# Phenol Red - pH Indicator

#### Glenn Davis

#### 2020-04-01

Phenol red is an indicator commonly used to measure pH in swimming pool test kits, see e.g. [2]. The goal of this colorSpec vignette is to reproduce the colors seen in such a test kit, for typical values of pool pH. Calculations like this one might make a good project for a college freshman chemistry class. Featured functions in this vignette are: `interpolate()` and `calibrate()`.

    library( colorSpec )
    library( spacesRGB )    # for functions plotPatchesRGB() and SignalRGBfromLinearRGB()

## Absorbance Spectra at Different pH Values

The absorbance data for phenol red has already been digitized from [1]:

    path = system.file( "extdata/stains/PhenolRed-Fig7.txt", package="colorSpec" )
    wave = 350:650
    phenolred = readSpectra( path, wavelength=wave )
    par( omi=c(0,0,0,0), mai=c(0.6,0.7,0.4,0.2) )
    plot( phenolred, main='Absorbance Spectra of Phenol Red at Different pH Values' )

Compare this plot with [1], Fig. 7. Unfortunately, the concentration and optical path length are unknown, but these curves can still be used as ‘relative absorbance’.

## Absorbance at Selected Wavelengths

We investigate how absorbance depends on pH for a few selected wavelengths.

    wavesel = c( 365, 430, 477, 520, 560, 590 )  # 365 and 477 are 'isosbestic points'
    mat = apply( as.matrix(wavesel), 1, function( lambda ) { as.numeric(lambda == wave) } )
    colnames( mat ) = sprintf( "%g nm", wavesel )
    mono = colorSpec( mat, wavelength=wave, quantity='power' )
    RGB = product( mono, BT.709.RGB, wavelength=wave )  # this is *linear* RGB
    colvec = grDevices::rgb( SignalRGBfromLinearRGB( RGB/max(RGB), which='scene' )$RGB )

    phenolsel = resample( phenolred, wavesel )
    pH = as.numeric( sub( '[^0-9]*([0-9]+)$', '\\1', specnames(phenolred) ) )
    pHvec = seq(min(pH),max(pH),by=0.05)
    phenolsel = interpolate( phenolsel, pH, pHvec )
    mat = t( as.matrix( phenolsel ) )
    par( omi=c(0,0,0,0), mai=c(0.8,0.9,0.6,0.4) )
    plot( range(pH), range(mat), las=1, xlab='pH', ylab='absorbance', type='n' )
    grid( lty=1 ) ; abline( h=0 )
    matlines( pHvec, mat, lwd=3, col=colvec, lty=1 )
    title( "Absorbance of Phenol Red at Selected Wavelengths")
    legend( 'topleft', specnames(mono), col=colvec, lty=1, lwd=3, bty='n' )

Note that the curves for the isosbestic points 365 and 477 nm are approximately flat, as expected. But for 430 nm the curve is distinctly non-monotone. This indicates that the solution is not truly a mixture of the acidic and basic species (especially for pH \(\le\) 6), and there may be an undesired side reaction, see [3].

## Interpolation from pH=6.8 to pH=8.2

Swimming pools should be slightly basic; a standard test kit covers the range from pH=6.8 to pH=8.2.

    pHvec = seq(6.8,8.2,by=0.2)
    phenolpool = interpolate( phenolred, pH, pHvec )
    par( omi=c(0,0,0,0), mai=c(0.6,0.7,0.4,0.2) )
    plot( phenolpool, main="Absorbance Spectra of Phenol Red at Swimming Pool pH Values" )

The rest of this section is best viewed on a display calibrated for sRGB, see [4].

    # create an uncalibrated 'material responder'
    testkit = product( D65.1nm, 'solution', BT.709.RGB, wave=wave )
    # now calibrate so that fully transparent pure water has response RGB=c(1,1,1)
    testkit = calibrate( testkit, response=1 )
    RGB = product( phenolpool, testkit )
    RGB

    ##                R         G         B
    ## pH=6.8 1.0282473 0.6840105 0.2260205
    ## pH=7   1.0237233 0.5938036 0.2506686
    ## pH=7.2 1.0182971 0.4961330 0.2788955
    ## pH=7.4 1.0124869 0.4022827 0.3100400
    ## pH=7.6 1.0067433 0.3195781 0.3440245
    ## pH=7.8 1.0014227 0.2505541 0.3812950
    ## pH=8   0.9969035 0.1947707 0.4225796
    ## pH=8.2 0.9935212 0.1503867 0.4683717

Unfortunately, in some cases the red value is greater than 1 (G and B are OK). The color is outside the sRGB gamut. Start over and recalibrate.

    testkit = product( D65.1nm, 'solution', BT.709.RGB, wave=wave )
    # recalibrate, but lower the background a little, to allow more 'headroom' for indicator colors
    bglin = 0.96  #  graylevel for the background, linear
    testkit = calibrate( testkit, response=bglin )
    RGB = product( phenolpool, testkit )   # this is *linear* sRGB
    RGB

