Nanotechnology: New Principle in Material Science Discovered

Nanotechnology: New Principle in Material Science Discovered

  7:58:00 PM    Science Lover

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Materials scientists have known that a metal's strength (or weakness) is governed by dislocation interactions, a messy exchange of intersecting fault lines that move or ripple within metallic crystals. But what happens when metals are engineered at the nanoscale? Is there a way to make metals stronger and more ductile by manipulating their nanostructures?

A material science team led by Brown University 
engineers has found that the deformation of 
nanotwinned metals is characterized by the 
motion of highly ordered, necklace-like patterns 
of crystal defects called dislocations. 
(Credit: Huajian Gao and Xiaoyan Li, Brown University)

Brown University scientists may have figured out a way. In a paper published in Nature, Huajian Gao and researchers from the University of Alabama and China report a new mechanism that governs the peak strength of nanostructured metals. By performing 3-D atomic simulations of divided grains of nanostructured metals, Gao and his team observed that dislocations organize themselves in highly ordered, necklace-like patterns throughout the material. The nucleation of this dislocation pattern is what determines the peak strength of materials, the researchers report.

The finding could open the door to producing stronger, more ductile metals, said Gao, professor of engineering at Brown. "This is a new theory governing strength in materials science," he added. "Its significance is that it reveals a new mechanism of material strength that is unique for nanostructured materials."

Divide a grain of metal using a specialized technique, and the pieces may reveal boundaries within the grain that scientists refer to as twin boundaries. These are generally flat, crystal surfaces that mirror the crystal orientations across them. The Chinese authors created nanotwinned boundaries in copper and were analyzing the space between the boundaries when they made an interesting observation: The copper got stronger as the space between the boundaries decreased from 100 nanometers, ultimately reaching a peak of strength at 15 nanometers. However, as the spacing decreased from 15 nanometers, the metal got weaker.

"This is very puzzling," Gao said.

So Gao and Brown graduate student Xiaoyan Li dug a little further. The Brown scientists reproduced their collaborators' experiment in computer simulations involving 140 million atoms. They used a supercomputer at the National Institute for Computational Sciences in Tennessee, which allowed them to analyze the twin boundaries at the atomic scale. To their surprise, they saw an entirely new phenomenon: A highly ordered dislocation pattern controlled by nucleation had taken hold and dictated the copper's strength. The pattern was characterized by groups of atoms near the dislocation core and assembled in highly ordered, necklace-like patterns.

"They're not getting in each other's way. They're very organized," Gao said.

From the experiments and the computer modeling, the researchers theorize that at the nanoscale, dislocation nucleation can become the governing principle to determining a metal's strength or weakness. The authors presented a new equation in the Nature paper to describe the principle.

"Our work provides a concrete example of a source-controlled deformation mechanism in nanostructured materials for the first time and, as such, can be expected to have a profound impact on the field of materials science," Gao said.

The other researchers who contributed to the paper are Yujie Wei from the University of Alabama and Ke Lu and Lei Lu from the Chinese Academy of Sciences. The U.S. National Science Foundation, the National Science Foundation in China and the Ministry of Science and Technology in China funded the research.

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Computer Model: Neurons Coordinate Messages

Computer Model: Neurons Coordinate Messages

  2:45:00 PM    Science Lover

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There is strength in numbers if you want to get your voice heard. But how to do you get your say if you are in the minority? That's a dilemma faced not only by the citizens of a democracy but also by some neurons in the brain.

Although they only account for a fraction of the synapses in the visual cortex, neurons in the thalamus get their message across loud and clear by coordination -- simultaneously hitting the "send" button -- according to a computer simulation developed by researchers at the Salk Institute for Biological Studies.

This is an image of a spiny stellate cell. 
(Credit: This image originally appeared in 
Churchill et al. BMC Neuroscience 2004 5:43.)

Their findings, published in the April 2, 2010 issue of the journal Science, hold important clues to how the brain encodes and processes information, which can be applied to a wide variety of applications, from understanding psychiatric disorders to the development of novel pharmaceuticals and new ways of handling information by computers or communication networks.

Historically, neuroscientists have been limited to recording the activity of single brain cells, which led to the widely accepted view that neurons communicate with each other through volleys of electrical spikes and that they increase the average rate of spiking to "speak up."

But communication between neurons is not limited to one-on-one interactions. Instead, any given cell receives signals from hundreds of cells, which send their messages through thousands of synapses, specialized junctions that allow signals to pass from one neuron to the next.

"Unfortunately, we don't have the technology yet to actually measure what all these neurons are saying to the recipient cell, which would require recording simultaneously from hundreds of cells, " says graduate student and first author Hsi-Ping Wang. "For this reason, nobody could answer a very basic question that's been puzzling neuroscientist for decades, which is: 'How many neurons or synapses does it take to reliably send a signal from point A to point B?'"

This question is particularly pressing for the thalamus, the central switchboard that processes and distributes incoming sensory information to all parts of the cortex. Thalamic input only accounts for five percent of the signals that so-called spiny stellate cells in the cortex receive, even though they drive a good portion of activity throughout the cerebral cortex.

