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When Pantelis Georgiou and his fellow biomedical engineers at Imperial College London decided to design an intelligent insulin pump for diabetes patients, they started at the source. "We asked ourselves, what does a pancreas do to control blood glucose?" Georgiou recalls. The answer is pretty well known: The organ relies primarily on two populations of cells—beta cells, to secrete insulin when blood glucose is high, and alpha cells, which release a hormone called glucagon when glucose levels are low. "We simulated them both in microchip form," Georgiou says. This biomimetic approach diverges from today's dominant method of delivering only insulin using a relatively simple control system.

Experimental microbial fuel cells could turn bacteria into batteries that generate electricity from biomass. The key to this technology is the ability of bacteria to transfer electrons to their surroundings—for example, to the anode of a microbial fuel cell. But if the organisms have to be in direct contact with the anode, such devices would have to have extremely large surface areas. Researchers from Aarhus University, in Denmark, report today in the journal Nature that bacteria appear to conduct electricity while separated by several millimeters, at least a thousand times as far apart than previously demonstrated. The naturally occurring electric currents, if confirmed, would allow bacteria spaced at least 12 millimeters apart to communicate electrically. The discovery might lead to new paths to treating infection and a better understanding of microbial ecosystems.

Menta SAS and LIRMM have taped out what they believe is the of worlds first MRAM-based FPGA which has patent-protected circuitry enabling compact integration of MRAM and embedded-FPGA solutions. Researchers at the Montpellier Laboratory of Informatics, Robotics and Microelectronics (LIRMM), in France, claimed in October that they had developed a FPGA circuit based on non volatile resistive memory cell.

Not so long ago, artists routinely made their own paints using all sorts of odd ingredients: clay, linseed oil, ground-up insects—whatever worked. It was a crude and rather ad hoc process, but the results were used to create some of the greatest paintings in the world. Today I and other scientists are developing our own special paints. We’re not trying to compete with Vermeer or Gauguin, though. We hope to create masterpieces of a more technical nature: optoelectronic components that will make for better photovoltaic cells, imaging sensors, and optical communications equipment. And we’re not mixing and matching ingredients quite so haphazardly. Instead, we’re using our blossoming understanding of the world of nanomaterials to design the constituents of our paints at the molecular level.

Have you ever written code that behaves correctly under a simulator only to have intermittent failures in the field? Or maybe your code no longer functions properly when you compile with a newer version of your tool chain. You review your test bench and verify 100 percent complete test coverage and that all tests have passed with no errors--yet the problem stubbornly remains. While designers understandably place great emphasis on coding and simulation, they often have only a nodding acquaintance with the internal workings of the silicon within an FPGA. As a result, incorrect logic synthesis and timing problems, rather than logic errors, are the cause of most logic failures. But writing FPGA code that creates predictable, reliable logic is simple if designers take the right steps. In FPGA design, logic synthesis and related timing closure occur during compilation. And many things, including I/O cell structure, asynchronous logic and timing constraints, can have a big impact on the compilation process, varying results with each pass through the tool chain. Let's take a closer look at ways to eliminate these variances to better and more quickly achieve timing closure.