In
this article, Yao Lu and Peter B. Harrington explore alternate methods to solve
cases of arson. The key part of their study was to find cheaper and more
accurate detection methods for ignitable liquids. The second leading cause of
deaths and injuries and the leading cause of fires is arson. Throughout the
article, Lu and Harrington use gas chromatography along with other methods to
find a solution.
One of the main problems in
detecting ignitable chemicals is the fact that chemicals can evaporate, and
additional pyrolysis products can be produced that can alter the composition of
the chemicals. This results in Lu and Harrington designing a new type of GC-DMS
(Gas Chromatograph – Differential mobility Spectrum) that will use a computer
statistic system called FuRES (multivariate classification algorithm that uses
fuzzy logic to classify data). The computer uses the algorithm along with the
data from the GC-DMS to infer what chemicals were used in the fire.
The next part of the article
describes the procedure for the experiment. Lu and Harrington used synthetic
carpet from a local store for their experiment. They then applied common
chemicals that arsons use.
The final part of the article
describes their findings. They use graphs from the GC-DMS to analyze the
results of gasoline, diesel, lighter fuel, and turpentine. In conclusion, their
findings were useful for the future experiments involving GC-DMS. Even though
this article was written in 2007, the findings will benefit the world today, if
they have not already.
1. Why did they use carpets to measure the arson compounds?
ReplyDelete2. Why did diesel have fuzzy/unclear peaks? And why did the others not?
1. Any reason for why the diesel had the least clear peaks?
ReplyDelete2. Which sample fuel, of the 3, had the clearest peaks? Why?
1. What other functions does the differential mobility spectrometer have for different fields?
ReplyDelete2. How do the properties of compounds analyzed change following arson?
1. What are the characteristics of a "clear peak"? Describe how clear peaks look and how fuzzy peaks look. (Don't tell me one is fuzzy and the other isn't!)
ReplyDelete2. Were mathematicians on this specific research team or was there collaboration from different sites?
1. What mechanism in the GC-DMS allows it that increased degree of precision?
ReplyDelete2. What was the degree of error in traditional GC analysis that made GC-DMS analysis more viable?
1. Did they only use four substances to test?
ReplyDelete2. Why did they choose to use synthetic carpet?
What are the characteristics of a "clear peak"? Describe how clear peaks look and how fuzzy peaks look. (Don't tell me one is fuzzy and the other isn't!)
ReplyDeletehttp://www.chromatographyonline.com/gc-troubleshooting-petrochemical-analysis
http://www.chromedia.org/chromedia?waxtrapp=ocgdzGsHiemBpdmBlIEcCvBaC&subNav=bkvfkEsHiemBpdmBlIEcCvBaCfC
Clear peaks will be symmetrical, non-overlapping, and easy to decipher between other peaks in the chromatogram. Fuzzy peaks can be non-symmetrical where it has a distorted or ‘tailing’ peak or could be ‘fronting’. This is where one side of the peak has a different slope than the other. Fuzzy peaks could also look like multiple peaks have been smeared together (almost like overlapping one another) and the peaks cannot be differentiated.
Why did they choose to use synthetic carpet?
https://strathmoredesign.com/carpethowitsmade
This experiment was trying to find cheaper yet more accurate ways to solve cases of arson and to do so, they would have to replicate the most common conditions found in these cases. With most arson cases occurring in homes using carpet in their experiments is logical so they know what carpet does to the results if any and if it makes detection harder. This is supported by the fact that almost 90% of carpet today is made of a synthetic fiber, whether it be nylon or polyester.
What was the degree of error in traditional GC analysis that made GC-DMS analysis more viable?
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5084691/
The GC-DMS analysis was most likely more viable because custom software can be made specifically for the identification a scientist is trying to accomplish. The GC-DMS also helps scientists be able to focus on single chemical identification by trying to determine of a target compound is present within more complex sample types (such as accelerants). It wasn’t that a traditional GC analysis had a major degree of error, it was just the fact that the samples used in this experiment had more complex compositions and wasn’t as easily identified with the GC.
Any reason for why the diesel had the least clear peaks?
https://core.ac.uk/download/pdf/82505359.pdf
Diesel had the least clear peaks most likely because of how many compounds are in the make-up of diesel. Scientists devoted to studying accelerants say that it is because of its composition that makes it so very hard to identify.