Dave and William, thanks for the percolation discussion. I agree, the research paper did not give details on just how the sensor works, or, for that matter, how it can get reset after detection a fault. I suspect that's because the team may want to commercialize their research, as so often happens these days, and don't want to reveal proprietary information. Just a guess.
There is a product that I believe functions by heat reducing the number of particles in contact, and that is the "PTC Fuse", which is a device that looks a lot like a larger disk capacitor.When the current rises above some setpoint the resistance heating separates the particles and the device heats rapidly, moving most of the particles out of contact, which causes a large and nonlinear increase i resistance, which limits the fault current.
What they don't mention in the description is that these devices have a finite life, and after that the trip current becomes lower and lower.
@przemek: Thanks for a good explanation of the concept of percolation. The reason I mentioned graph theory is that it looks like work done by Professor Meguid's group (although it's not clear from this article) has been mainly focused on computational modeling of these materials -- not actually making them in the lab. There is an entire branch (no pun intended!) of graph theory which deals with percolation -- called, unsuprisingly, percolation theory.
I'd still like to know what a sensor based on this concept would actually measure, and how it would actually work. If you wanted to locate a crack, it seems like you would need a way to accurately measure local conductivity changes on a fairly small scale. And in order to understand what you were measuring, you would need to have a good understanding of how the presence of a crack changes the alignment of the nanotubes -- which seems like it could be an even tougher compuational challenge.
'percolation' is a physical phenomenon, referring to topological arrangements within a multi-component solid. Imagine for instance a matrix of substance A with embedded uniform spheres of conductive substance B. As you increase the concentration of B, at some point they will start touching each other on a macroscopic scale, so that the material would become conductive---that would be an example of percolation.
The concept is used in many contexts, for instance to describe flow of oil through pores in a rock matrix.
I can see how this could indeed work to indicate the start of failure. That part does make sense. But the question comes as to how to reset the detection scheme after the repairs are done. In the same way that embedded fiber optics do detect failures, the change is permanent and nonreverseable. Broken fibers and gaps between the microfibers just do not repair. The fix is a replacement. So while the detection system could work, the repairs would equate to replacements.
@Ann: Can you walk me through how a sensor like this would work? I understand that Professor Meguid's group is studying how alignment of the nanotubes or nanowires affects the electrical conductivity of the adhesive. Is the idea that the presence of a crack would alter the alignment of the nanotubes or nanowires, and that this could be measured as a change in conductivity?
The use of the term "percolation threshold" seems to indicate that they are using graph theory, which is a good example of how seemingly abstract branches of mathematics can sometimes have extremely practical uses.
This should contribute greatly to our understanding of failure mechanisms of composites in real-world applications. After all, failure mechanisms of steels is well understood, but composites are in still comparatively new in many of these applications. This is an important story.
The idea that some sort of nanotechnology adhesive can help predict a structural failure in a composite airplane wing is definitely science fiction-like. How far away is this technology from being commercialized given that composites are increasingly being deployed in planes?
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.
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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.