    ##                R         G         B
    ## pH=6.8 0.9871174 0.6566501 0.2169797
    ## pH=7   0.9827743 0.5700514 0.2406419
    ## pH=7.2 0.9775652 0.4762877 0.2677396
    ## pH=7.4 0.9719874 0.3861913 0.2976384
    ## pH=7.6 0.9664736 0.3067950 0.3302635
    ## pH=7.8 0.9613658 0.2405320 0.3660432
    ## pH=8   0.9570273 0.1869799 0.4056764
    ## pH=8.2 0.9537803 0.1443713 0.4496368

All values have been multiplied by `bglin`, and are now OK. Draw the RGB patches on a white background multiplied by the same amount.

    df.RGB = data.frame( LEFT=1:nrow(RGB), TOP=0, WIDTH=1, HEIGHT=2 )
    df.RGB$RGB = RGB
    par( omi=c(0,0,0,0), mai=c(0.3,0,0.3,0) )
    plotPatchesRGB( df.RGB, space='sRGB', which='scene', labels=F, background=bglin )
    text( (1:nrow(RGB)) + 0.5, 2, sprintf("%.1f",pHvec), adj=c(0.5,1.2), xpd=NA )
    title( main='Calculated Colors for pH from 6.8 to 8.2' )

The background color is that of pure water, and is not the full RGB=(255,255,255).

In the first figure above, the phenol red concentration and optical path length are unknown. Compared to a real test kit, the calculated colors look a little faded. An absorbance multiplier can easily tweak the unknown concentration, as follows.

    tweak = 1.3
    phenolpool = multiply( phenolpool, tweak )
    df.RGB = data.frame( LEFT=1:nrow(RGB), TOP=0, WIDTH=1, HEIGHT=2 )
    df.RGB$RGB = product( phenolpool, testkit ) # this is *linear scene* sRGB
    par( omi=c(0,0,0,0), mai=c(0.3,0,0.3,0) )
    plotPatchesRGB( df.RGB, space='sRGB', which='scene', background=bglin, labels=F )
    text( (1:nrow(RGB)) + 0.5, 2, sprintf("%.1f",pHvec), adj=c(0.5,1.2), xpd=NA )
    main = sprintf( 'Calculated Colors for pH from 6.8 to 8.2 (absorbance multiplier=%g)', tweak )
    title( main=main )

These colors are a better match to those in the test kit.

## References

[1] LUIGI ROVATI, Luca Ferrari, Paola Fabbri and PILATI, Francesco. Plastic Optical Fiber pH Sensor Using a Sol-Gel Sensing Matrix. In: MOH. YASIN Sulaiman W. Harun and Hamzah AROF, eds. Fiber Optic Sensors [online]. B.m.: InTech, 2012. Available at: doi:10.5772/26517

[2] TAYLOR TECHNOLOGIES, Inc. K-1000 sureCHECK Safety Test, Bromine & Chlorine (hi range), OT/pH [online]. 2017. Available at: https://www.taylortechnologies.com/en/product/test-kits/surecheck-safety-test-bromine-chlorine-hi-range-otph--K-1000

[3] WIKIPEDIA. pH indicator — Wikipedia, The Free Encyclopedia [online]. 2017. Available at: https://en.wikipedia.org/w/index.php?title=PH_indicator. [Online; accessed 10-November-2017]

[4] WIKIPEDIA. SRGB — wikipedia, the free encyclopedia [online]. 2017. Available at: https://en.wikipedia.org/w/index.php?title=SRGB. [Online; accessed 13-November-2017]

## Session Information

    R version 3.6.3 (2020-02-29)
    Platform: i386-w64-mingw32/i386 (32-bit)
    Running under: Windows 7 (build 7601) Service Pack 1

    Matrix products: default

    locale:
    [1] LC_COLLATE=C
    [2] LC_CTYPE=English_United States.1252
    [3] LC_MONETARY=English_United States.1252
    [4] LC_NUMERIC=C
    [5] LC_TIME=English_United States.1252

    attached base packages:
    [1] stats     graphics  grDevices utils     datasets  methods   base

    other attached packages:
    [1] spacesRGB_1.3-0 colorSpec_1.2-1

    loaded via a namespace (and not attached):
     [1] Rcpp_1.0.3           digest_0.6.25        spacesXYZ_1.1-1
     [4] MASS_7.3-51.5        magrittr_1.5         evaluate_0.14
     [7] rlang_0.4.4          stringi_1.4.6        rmarkdown_2.1
    [10] tools_3.6.3          stringr_1.4.0        xfun_0.12
    [13] yaml_2.2.1           compiler_3.6.3       microbenchmark_1.4-7
    [16] htmltools_0.4.0      knitr_1.28