Andrew Shea for Columbia Engineering

In a new study, published in Science May 31, 2013, Columbia Engineering researchers demonstrate that graphene, even if stitched together from many small crystalline grains, is almost as strong as graphene in its perfect crystalline form. This work resolves a contradiction between theoretical simulations, which predicted that grain boundaries can be strong, and earlier experiments, which indicated that they were much weaker than the perfect lattice.

Graphene consists of a single atomic layer of carbon, arranged in a honeycomb lattice. “Our first Science paper, in 2008, studied the strength graphene can achieve if it has no defects—its intrinsic strength,” says James Hone, professor of mechanical engineering, who led the study with Jeffrey Kysar, professor of mechanical engineering. “But defect-free, pristine graphene exists only in very small areas. Large-area sheets required for applications must contain many small grains connected at grain boundaries, and it was unclear how strong those grain boundaries were. This, our second Science paper, reports on the strength of large-area graphene films grown using chemical vapor deposition (CVD), and we’re excited to say that graphene is back and stronger than ever.”

The study verifies that commonly used methods for post-processing CVD-grown graphene weaken grain boundaries, resulting in the extremely low strength seen in previous studies. The Columbia Engineering team developed a new process that prevents any damage of graphene during transfer. “We substituted a different etchant and were able to create test samples without harming the graphene,” notes the paper’s lead author, Gwan-Hyoung Lee, a postdoctoral fellow in the Hone lab. “Our findings clearly correct the mistaken consensus that grain boundaries of graphene are weak. This is great news because graphene offers such a plethora of opportunities both for fundamental scientific research and industrial applications.”

                                              Profs. James Hone and Jeffrey Kysar
In its perfect crystalline form, graphene (a one-atom-thick carbon layer) is the strongest material ever measured, as the Columbia Engineering team reported in Science in 2008—so strong that, as Hone observed, “it would take an elephant, balanced on a pencil, to break through a sheet of graphene the thickness of Saran Wrap.” For the first study, the team obtained small, structurally perfect flakes of graphene by mechanical exfoliation, or mechanical peeling, from a crystal of graphite. But exfoliation is a time-consuming process that will never be practical for any of the many potential applications of graphene that require industrial mass production.

Currently, scientists can grow sheets of graphene as large as a television screen by using chemical vapor deposition (CVD), in which single layers of graphene are grown on copper substrates in a high-temperature furnace. One of the first applications of graphene may be as a conducting layer in flexible displays.

“But CVD graphene is ‘stitched’ together from many small crystalline grains—like a quilt—at grain boundaries that contain defects in the atomic structure,” Kysar explains. “These grain boundaries can severely limit the strength of large-area graphene if they break much more easily than the perfect crystal lattice, and so there has been intense interest in understanding how strong they can be.”

The Columbia Engineering team wanted to discover what was making CVD graphene so weak. In studying the processing techniques used to create their samples for testing, they found that the chemical most commonly used to remove the copper substrate also causes damage to the graphene, severely degrading its strength.

WATCH VIDEO
Click on the Video to watch Prof. James Hone take us on a tour of his synthesis lab in the Northwest Corner Building, where he grows graphene and nanotubes.

Their experiments demonstrated that CVD graphene with large grains is exactly as strong as exfoliated graphene, showing that its crystal lattice is just as perfect. And, more surprisingly, their experiments also showed that CVD graphene with small grains, even when tested right at a grain boundary, is about 90% as strong as the ideal crystal.

“This is an exciting result for the future of graphene, because it provides experimental evidence that the exceptional strength it possesses at the atomic scale can persist all the way up to samples inches or more in size,” says Hone. “This strength will be invaluable as scientists continue to develop new flexible electronics and ultrastrong composite materials.”

Strong, large-area graphene can be used for a wide variety of applications such as flexible electronics and strengthening components—potentially, a television screen that rolls up like a poster or ultrastrong composites that could replace carbon fiber. Or, the researchers speculate, a science fiction idea of a space elevator that could connect an orbiting satellite to Earth by a long cord that might consist of sheets of CVD graphene, since graphene (and its cousin material, carbon nanotubes) is the only material with the high strength-to-weight ratio required for this kind of hypothetical application.

