Our instrument consists of source, sample containment, and detector, each described further below, arranged using Dollar Tree plastic milk crates and some DVD cases to maintain the geometry. Each of the source and sample crates had some sides removed, as-needed, to allow unobstructed passage of light and easy access. All items were arranged on a black plastic tray to contain spills. Black fabric was placed over the entire assembly during data acquisition to keep out ambient light. Black construction paper was used in several places, including over unneeded portions of the source, to minimize reflections and stray light.

SourceAn NPower In-Vision 7” (18 cm) digital photo frame, model NDF6052-DTE, was used for the work reported here. Some earlier work was completedusing a Dell 15” LCD computer monitor or the display of an Asus Eee 701SD netbook computer. In all cases a pure white image (jpg or blank presentation slide) was displayed on the screen during data acquisition. The photo frame was inverted with respect to its intended operation to allow access to the controls and proximity to the samples. Its stand was inserted upside-down and shimmed with CD and VHS cases.

SampleTableCraft Products Company 2 oz (60 ml) salt and pepper shakers, model 154S&P (and similar of unknown manufacture), and TableCraft Products Company ½ oz (15 ml) salt and pepper shakers, model

30S&P, were used, without their caps, as sample cuvettes. The cuvettes were elevated on DVD cases as needed. Sample concentrations reported below are typically milliliters of the stock solutions per cuvette.

DetectorA KODAK DC4800 Zoom digital camera was used in fully automatic close-up mode to acquire images of the cuvettes in front of the source. The top portion of a tripod was attached to the detector crate to position the camera.

Typical Camera SettingsWhite Balance Color Temperature, 7000 KColor Mode Neutral ColorQuality 0.8 MPExposure Metering Multi-PatternSharpness StandardISO Speed 100 – 400, AutoShutter Speed AutoDate/Time Stamp NoneZoom 3.0 – 3.9Flash Off

The camera’s memory card was transferred to a Dell Vostro 200 computer running Ubuntu Linux 10.04 LTS for image processing.

MATERIALS AND METHODSSolution Preparation and Volume MeasurementStock solutions of Great Value Assorted Food Colors were made by diluting 8-10 drops of color in about 500 ml of water. The various oils, Kroger Value Distilled White Vinegar, Pine Glo Ammonia, and the Home Store Bleach were used as-received.

Solutions were prepared in the cuvettes immediately prior to analysis. Volume measurements were made with the syringes shown below. A 30 ml Flavor Injector basting syringe was used for larger volumes of water. A 10 ml CVS pharmacy Oral Syringe or eye dropper was used for all other volume measurements.

INTRODUCTIONWe report on work, still in progress, using a simple homemade spectrometer. The broad goal is to introduce science concepts to secondary students using common household items. Of immediate concern is the development of tools to be be used for more significant work in the future. Areas investigated so far include: Beer’s Law calibrations, including two-component mixtures; kinetics of bleaching; monitoring pH changes; and the classification of vegetable oils.

INSTRUMENT

Spectroscopy for Secondary Students:Exploring the Limits of Analysis at Home

Christopher A. Marks, camarks@yahoo.comJames M. Quagliano, St. Christopher’s School

Richmond, VA USA

Red Cabbage pH Indicator Preparation1. Put about ¼ of a very small head of red cabbage in a Vita-Prep blender.2. Added about 100 ml of water.3. Blended on high for several minutes.4. Strained through a coffee filter, rinsing blender with a 30 – 50 ml water.5. Added Assured 50% Isopropyl Alcohol to increase the total volume by about

25%.6. Some further settling of solids was observed a day later; the solids were

removed by decanting the liquid into a clean bottle.The indicator was stored at room temperature in several small plastic bottles.

Image Acquisition and Data ProcessingA sample cuvette and reference cuvette (water or mineral oil, as appropriate) were placed side-by-side immediately in front of the source. A small piece of black construction paper was inserted between the two cuvettes. Images were taken after depressing the shutter button half-way to allow automatic focus and exposure metering and then fully depressing the shutter button.

The images are analyzed using the GNU Image Manipulation Program (GIMP 2.6.X). Red, green, and blue (RGB) intensities (I) are averaged from appropriate image regions (containing thousands of pixels) for the blank and the sample. The sample absorbances are calculated as -log10(I

sample/I

blank) for

each of the red, green, and blue channels. Determination of the red channel Isample

is shown below; Iblank

is determined by moving the selection region to the

reference cuvette at the left.