"That is a paradox," says Howard Hughes Medical Institute investigator Terrence J. Sejnowski, Ph.D., professor and head of the Computational Neurobiology Laboratory. "How can so few synapses have such a big impact? If the average spiking rate were the determining factor, thalamic input would be drowned out by the other 95 percent of the inputs from other cortical cells."

Based on the assumption that the brain cares about the reliability and precision of spikes, Sejnowki's team developed a realistic computer model of a spiny stellate cell and the signals it receives through its roughly 6,000 synapses. "We found that it is not the number of spikes that's relevant but rather how many spikes arrive at the same time," says Sejnowski.

"Surprisingly, our model predicts that it only takes about 30 synapses out of 6,000 firing simultaneously to create extremely reliable signaling," explains Wang, "and our prediction lines up with currently available in vivo measurements and understanding. You could have all 6,000 synapses firing at the same time, but it would be a waste of resources."

The researchers hope that their findings will give them new insight into the holy grail of neurobiology: decoding the neural code or language of the brain. If the eye receives the same visual information under identical conditions over and over again, one would expect that the signal, the series of generated spikes or bits, is essentially the same.

"But it's not known whether that happens under natural conditions, and it's technically very difficult to measure, " says senior researcher and co-author Donald Spencer, Ph.D. "That's where the power of computational neurobiology really comes to bear on otherwise intractable questions."

"Applying theories of engineering to the study of the brain has helped us gain new insight into how neurons communicate with each other," says Wang. "On the other hand, there are certain things that the brain does in unique ways that are completely different from how computers work. A better understanding of the brain allows us the capture these algorithms and could very well affect the things engineers do in everyday life."

Jean-Marc Fellous, an associate professor in the Department of Psychology and Applied Mathematics at the University of Arizona, also contributed to the work.

The work was supported by the Howard Hughes Medical Institute.

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Scientists Find Universal Rules For Food-web Stability

Scientists Find Universal Rules For Food-web Stability

  8:11:00 PM    Science Lover

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New findings, published in the journal Science, conclude that food-web stability is enhanced when many diverse predator-prey links connect high and intermediate trophic levels. The computations also reveal that small ecosystems follow other rules than large ecosystems: differences in the strength of predator-prey links increase the stability of small webs, but destabilize larger webs.

A Juvenile African Bush Viper (Atheris chlorechis) with a small frog, at night.
Researchers found that food-web stability is enhanced when many diverse predator-prey links connect high and intermediate trophic levels. (Credit: iStockphoto/Mark Kostich)

Natural ecosystems consist of interwoven food chains, in which individual animal or plant species function as predator or prey. Potential food webs not only differ by their species composition, but also vary in their stability. Observable food webs are stable food webs, with the relationships between their species remaining constant over relatively long periods of time.

Understanding complex systems such as food webs present major challenges to science. They can either be examined by observing natural environments, or by computer simulations. To enable computer simulations of such systems, scientists often have to make simplifying assumptions, keeping the number of model parameters as low as possible. Yet, the computational demands of such simulations are high and their relevance is often limited.

Innovative methodology

Scientists from the Max Planck Institute for the Physics of Complex Systems (MPIPKS) in Dresden, Germany, have developed a new method that allows them to efficiently analyze the impact of innumerable parameters on complex systems.

"By using a method called generalized modeling, we examine whether a given food web can, in principle, be stable, i.e., whether its species can coexist in the long term," says Thilo Gross from MPIPKS. Complex ecosystems can thus be simulated and analyzed under almost any conditions. "In this way we can estimate which parameters will keep ecosystems stable and which will upset their balance."

The method can also be used for examining other complex systems, such as human metabolism or gene regulation.

Generalists stabilize, specialists destabilize

Applying this innovative modeling approach together with colleagues at the International Institute for Applied Systems Analysis (IIASA) in Laxenburg, Austria, and Princeton University, USA, the scientists have succeeded in discovering not just one, but several universal rules in the dynamics of ecosystems.

"Food-web stability is enhanced when species at high trophic levels feed on multiple prey species and species at intermediate trophic levels are fed upon by multiple predator species," says Ulf Dieckmann of IIASA.

The scientists have also identified additional stabilizing and destabilizing factors within ecosystems. Ecosystems with high densities of predator-prey links are less likely to be stable, while a strong dependence of predation on predator density destabilizes the system. On the other hand, a strong dependence of predation on prey density has a stabilizing impact on food webs.

Differences between small and large systems

A further important finding is that food webs consisting of only a few species behave qualitatively different from webs consisting of many species.

"Small ecosystems apparently follow different rules than large ecosystems," says Ulf Dieckmann. "Systems with fewer species are more stable if there are strong interactions between some species, but only weak interactions between others. For food webs with many species, exactly the opposite is true. Extremely strong or weak predator-prey links in nature should therefore be the rarer the more species a food web contains," he concludes.

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