The team is also excited about studying 2D materials like graphene. “Very little is known about the effects of grain boundaries in 2D materials,” Kysar adds. “Our work shows that grain boundaries in 2D materials can be much more sensitive to processing than in 3D materials. This is due to all the atoms in graphene being surface atoms, so surface damage that would normally not degrade the strength of 3D materials can completely destroy the strength of 2D materials. However with appropriate processing that avoids surface damage, grain boundaries in 2D materials, especially graphene, can be nearly as strong as the perfect, defect-free structure.”

The study was supported by grants from the Air Force Office of Scientific Research and the National Science Foundation.

—by Holly Evarts

Source: Columbia University

Grad Student Solves 30-Year-Old Physics Problem

                    Emilie Huffman, second year PhD student in physics. Credit: Duke University

Sometimes an age-old question just needs a fresh set of eyes.

That was the case in Duke’s physics department, where a graduate student and professor recently resolved a calculating dilemma that has vexed computational physicists for decades.

Emilie Huffman is a second-year PhD student from Charlotte, North Carolina. Last spring she began working with Shailesh Chandrasekharan, an associate professor and the director of graduate studies in physics, on what’s known as a sign problem.

Chandrasekharan is a theoretical nuclear and particle physicist who specializes in solving sign problems, which arise when one uses certain computational algorithms to calculate the behavior of large numbers of particles called fermions.

“Almost all the matter we know of are made with fermions,” Chandrasekharan said. “As building blocks of matter, it’s very important to be able to do calculations with them.”

But calculations of such complexity get tricky, and sign problems make it easy for wrong results to surface.

“It’s a very broad problem that affects almost all fields of physics involving quantum mechanics with strong correlations, where Monte Carlo methods are essential to perform calculations,” Chandrasekharan said.

Some in the field have simply moved on since the 1980s, leaving interesting questions plagued by sign problems unexplored. Other scientists have found workarounds and approximations. Very few, including Chandrasekharan, have tried to figure out solutions through the years. Huffman began work to expand on one of her advisor’s solutions, involving a grouping concept called fermion bags, and apply them to a new class of problems.

“She finally figured out a nice formula,” Chandrasekharan said. “Although the formula is quite simple and elegant, I couldn’t guess it.”

“In physics, often there’s a truth, and if you’re hitting on the right truth, everything starts falling into place.” Chandrasekharan says that’s what happened when he began applying Huffman’s formula to a class of problems.

Their paper appeared recently in the journal Physical Review B’s Rapid Communications.

“Now that I have a solution, I can begin to apply it,” Huffman said. Starting with condensed matter physics, Huffman plans to apply her solution to various questions that have been stymied by sign problems. “I can use this solution to study properties of graphene,” she said, referring to the single-layer carbon that has been touted as the strongest material in the world. Many puzzles remain in the field, especially involving multi-layer graphene sheets.

Wherever she turns her attention next, it’s clear Huffman has a promising career ahead.

Citation: “Solution to sign problems in half-filled spin-polarized electronic systems,” Emilie Huffman and Shailesh Chandrasekharan. Physical Review B Rapid Communications, March 12, 2014. DOI: 10.1103/PhysRevB.89.111101.

Source: Duke University

How to Learn math without fear, Stanford expert says

Stanford Prof. Boaler finds that children who excel in math learn to develop "number sense," which is much different from the memorization that is often stressed in school.
Image Credit: THEPLANETWALL STOCK

Students learn math best when they approach the subject as something they enjoy, according to a Stanford education expert. Speed pressure, timed testing and blind memorization pose high hurdles in the youthful pursuit of math.

"There is a common and damaging misconception in mathematics – the idea that strong math students are fast math students," said Jo Boaler, a Stanford professor of mathematics education and the lead author on a new working paper. Boaler's co-authors are Cathy Williams, cofounder of Stanford'sYouCubed, and Amanda Confer, a Stanford graduate student in education. 

Curriculum timely

Fortunately, said Boaler, the new national curriculum standards known as the Common Core Standards for K-12 schools de-emphasize the rote memorization of math facts. Maths facts are fundamental assumptions about math, such as the times tables (2 x 2 = 4), for example. Still, the expectation of rote memorization continues in classrooms and households across the United States.

While research shows that knowledge of math facts is important, Boaler said the best way for students to know math facts is by using them regularly and developing understanding of numerical relations. Memorization, speed and test pressure can be damaging, she added.

