UV reactive bead spectra
Background
I was interested in designing some educational experiments using UV-reactive beads to teach about the presence/absence and intensity of UV light under different atmospheric conditions. The beads turn from clear or colorless to various bright colors when exposed to UV light. Unfortunately, these beads are just too sensitive – they even react strongly to the stray 400 nm light coming through glass windows. And reach full color intensity within a minute, even at 51° N in February! It's fun to watch, but not very useful for detecting physiological UV conditions for vitamin D synthesis.
I don't have a lot of scientific information abou these, so the range of UV light needed for the color change is not well characterized, and the resultant absorbance spectra of the beads (related to their aparent colors) is not readily available. I decided to study them with a reflectance spectrophotometer to see what I could learn.
It may not be useful for the educational project I had in mind, but I'll write it up here anyway, along with the R-code used to analyze the data….
Experimental
I ordered UV Reactive beads from UV gear, UK.
I used a table in the garden on a sunny day for the experiments. The sky was open directly above and direct sunlight came from the south. There were a few leafless tree branches in the way, and some buildings nearby, so it was not full sky exposure, but at least there was full direct sunlight. The table was covered with a small white blanket to provide a consistent background. The beads equibilbrated 10-15 min in direct sunlight before spectral measurements were made.
I used an Ocean Optics model USB2000+ spectrometer connected to a 1 meter UV-Vis fiber optic cable (part number QP400-1-UV-VIS from Ocean Optics) with a cosine correction filter at the end (Ocean Optics part CC-3-UV-S) to minimize stray light. The spectrometer was connected by USB to a MacBook Pro (OS X mountain lion 10.8.1) running SpectraSuite software for data collection. Spectra were measured with 30 averages in reflectance mode and saved as tab-delimited text files. The reflectance measurements required a 'reference spectrum' (light spectrum) of the white blanket and a second, 'dark' reference, which was obtained by blocking the end of the cosine correction filter. To collect the reflectance spectra, I pointed the fiber optic light pipe at individual beads from a distance of < 0.5 cm.
Spectral analysis can be done in the SpectraSuite software, however, many basic functions had not (yet?) been implemented in the OS X version of the software. Also, I wanted to practice my R skills, so I decided to load it into R and see what I could learn. R has multiple spectroscopy packages, and in fact a new one has come out since I started this project. I looked into using hyperspec, but the data structure seemed overly complicated for the simple analysis I had in mind. So what follows is my simple R analysis of reflectance data on sunlight-exposed UV beads.
Load in the Data
# change working directory
try(setwd("/Users/suz/Documents/vitD Schools/UV bead exp 19022013/spectrometer data/"))
# data is tab-separated, with a header. The end of file wasn't recognized
# by R automatically, but a read function can specify the number of rows
# to read.
spec.read <- function(spec.name) {
read.table(spec.name, sep = "\t", skip = 17, nrows = 2048)
}
# the function can then read in all the files ending in '.txt', put them
# in a list.
spec.files <- list.files(pattern = ".txt")
df.list <- lapply(spec.files, spec.read)
# convert the list to a matrix: the first column is the wavelengths and
# the other columns are experimental data -- one reflectance measurement
# at each wavelength.
spec.mat <- matrix(df.list[[1]][, 1], nrow = 2048, ncol = (1 + length(spec.files)))
spec.mat[, 2:11] <- sapply(df.list, "[[", 2)
matplot(spec.mat[, 1], spec.mat[, 2:11], type = "l", lty = 1, lwd = 3, xlab = "wavelength (nm)",
ylab = "reflectance", main = "UV color changing beads, after UV exposure")
text(500, 25000, "Raw Data")
Looks like we need to do some clean-up!
Clean up the data
Baselines and edges
At the edges of the spectral range, the reflectance data is dominated by noise, so it isn't useful. The baselines for the different spectra also need aligning, and we'll scale them to the same intensity for comparison. The intensity range observed in the data depends somewhat on the angle of the probe, even with a cos filter in place.
# define terms for the processing:
nm.min <- 400
nm.max <- 800 # edges of the displayed spectrum
base.min <- 720
base.max <- 900 # define baseline correction range
peak.range.min <- 420
peak.range.max <- 680 # where to find peaks for scaling.
