A team of IBM researchers in Zurich, Switzerland, with support from colleagues in Yorktown Heights, N.Y., has developed a relatively simple, robust and versatile process for growing crystals made from compound semiconductor materials that will allow them be integrated onto silicon wafers—an important step toward making future computer chips that will allow integrated circuits to continue shrinking in size and cost even as they increase in performance.
Appearing in Applied Physics Letters, the work may allow an extension to Moore's Law, the famous observation by Gordon Moore that the number of transistors on an integrated circuit double about every two years. In recent years some in the industry have speculated that our ability to keep pace with Moore's Law may become exhausted eventually unless new technologies come along that will lend it leash.
"The whole semiconductor industry wants to keep Moore's Law going. We need better performing transistors as we continue down-scaling, and transistors based on silicon won't give us improvements anymore," said Heinz Schmid, a researcher with IBM Research GmbH at Zurich Research Laboratory in Switzerland and the lead author on the paper.
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Tuesday, July 14, 2015
Research reveals how computer chips could beat the heat
Now, x-ray studies at the U.S. Dept. of Energy (DOE)'s SLAC National Accelerator Laboratory have, for the first time, observed an exotic property that could warp the electronic structure of a material in a way that reduces heat buildup and improves performance in ever-smaller computer components.
The research was conducted, in part, at SLAC's Stanford Synchrotron Radiation Lightsource (SSRL), a DOE Office of Science User Facility, and published in Nature Materials.
Energy-bending properties
The team studied a form of iridium oxide, Sr3Ir2O7, that belongs to a class of so-called correlated materials in which electrons can be made to behave in sync. It is a candidate for reducing the heat generated by the billions of transistors at the core of modern computers.
Research shows genomics can match plant variety to climate stresses
A new study led by a Kansas State Univ. geneticist has shown that genomic signatures of adaptation in crop plants can help predict how crop varieties respond to stress from their environments.
It is the first study to document that these genomic signatures of adaptation can help identify plants that will do well under certain stresses, such drought or toxic soils, said Geoff Morris, assistant professor of agronomy at Kansas State Univ. and a researcher affiliated with the university's Feed the Future Innovation Lab for Collaborative Research on Sorghum and Millet.
Researchers conducted the study with sorghum, one of the oldest and most widely grown cereal grain crops in the world. Sorghum is grown in Africa and Asia as well as in some of the world's harshest crop-growing regions. More than 43,000 sorghum varieties around the world have been collected and stored in crop gene banks, which are centers that serve as repositories for crop diversity.
It is the first study to document that these genomic signatures of adaptation can help identify plants that will do well under certain stresses, such drought or toxic soils, said Geoff Morris, assistant professor of agronomy at Kansas State Univ. and a researcher affiliated with the university's Feed the Future Innovation Lab for Collaborative Research on Sorghum and Millet.
Researchers conducted the study with sorghum, one of the oldest and most widely grown cereal grain crops in the world. Sorghum is grown in Africa and Asia as well as in some of the world's harshest crop-growing regions. More than 43,000 sorghum varieties around the world have been collected and stored in crop gene banks, which are centers that serve as repositories for crop diversity.
Researchers develop basic computing elements for bacteria
The “friendly” bacteria inside our digestive systems are being given an upgrade, which may one day allow them to be programmed to detect and ultimately treat diseases such as colon cancer and immune disorders.
In a paper published in Cell Systems, researchers at MIT unveil a series of sensors, memory switches and circuits that can be encoded in the common human gut bacterium Bacteroides thetaiotaomicron.
These basic computing elements will allow the bacteria to sense, memorize, and respond to signals in the gut, with future applications that might include the early detection and treatment of inflammatory bowel disease or colon cancer.
Researchers have previously built genetic circuits inside model organisms such as E. coli. However, such strains are only found at low levels within the human gut, according to Timothy Lu, an associate professor of biological engineering and of electrical engineering and computer science, who led the research alongside Christopher Voigt, a professor of biological engineering at MIT.
In a paper published in Cell Systems, researchers at MIT unveil a series of sensors, memory switches and circuits that can be encoded in the common human gut bacterium Bacteroides thetaiotaomicron.
These basic computing elements will allow the bacteria to sense, memorize, and respond to signals in the gut, with future applications that might include the early detection and treatment of inflammatory bowel disease or colon cancer.
Researchers have previously built genetic circuits inside model organisms such as E. coli. However, such strains are only found at low levels within the human gut, according to Timothy Lu, an associate professor of biological engineering and of electrical engineering and computer science, who led the research alongside Christopher Voigt, a professor of biological engineering at MIT.
Longstanding problem put to rest
Comparing the genomes of different species—or different members of the same species—is the basis of a great deal of modern biology. DNA sequences that are conserved across species are likely to be functionally important, while variations between members of the same species can indicate different susceptibilities to disease.
The basic algorithm for determining how much two sequences of symbols have in common—the “edit distance” between them—is now more than 40 years old. And for more than 40 years, computer science researchers have been trying to improve upon it, without much success.
At the ACM Symposium on Theory of Computing (STOC), Massachusetts Institute of Technology (MIT) researchers will report that, in all likelihood, that’s because the algorithm is as good as it gets. If a widely held assumption about computational complexity is correct, then the problem of measuring the difference between two genomes—or texts, or speech samples, or anything else that can be represented as a string of symbols—can’t be solved more efficiently.
The basic algorithm for determining how much two sequences of symbols have in common—the “edit distance” between them—is now more than 40 years old. And for more than 40 years, computer science researchers have been trying to improve upon it, without much success.
At the ACM Symposium on Theory of Computing (STOC), Massachusetts Institute of Technology (MIT) researchers will report that, in all likelihood, that’s because the algorithm is as good as it gets. If a widely held assumption about computational complexity is correct, then the problem of measuring the difference between two genomes—or texts, or speech samples, or anything else that can be represented as a string of symbols—can’t be solved more efficiently.
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