On the other hand, people with "number sense" are those who can use numbers flexibly, she said. For example, when asked to solve the problem of 7 x 8, someone with number sense may have memorized 56, but they would also be able to use a strategy such as working out 10 x 7 and subtracting two 7s (70-14).

"They would not have to rely on a distant memory," Boaler wrote.

In fact, in one research project the investigators found that the high-achieving students actually used number sense, rather than rote memory, and the low-achieving students did not.

The conclusion was that the low achievers are often low achievers not because they know less but because they don't use numbers flexibly.

"They have been set on the wrong path, often from an early age, of trying to memorize methods instead of interacting with numbers flexibly," she wrote. Number sense is the foundation for all higher-level mathematics, she noted. 

Role of the brain

Boaler said that some students will be slower when memorizing, but still possess exceptional mathematics potential.

"Math facts are a very small part of mathematics, but unfortunately students who don't memorize math facts well often come to believe that they can never be successful with math and turn away from the subject," she said.

Prior research found that students who memorized more easily were not higher achieving – in fact, they did not have what the researchers described as more "math ability" or higher IQ scores. Using an MRI scanner, the only brain differences the researchers found were in a brain region called the hippocampus, which is the area in the brain responsible for memorizing facts – the working memory section.

But according to Boaler, when students are stressed – such as when they are solving math questions under time pressure – the working memory becomes blocked and the students cannot as easily recall the math facts they had previously studied. This particularly occurs among higher achieving students and female students, she said.

Some estimates suggest that at least a third of students experience extreme stress or "math anxiety" when they take a timed test, no matter their level of achievement. "When we put students through this anxiety-provoking experience, we lose students from mathematics," she said.

Boaler contrasts the common approach to teaching math with that of teaching English. In English, a student reads and understands novels or poetry, without needing to memorize the meanings of words through testing. They learn words by using them in many different situations – talking, reading and writing.

"No English student would say or think that learning about English is about the fast memorization and fast recall of words," she added.

Strategies, activities 

In her paper, "Fluency without Fear," Boaler provides activities for teachers and parents that help students learn math facts at the same time as developing number sense. These include number talks, addition and multiplication activities, and math cards.

Importantly, she said, these activities include a focus on the visual representation of number facts. When students connect visual and symbolic representations of numbers, they are using different pathways in the brain, which deepens their learning, as shown by recent brain research.

"Math fluency" is often misinterpreted, with an over-emphasis on speed and memorization, she said. "I work with a lot of mathematicians, and one thing I notice about them is that they are not particularly fast with numbers; in fact some of them are rather slow. This is not a bad thing; they are slow because they think deeply and carefully about mathematics."

She refers to the famous French mathematician, Laurent Schwartz, who wrote in his autobiography that he often felt stupid in school, as he was one of the slowest math thinkers in class.
Math anxiety and fear play a big role in students dropping out of mathematics, said Boaler.

"When we emphasize memorization and testing in the name of fluency we are harming children, we are risking the future of our ever-quantitative society and we are threatening the discipline of mathematics. We have the research knowledge we need to change this and to enable all children to be powerful mathematics learners. Now is the time to use it," she said.

Source: Standford Unversity

Live adaptation of organ models in the OR

The non-deformed liver model (red) adapts to the deformed surface profile (blue). Credit: Graphics: Dr. Stefanie Speidel, KIT, in Medical Physics, 41

During minimally invasive operations, a surgeon has to trust the information displayed on the screen: A virtual 3D model of the respective organ shows where a tumor is located and where sensitive vessels can be found. Soft tissue, such as the tissue of the liver, however, deforms during breathing or when the scalpel is applied. Endoscopic cameras record in real time how the surface deforms, but do not show the deformation of deeper structures such as tumors. Young scientists of the Karlsruhe Institute of Technology (KIT) have now developed a real-time capable computation method to adapt the virtual organ to the deformed surface profile.

The principle appears to be simple: Based on computer tomography image data, the scientists construct a virtual 3D model of the respective organ, including the tumor, prior to operation. During the operation, cameras scan the surface of the organ and generate a stiff profile mask. To this virtual mold, the 3D model then is to fit snuggly, like jelly to a given form. The Young Investigator Group of Dr. Stefanie Speidel analyzed this geometrical problem of shape adaptation from the physical perspective. "We model the surface profile as electrically negative and the volume model of the organ as electrically positive charged," Speidel explains. "Now, both attract each other and the elastic volume model slides into the immovable profile mask." The adapted 3D model then reveals to the surgeon how the tumor has moved with the deformation of the organ.