# remove ends of the data range that consist of noise
spec.mat <- spec.mat[(spec.mat[, 1] > nm.min) & (spec.mat[, 1] < nm.max), ]
# normalize baselines, set baseline range = 0.
spec.base <- colMeans(spec.mat[(spec.mat[, 1] > base.min) & (spec.mat[, 1] <
base.max), ])
spec.base[1] <- 0 # don't shift the wavelengths
spec.mat <- scale(spec.mat, center = spec.base, scale = FALSE)
Choose colors for the plot by relating the file names to R's built-in color names.
bead.col <- sapply(strsplit(spec.files, " bead"), "[[", 1)
# replace un-recognized colors with r-recognized colors (see 'colors()')
bead.col <- gsub("darker pink", "magenta", bead.col)
bead.col <- gsub("dk ", "dark", bead.col)
bead.col <- gsub("lt ", "light", bead.col)
bead.col <- gsub("lighter ", "light", bead.col)
# plot corrected data
matplot(spec.mat[, 1], spec.mat[, 2:11], type = "l", lty = 1, lwd = 3, col = bead.col,
xlab = "wavelength (nm)", ylab = "reflectance", main = "UV color changing beads, after UV exposure")
text(500, 10, "Baseline Corrected")
From this plot, we can see that the lighter colored beads have smaller peaks than the darker beads. The lighter color probably represents less dye in the beads. There seems to be a lot of variation in the peak intensity of some beads, particularly the yellow beads and the dark blue beads. Based on the width of the peaks, the purple and magenta beads appear to have mixtures of dyes for both pink and blue colors. The dark blue beads appear to be either a mixture of all the dye colors or a mixture of pink and blue, but much more dye is used than for the paler pink or blue beads. The yellow bead spectra is oddly shaped on the short wavelength side, probably due to instrument cutoffs around 400 nm.
Scaling and smoothing
Now I'll scale the data to the same range. It turns out that the R command 'scale' is perfect for this.
# scale the peaks based on the min reflected intensity
peak.range <- which((spec.mat[, 1] > peak.range.min) & (spec.mat[, 1] < peak.range.max))
spec.min <- apply(spec.mat[peak.range, ], 2, min)
spec.min[1] <- 1 # don't scale the wavelengths
spec.mat <- scale(spec.mat, center = FALSE, scale = abs(spec.min))
The spectra are also jittery due to noise. This can be removed by filtering. This filters over a range of 10 points.
data.mat <- spec.mat[, 2:11]
dataf.mat <- apply(data.mat, 2, filter, rep(1, 10))
dataf.mat <- dataf.mat/10
specf.mat <- matrix(c(spec.mat[, 1], dataf.mat), nrow = dim(spec.mat)[1], ncol = dim(spec.mat)[2],
byrow = FALSE)
matplot(specf.mat[, 1], specf.mat[, 2:11], type = "l", lty = 1, lwd = 3, col = bead.col,
xlab = "wavelength (nm)", ylab = "reflectance", main = "UV color changing beads, after UV exposure")
text(500, 0.2, "Scaled and Smoothed")
I could attempt to prettify the spectra further by using actual colors from pictures of the beads. It looks like the Bioconductor project has a package 'EBImage' that should be just what I want, but it looks like I need to update to R version 3.0.1 in order to run it. So I guess I get some spot colors from JImage.
bead.yellow <- rgb(185, 155, 85, maxColorValue = 255)
bead.orange <- rgb(208, 155, 82, maxColorValue = 255)
bead.purple <- rgb(110, 25, 125, maxColorValue = 255)
bead.pink <- rgb(190, 100, 120, maxColorValue = 255)
bead.dkblu <- rgb(22, 18, 120, maxColorValue = 255)
bead.ltblu <- rgb(130, 135, 157, maxColorValue = 255)
bead.dkpink <- rgb(200, 25, 140, maxColorValue = 255)
bead.col2 <- c(bead.dkpink, bead.dkblu, bead.dkblu, bead.pink, bead.ltblu, bead.orange,
bead.pink, bead.purple, bead.yellow, bead.yellow)
matplot(specf.mat[, 1], specf.mat[, 2:11], type = "l", lty = 1, lwd = 3, col = bead.col2,
xlab = "wavelength (nm)", ylab = "reflectance", main = "UV color changing beads, after UV exposure")
text(500, 0.2, "Colors from Photo")
Analysis
I can carry this anlaysis further by quantifying the wavelength of the peak absorbance and the peak width (usually Full Width at Half Maximum – FWHM) for each spectrum. This could be useful in further analyses, reports, or as a feature in a machine learning approach.
