As electronics devices become smaller and smaller, the challenges faced when designing them become questions of scale. Semiconductors, for example, have a thin, 35-angstrom layer of silicon dioxide used as an insulating material. As the chips get smaller, the insulating material must also proportionally shrink. But once the thickness falls below 20 angstroms, the silicon layer is no longer an effective insulator. Researchers at Motorola, Pacific Northwest National Labs, and Oak Ridge National Lab (ORNL) are joining forces for development of new insulating materials from crystalline oxides on silicons that are expected to have higher dielectric strengths and higher capacitance. "We are able to eliminate one of the hurdles to continuing the current rate of growth in the semiconductor industry," says Rodney McKee, a researcher at ORNL Metals and Ceramics Div. "If Moore's Law continues to hold true, we'll need the new insulating materials in just a few years." For more information, call Jan Haerer at (865) 241-7613.
Truchard will be presented the award at the 2014 Golden Mousetrap Awards ceremony during the co-located events Pacific Design & Manufacturing, MD&M West, WestPack, PLASTEC West, Electronics West, ATX West, and AeroCon.
In a bid to boost the viability of lithium-based electric car batteries, a team at Lawrence Berkeley National Laboratory has developed a chemistry that could possibly double an EV’s driving range while cutting its battery cost in half.
For industrial control applications, or even a simple assembly line, that machine can go almost 24/7 without a break. But what happens when the task is a little more complex? That’s where the “smart” machine would come in. The smart machine is one that has some simple (or complex in some cases) processing capability to be able to adapt to changing conditions. Such machines are suited for a host of applications, including automotive, aerospace, defense, medical, computers and electronics, telecommunications, consumer goods, and so on. This discussion will examine what’s possible with smart machines, and what tradeoffs need to be made to implement such a solution.