Simulations and experiments using a close-to-reality phantom liver have demonstrated that the electrostatic-elastic method even works when only parts of the deformed surface profile are available. This is the usual situation at the hospital. The human liver is surrounded by other organs and, hence, only partly visible by endoscopic cameras. "Only those structures that are clearly identified as parts of the liver by our system are assigned an electric charge," says Dr. Stefan Suwelack who, as part of Speidel's group, wrote his Ph.D. thesis on this subject. Problems only arise, if far less than half of the deformed surface is visible. To stabilize computation in such cases, the KIT researchers can use clear reference points, such as crossing vessels. Their method, however, in contrary to others does not rely on such references from the outset.

In addition, the model of the KIT researchers is more precise than conventional methods, because it also considers biomechanical factors of the liver, such as the elasticity of the tissue. So for instance, the phantom liver used by the scientists consists of two different silicones: A harder material for the capsule, i.e. the outer shell of the liver, and a softer material for the inner liver tissue.

As a result of their physical approach, the young scientists also succeeded in accelerating the computation process. As shape adaptation was described by electrostatic and elastic energies, they found a single mathematical formula. Using this formula, even conventional computers equipped with a single processing unit only work so quickly that the method is competitive. Contrary to conventional computation methods, however, the new method is also suited for parallel computers. Using such a computer, the Young Investigator Group now plans to model organ deformations stably in real time.

Source: Karlsruhe Institute of Technology

Statistical model predicts performance of hybrid rice

Long-grain rice

Genomic prediction, a new field of quantitative genetics, is a statistical approach to predicting the value of an economically important trait in a plant, such as yield or disease resistance. The method works if the trait is heritable, as many traits tend to be, and can be performed early in the life cycle of the plant, helping reduce costs.

Now a research team led by plant geneticists at the University of California, Riverside and Huazhong Agricultural University, China, has used the method to predict the performance of hybrid rice (for example, the yield, growth-rate and disease resistance). The new technology could potentially revolutionize hybrid breeding in agriculture.

The study, published online in the Proceedings of the National Academy of Sciences, is a pilot research project on rice. The technology can be easily extended, however, to other crops such as maize.

"Rice and maize are two main crops that depend on hybrid breeding," said Shizhong Xu, a professor of genetics in the UC Riverside Department of Botany and Plant Sciences, who co-led the research project. "If we can identify many high-performance hybrids in these crops and use these hybrids, we can substantially increase grain production to achieve global food security."

Genomic prediction uses genome-wide markers to predict future individuals or species. These markers are genes or DNA sequences with known locations on a chromosome. Genomic prediction differs from traditional predictions in that it skips the marker-detection step. The method simply uses all markers of the entire genome to predict a trait.

"Classical marker-assisted selection only uses markers that have large effects on the trait," Xu explained. "It ignores all markers with small effects. But many economically important traits are controlled by a large number of genes with small effects. Because the genomic prediction model captures all these small-effect genes, predictability is vastly improved."

Without genomic prediction, breeders must grow all possible crosses in the field to select the best cross (hybrid). For example, for 1000 inbred parents, the total number of crosses would be 499500.

"It is impossible to grow these many crosses in the field," Xu said. "However, with the genomic prediction technology, we can grow only, say, 500 crosses, then predict all the 499500 potential crosses, and select the best crosses based on the predicted values of these hybrids."

Xu noted that genomic prediction is particularly useful for predicting hybrids because hybrid DNA sequences are determined by their inbred parents.

"More cost-saving can be achieved because we do not need to measure the DNA sequences of the hybrids," he said. "Knowing the genotypes of the parents makes it possible to immediately know the genotype of the hybrid. Indeed, there is no need to measure the genotype of the hybrid. It is fully predicted by the model."

When the researchers incorporated "dominance" and "epistasis" into their prediction model, they found that predictability was improved. In genetics, dominance describes the joint action of two different alleles (copies) of a gene. For example, if one copy of a gene has a value of 1 and the other copy has a value of 2, the joint effect of the two alleles may be 4, indicating that the two alleles are not additive. In this case, dominance has occurred. Epistasis refers to any type of gene-gene interaction.

