Anyone know of commercial development of this visual CYA test?

[KKell]

Hi,
I'm just reordering CYA testing chemicals and like everyone I hate and loathe the turbidity test. I was doing a quick search through google scholar on whether there are any other methods available, and through my University library access I was able to read this 2014 paper on a visual test that seems to work much like the color matching of the PH test. Colorimetric and visual read-out determination of cyanuric acid exploiting the interaction between melamine and silver nanoparticles

I'm throwing in a screenshot of the picture of what the test might look like:

Is anyone aware of any attempts to commercially develop this? I didn't have the time to read the paper in detail in order to fully understand just what chemicals you need, but the person developing it has as his primary research interest " Low-Cost Diagnostics", [Dionysios Christodouleas | Chemistry | UMass Lowell] so I was hoping it might be something that could be done somewhat cheaply.

The article is behind a paywall, and I don't want to promote illegal ways to circumvent that, but perhaps through your local library you might be able to get an inter-library loan copy, or if you've got library access to any kind of University affiliation.

So yeah, anyone know if this can or is being made commercially?

 

[JoyfulNoise]

There are all sorts of color based tests with melamine causing a change in pH by removing/reacting with CYA but as far as I can tell, the color discrimination is very poor. This is how CYA test strips work. There’s really no silver bullet (pub intended!) here. In fact, that image you posted looks pretty terrible to me in terms of color gradation. Perhaps there’s another type of metal nanoparticle (Au nanoparticles can have some interesting colors) that would work better...

Will it be cheaper and more easily commercialized than the melamine turbidity test? I sincerely doubt it...

 

[CombatYoga]

I think an AI-based visual recognition service could be trained to recognize different levels of CYA.
This reminds me of a use case where an AI system was trained to recognize pre-cancerous cells from images.
Hmmm...not enough money in this particular use case to cause anyone to invest. Would need to be a skunk works project.

 

[LiveHereNow]

I think an AI-based visual recognition service could be trained to recognize different levels of CYA.
This reminds me of a use case where an AI system was trained to recognize pre-cancerous cells from images.
Hmmm...not enough money in this particular use case to cause anyone to invest. Would need to be a skunk works project.

What if your phone "looked" at the test(s) and gave you a more specific readout then a person visually swagging it? You pour some water into the test unit, drop in reagents, hold up your phone and get back numerical data.

 

[Donldson]

What if your phone "looked" at the test(s) and gave you a more specific readout then a person visually swagging it? You pour some water into the test unit, drop in reagents, hold up your phone and get back numerical data.

Any time I see a suggestion like this I am reminded of XKCD

 

[Katodude]

So the AI required to look at a picture of the dot and determine if it was there is probably not all that hard to do.

For example checking if the photo is of a bird is now extremely easy to do. What was hard before is sometimes easier now.

 

[JoyfulNoise]

What gets lost in all these discussions of how to build a better CYA mousetrap is the simple truth that measuring and achieving an exact CYA level is really not as important as most people think it is. A pool can be easily managed with CYA anywhere between 30 and 100ppm and if your reading is anywhere between +/-10ppm of the "true value", you'll be just fine. What determines if a pool will get in to trouble has much more to do with operator error (ie, lazy pool owner letting chemical levels swing all over the place) than the exact quantity of CYA in the water...consistency is much more important than precision.