To extract this information, I could try to fit a series of gaussians to the peak, representing the fraction of pink, blue or yellow dye present, but the quality of the data doesn't really justify this, particularly as I don't have a good shape for the yellow absorbance peak or adequate reference data for each of the dyes. As a quick and dirty method, I'll take the median position of the data values that are at 95% of peak. That should give something in the center of the peak. Since the peaks have all been scaled, that corresponds to the center of the data values < -0.95.
Likewise, the usual peak width (FWHM) woud be the range of values < -0.5, however, the poor baseline at shorter wavelengths makes this range more or less unusable. For this reason, we can take a more well-behaved approaximate peak width measurement as the range of reflectance values < -0.8.
# approximate peak wavelength
indcs <- apply(specf.mat[, 2:11], 2, function(x) median(which(x <= (-0.95))))
pks <- specf.mat[indcs, 1]
# approximate peak width
lowidx <- apply(specf.mat[, 2:11], 2, function(x) min(which(x <= (-0.8))))
highidx <- apply(specf.mat[, 2:11], 2, function(x) max(which(x <= (-0.8))))
pkwidth80 <- (specf.mat[240, 1] - specf.mat[140, 1])/100 * (highidx - lowidx)
features <- data.frame(pks, pkwidth80, bead.col, bead.col2)
features <- features[order(pks), ]
features
## pks pkwidth80 bead.col bead.col2
## 10 436.4 75.21 yellow #B99B55
## 6 449.8 88.86 orange #D09B52
## 9 451.7 98.07 yellow #B99B55
## 7 529.3 111.35 pink #BE6478
## 4 533.6 99.18 lightpink #BE6478
## 1 549.8 110.61 magenta #C8198C
## 8 568.7 133.10 purple #6E197D
## 3 581.1 179.93 darkblue #161278
## 2 585.4 136.79 darkblue #161278
## 5 603.0 76.32 lightblue #82879D
# save your work!
write.csv(features, "UVbead data features.csv", quote = TRUE)
One side effect of this is that we now have a small table of metrics that describe the relatively large original data set reasonably accurately and could be used to classify new data. In current data analytics parlance, this is known as 'feature extraction'. In traditional science, these characterizing features could be combined with others from different studies (crystallography, electrochemistry, UV-vis, IR, Raman, NMR, …) to help predict the effects of a chemical change or a different chemical environment on the behaviour of the molecule. Such studies are traditionally used to help direct synthetic chemists toward better products.
Conclusions
From this analysis, we can see that the blue beads are absorbing at longer wavelengths than the yellow, and the pink and purple beads have absorbances in between. The darker colors have broader absorbance peaks than the lighter colors, with the darkest blue having a range that appears to cover the purple, yellow and blue regions. These darker beads probably contain combinations of the dyes used for the different colors, and not just more of the dye used for the light blue beads.
The reflectance spectra are not as observant as our eyes. For instance, the yellow and orange beads are readily distinguished by eye, but not so clearly in the observed spectra or the extracted features. This may be due to the 400nm cutoff of the light pipe, which distorts the peak shapes for the yellow and orange beads. Ideally, we could observe the changes in the absorption spectra over the whole range 280-800 nm as a function of time. The current reflectance spectrometer setup, however, is only capable of capturing the 400-750 nm range. This means that we do not have access to the interesting behavior of these dyes at shorter wavelengths.
Chemically, I expect that absorption of the UV light in the 300-360 nm range causes a reversible conformation change in the dye molecules, as has long been known for the azo-benzenes and their derivatives. After the conformation change, the absorption maximum of the dye is shifted to a much longer wavelength. If the UV dyes in these beads are very closely related to each other, is likely that the yellow beads absorb at relatively short UV wavelengths and the blue beads at longer wavelengths before the transition, however, without measuring the UV absorption spectra we cannot know this. It is quite possible that their UV absorption spectra are nearly indistinguishable and the effects of their chemical differences are only apparent in the visible spectra. Without access to better hardware or more information about the molecules involved there is no way to know.
Next steps
We do have access to one thing that varies in the appropriate way. The experiments shown here were taken at relatively low UV light levels (February in England). During the summer, the angle of variaton of the sun is much larger. At dawn, it is at the horizon, while at noon, it is about 60° higher. Since light scattering in the atmosphere is a strong function of wavelength, the relative intensities of light at 300, 360, and 400 nm will vary with the angle of the sun. If the beads have different absorption peaks in the UV range, the time dependence of their color changes should vary by the time of day.
The simplest way to measure this is not with a spectrometer, but probably by following color changes in video images.