"By incorporating dominance and epistasis, we took into account all available information for prediction," Xu said. "It led to a more accurate prediction of a trait value."

Genomic prediction can be used to predict heritable human diseases. For example, many cancers are heritable and genome prediction can be performed to predict disease risk for a person.

Xu was joined in the research by Qifa Zhang and his student Dan Zhu at Huazhong Agricultural University, China.

Next the research team, led by Xu and Zhang, will design a field experiment to perform hybrid prediction in rice.

Source: University of California - Riverside

Defects in solar cells made of silicon identified

Sergio Castellanos wants continue researching, work in an industry and does not rule out to eventually move to another country. Credit: Image courtesy of Investigación y Desarrollo

Since he was a teenager, engineer Sergio Castellanos had the desire to study abroad to prepare and do research in the best laboratories, particularly on solar energy. With six years of stay in the United States, first at the University of Arizona and now at the Massachusetts Institute of Technology (MIT) in Boston, his dream has come true:

"Working on defects found on silicon and their impact on the efficiency of solar cells made with this material."

This research is carried out to obtain his doctorate from MIT.

"Dislocation is a defect that occurs at high temperatures, of 500 ° C onwards. In my research I analyze these defects and their impact on the efficiency of solar cells made from silicon, since this material is used in over 90 percent of solar panels worldwide ."

The Mexican researcher in Boston explains that the harmful part of the dislocation is interacting with other defects such as metallic impurities within the material of solar cells; they tend to reduce efficiency by -for example- interacting with electrons.

"When having a dislocation is very easy for impurities to settle into a defect in the material. Therefore, in my research I analyze at an early scale what kind of dislocations will be more harmful to the cells, meaning, which ones will interact more with impurities because not all do likewise, hence not all dislocations are equally harmful."

The proposal of Sergio Castellanos at the MIT is to apply a method in wafers of polycrystalline silicon before being processed into solar cells. This method involves using a chemical treatment in order to view the dislocations and analyze the geometric variation on the surface. After making crystallographic analysis as well as X-rays for determining the distribution and concentration of metal impurities, a correlation is made with the geometric appearance of the surface and then, just by looking at the surface, one can deduce what the electrical behavior within material will be.

"The goal is to identify which areas of the material will be more likely for electrons to recombine before being extracted by contacts, becoming less efficient cells."

A little bit of history

When the native of Hermosillo, Sonora (northern state of Mexico), was in high school, he applied for the Massachusetts Institute of Technology (MIT) and was not admitted. He told himself he would not be discouraged because surely the opportunity would could come later. He decided to study mechanical engineering at the Technological Institute of Hermosillo and two years in his parents supported him to finish his degree abroad.

He was transferred to the University of Arizona where he finished his degree. At the university, he became involved in several projects on the subject of energy, as was the case with hydrogen cells, a solar car and installing solar panels.

The Mexican says he enjoyed doing research and started looking for projects and teachers who worked in that area. He spotted four scientists, but wanted to go to MIT because "for any engineer to be in this school is a dream. I had practice in energy research during my bachelor's and for my doctorate I looked for subjects in this area. I applied at several universities and at last I was admitted at MIT in Boston."

His research in solar cells is in the last stage, and once completed in the next year he will make it available to other researchers. This work was presented at various conferences and has received good reviews in terms of utility.

To "finish the tale" on solar cells, the Mexican will complete his studies in six to eight months, and is more than satisfied with the subject that has developed during his research.

Sergio Castellanos wants continue researching, work in an industry and does not rule out to eventually move to another country. In the remaining months he will define his next step. (Agencia ID)

Source: Investigación y Desarrollo

Astronomers bring the third dimension to a doomed star's outburst

A new shape model of the Homunculus Nebula reveals protrusions, trenches, holes and irregularities in its molecular hydrogen emission. The protrusions appear near a dust skirt seen at the nebula's center in visible light (inset) but not found in this study, so they constitute different structures. Credit: NASA Goddard (inset: NASA, ESA, Hubble SM4 ERO Team)

In the middle of the 19th century, the massive binary system Eta Carinae underwent an eruption that ejected at least 10 times the sun's mass and made it the second-brightest star in the sky. Now, a team of astronomers has used extensive new observations to create the first high-resolution 3-D model of the expanding cloud produced by this outburst.

