Public Lab Research note


Imagining & testing Polarized Light Microscopy for Silica dust speciation

by mathew | May 21, 2014 01:04 21 May 01:04 | #10493 | #10493

What I want to do

Sample and identify silica dust particles preferably at PM2.5 (2.5 μM, roughly). Polarized light is used in the analysis of a group of crystals that includes silica. This explanation from Nikon is pretty comprehensive.

I'm interested in whether we can use polarized light microscopy to identify silica that has stuck to sticky pads.

My attempt and results

I scooped up some aggregate off the side of the road. We had a snow storm this spring and there ought to still be sand on the road from it.

I modified my usb microscope with some black paper to block its always-on LEDs:

Then I stacked my headlamp below a polarized filter, then dust, then another polarized filter offset 90 degrees, with the microscope on top.

My choice of sampling tray wasn't the best-- the HDPE container's photoelasticity is visible as rainbow colors through my rapidly constructed polariscope.

This photoelastic effect accounts for the rainbow background colors. But even with that, the silica particles pop right out from the other dust as bright rainbow dots:

Screen_Shot_2014-05-20_at_4.17.52_PM.png

There is a clear difference between the polarized light images and the unpolarized images. While the crystals still glow on in the light, they aren't nearly as sparkley:

Screen_Shot_2014-05-20_at_4.16.46_PM.png

Questions and next steps

The particles I examined were only under a 50x magnification and weren't nearly as small as I want to be able to identify. Ideally, a substantially sized sample of a sticky pad would be able to be scanned all at once. My initial hope was that a flatbed scanner could detect small particles, and current resolutions are pretty close. using this DPI calculator I figured out that a pixel on a 4800dpi scanner is 5.3μm wide. On a 6400dpi scanner, a pixel is 4μm wide. Not quite small enough to detect a 2.5μm particle, much less identify it.

But... its not impossible. Cameras made out of scanners are old news, its called "Scanography." Some people have built some elaborate scanner mods. If I can enlarge the sample by a few times, say 10x-20x, a 1"-1/2" sample would clearly present 2.5μm particles.

Challenges

I'm not sure a one to one half-inch sample is big enough, or if 10 pixels per dust particle is really enough, or if the optics I'll use will have too much distortion to make this work, but I think its worth a shot. I'm hoping a computer vision system could identify the silica particles. This would go a long way to addressing a big concern with electronic dust monitors-- figuring out what the detected particles are.

I'm headed to the library to ILL this article right now. hopefully it will give a better idea of how to go about this. Farnfield, R.A. and Birch, W.J. (1997) "Environmental Dust Monitoring Using Computer Scanned Images Obtained from Sticky Pad Poly-directional Dust Gauges", Clean Air, 27, pp73-76.


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20 Comments

cool, want some coal dust to play with?

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Nice! What kind of lens would it take to make a smartphone can work? I'm thinking about plastic or resin lenses... and portability, but probably jumping the gun. This is rad.

If the background were green or something, we could chroma key out the background and the non silica... But maybe that's not possible as you'll need full spectrum light?

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Not to derail the post, but am I the only one who thinks those pictures look like they were taken from the Hubble telescope?

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@eustatic in a bit, lets get something working first ;-)

@warren A smartphone would definitely work for identifying silica! its just a matter of magnification. The reason why I'm looking at a scanner is I want to capture a large enough area to determine the PM2.5 & PM10 concentration in the air, not just identify the small particles. Perhaps a smartphone could be used to scan a sample...

There's an instructable about using laserpointer lenses to make a microscope out of a smartphone. gotta try that soon! I have some cheap laser pointers around: http://www.instructables.com/id/10-Smartphone-to-digital-microscope-conversion/

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Ok-- apparently my math is all wrong. I thought DPI was dots per square inch. this is completely wrong. it is dots that can be placed in a line one inch long. Updating this research note momentarily

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Ok. Updated. the situation is better than I thought. A 4800dpi scanner could definitely give straight PM10 measurements, possibly with identification of the particles. Some optical tricks could give much higher resolution.

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cool. My understanding is that, at least for coal dust (=mostly crystalline silica), most particles of interest fall in the PM10 category.

GCMonitor is working on a public release on coal dust with some numbers on extent of impact from terminal operations, size of particles, and health concerns. once that goes live, I'll share it.

couldn't find that Clean Air paper through my contacts, could you share it with me, though, when you get it? I have a public health student writing about C.Silica working for GRN.

<3 eustatic

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Also, just want to repeat that corporate and government types are very sensitive to this kind of data.

Even though I am tasked to work on water, I 'm very excited about these trials. I've never seen the resistance from government and companies to citizens' monitoring water like I have to even the idea that we could be measuring our own PM.

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Neat Mathew! nice work.

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I found a scanner, the Canon 9000F and 9000F MKII, with an optical resolution of 9600dpi and an interpolated resolution of 19200dpi, or pixels 2.6μm and 1.3μm respectively. Its going for ~$160. There are also slide scanners that hit 10,000dpi, like the Pacific Image Prime Film XE scanner.

it looks with those kinds of resolutions we recognize pm2.5 particles, identifying them might not be possible. but still... pretty exciting.

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I was wondering if, since the silica kind of redirects the light (a little like fiber optic), if you could illuminate it with a directional light diagonally from one side, so that the camera doesn't see the direct light, but only the light that illuminates the silica particles. Then they might be bright against a relatively dark background.

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What could be applicable here is a lens free holographic microscope. I've been wanting to build one for a long time, maybe this will be my excuse! https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2941438/

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Hi there! We're going to be chatting about this on the OpenCall tomorrow at 2pm Central if you're interested in joining on! https://publiclab.org/wiki/open-call

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Will try to!

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Ah yes - but good question! There is also an OpenHour tonight at 8pm on Hydrogen Sulfide Monitoring Methods which should be great as well. The particulate imaging conversation is tomorrow at 2pm central.

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:) OK, Got that now!

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I think they already had a very similar previous publication, but this came up today in one of my Scholar alerts: https://pdfs.semanticscholar.org/db10/e9e28079128ec4dc828ff9f33ab61cd5e4dd.pdf EnLightenment: High resolution smartphone microscopy as an educational and public engagement platform

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Just wondering, how did you confirm that the particles that illuminate are silica? Lots of different minerals (based on their anisotropic nature) should illuminate under polarized light. Did you perform some sort of alternate analysis to verify these are silica. Common silicates, carbonates, etc should also illuminate - and the degree of illumination has to do with their birefringence and their orientation (i.e., with respect to the polarization angle) when you view/image. Very interested to hear more as I have also thought about this type of analysis for specific applications in airborne particulate research.

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@emmyallyn -- that's a great question which I think we will want to dig deeper into as we make progress on analyzing microscopic photos of dust (see #particle-imaging for some recent work on this). Would you mind re-posting that as a question using the prompt below your comment? I don't know nearly as much as you do about illumination and polarized light, so we'd deeply appreciate the help.

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