"Our model indicates that this vast shell of gas and dust has a more complex origin than is generally assumed," said Thomas Madura, a NASA Postdoctoral Program fellow at NASA's Goddard Space Flight Center in Greenbelt, Maryland, and a member of the study team. "For the first time, we see evidence suggesting that intense interactions between the stars in the central binary played a significant role in sculpting the nebula we see today."

Eta Carinae lies about 7,500 light-years away in the southern constellation of Carina and is one of the most massive binary systems astronomers can study in detail. The smaller star is about 30 times the mass of the sun and may be as much as a million times more luminous. The primary star contains about 90 solar masses and emits 5 million times the sun's energy output. Both stars are fated to end their lives in spectacular supernova explosions.

Between 1838 and 1845, Eta Carinae underwent a period of unusual variability during which it briefly outshone Canopus, normally the second-brightest star. As a part of this event, which astronomers call the Great Eruption, a gaseous shell containing at least 10 and perhaps as much as 40 times the sun's mass was shot into space. This material forms a twin-lobed dust-filled cloud known as the Homunculus Nebula, which is now about a light-year long and continues to expand at more than 1.3 million mph (2.1 million km/h).

Using the European Southern Observatory's Very Large Telescope and its X-Shooter spectrograph over two nights in March 2012, the team imaged near-infrared, visible and ultraviolet wavelengths along 92 separate swaths across the nebula, making the most complete spectral map to date. The researchers have used the spatial and velocity information provided by this data to create the first high-resolution, fully 3-D model of the Homunculus Nebula. The new model contains none of the assumptions about the cloud's symmetry found in previous studies.

The shape model, which is now published by the journal Monthly Notices of the Royal Astronomical Society, was developed using only a single emission line of near-infrared light emitted by molecular hydrogen gas. The characteristic 2.12-micron light shifts in wavelength slightly depending on the speed and direction of the expanding gas, allowing the team to probe even dust-obscured portions of the Homunculus that face away from Earth.

"Our next step was to process all of this using 3-D modeling software I developed in collaboration with Nico Koning from the University of Calgary in Canada. The program is simply called 'Shape,' and it analyzes and models the three-dimensional motions and structure of nebulae in a way that can be compared directly with observations," said lead researcher Wolfgang Steffen, an astrophysicist at the Ensenada campus of the National Autonomous University of Mexico.

The new shape model confirms several features identified by previous studies, including pronounced holes located at the ends of each lobe and the absence of any extended molecular hydrogen emission from a dust skirt apparent in visible light near the center of the nebula. New features include curious arm-like protrusions emanating from each lobe near the dust skirt; vast, deep trenches curving along each lobe; and irregular divots on the side facing away from Earth.

"One of the questions we set out to answer with this study is whether the Homunculus contains any imprint of the star's binary nature, since previous efforts to explain its shape have assumed that both lobes were more or less identical and symmetric around their long axis," explained team member Jose Groh, an astronomer at Geneva University in Switzerland. "The new features strongly suggest that interactions between Eta Carinae's stars helped mold the Homunculus."

Every 5.5 years, when their orbits carry them to their closest approach, called periastron, the immense and brilliant stars of Eta Carinae are only as far apart as the average distance between Mars and the sun. Both stars possess powerful gaseous outflows called stellar winds, which constantly interact but do so most dramatically during periastron, when the faster wind from the smaller star carves a tunnel through the denser wind of its companion. The opening angle of this cavity closely matches the length of the trenches (130 degrees) and the angle between the arm-like protrusions (110 degrees), indicating that the Homunculus likely continues to carry an impression from a periastron interaction around the time of the Great Eruption.

Once the researchers had developed their Homunculus model, they took things one step further. They converted it to a format that can be used by 3-D printers and made the file available along with the published paper.

"Now anyone with access to a 3-D printer can produce their own version of this incredible object," said Goddard astrophysicist Theodore Gull, who is also a co-author of the paper. 

"While 3-D-printed models will make a terrific visualization tool for anyone interested in astronomy, I see them as particularly valuable for the blind, who now will be able to compare embossed astronomical images with a scientifically accurate representation of the real thing."

Source: NASA