ACKNOWLEDGEMENTSThe authors would like to thank John R. Quagliano for many helpful discussions and suggestions during the course of this work. Chris also thanks James Burger (BurgerMetrics) for his enthusiastic support (including JIMIA software) during the very early stages of this work. Mr. John Kloke II donated the Kodak DC4800 camera that was used for this work.

REFERENCESKohl, S. K.; Landmark, J. D.; Stickle, D. F. J. Chem Educ. 2006, 83, 644-646.

Mathews, K. R.; Landmark, J. D.; Stickle, D. F. J. Chem Educ. 2004, 81, 702–704.

Spectroscopy in a Suitcase: Teachers’ resource, Royal Society of Chemistry, 2009, 1-36, available from http://www.rsc.org/images/Teacher%20resource%20pack_ENGLISH_tcm18-204373.pdf.

AUTHORSChris Marks has worked as a chemist and materials scientist in industry and academia. He has taught chemistry at a high school and at a community college. He attended the First Winter School on Chemometrics to receive some formal training in multivariate methods and to visit Russia, a country which has long intrigued him. He is pleased to have attended all subsequent WSC conferences and proud to have adopted his daughter, Alyona, from Russia in 2004. His interest in bringing quality science to students using materials and methods familiar to them has led to the present collaboration. He is the uncle of his coauthor.

RESULTS AND DISCUSSIONFood Coloring CalibrationsLinear Beer's law plots were obtained for yellow and green food colors up to 20 concentration units and up to 50 units for the blue color. Fifty units is pure stock solution, so no higher concentrations were available for this data set. Calibration curves were fit using the LINEST spreadsheet function. Higher noise was observed on the red channel than with the green or blue channels. This especially affected the precision of the blue food color measurements, as seen in the mixture results.

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1.8Blue Food Coloring and Beer's Law

Concentration (arb. units)

Ab

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Kroger Soybean

Rozzano EVOO

Gem EVOO

GV Extra Light Olive Oil

GV EVOO

CriscoEVOO

Filippo Berio EVOO

CWP Soybean

CWP Corn

CWP Canola

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Vegetable Oil Spectra

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Bleach Kinetics

SiaS Data

Slope = 0.0144, Rsq = 0.997

Our Data

Slope = 0.0112, Rsq = 0.976

Bleach Concentration (arb. units)

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Ammonia Concentration (arb. units)

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FUTURE WORKIn Progress

Red food colorTernary mixtures of food colorsStandard additions with food colorspKa of red cabbage anthocyanins and pH measurementBleaching with other colors and oxidants

Planned ProjectsTurbidity measurementContinuous source and grating (CD or DVD) modifications to spectrometerVideo, web, and other cameras for live measurement or bit depth improvementEffect of TIFF or other uncompressed image formatsMultivariate calibration and classificationAnalysis of Mtn Dew and other soft drinksStudy of the starch, iodine, vitamin C system

CONCLUSIONSJim's PerspectiveI have had a great experience working on this spectroscopy project. These experiments are great since we utilized materials that I am familiar with. I learned a lot about the science to back up our results. I have learned about Beer’s law and the solution properties that have to be met. I’ve enjoyed helping in the preparation of the different solutions for our different experiments, especially the bleaching.

Some of the math required to make sense of our data was difficult for me to understand. I have not covered much of this math yet in school, and so when we first went over the matrix and vectors I was utterly confused. Now it seems to make a little more sense, but I am still a novice.

The mixtures gave us problems, e.g., the green was made up of blue and a different yellow than the one that they gave us. Therefore, we were unsuccessful when trying to replicate the green food coloring by making a mixture of yellow and blue food colorings. We believe that we must add a small amount of red dye to the green since some red dye is already present in the yellow food coloring. We are investigating this hypothesis by standard additions.

In the future I hope to analyze some soft drinks, but we will have to get past the problems of carbonation and turbidity, which will violate some of the Beer’s law assumptions. Standard additions may also provide a way around these problems.

All-in-all I have had a blast working on this project.

Chris's PerspectiveWe have successfully built a basic spectrometer from common materials which are familiar to most secondary students. Some of the materials were already on hand or were donated to the project. However, even if starting from scratch, suitable materials (excluding the computer) can be purchased for less than $100.

Students' familiarity with the components leads to simple and easy operation. This allows more time and energy to be spent on the science, even more advanced topics.

As impressive as the Biochrom, Ocean Optics, or other lower cost spectrometers are, their small, solid-state designs are a disadvantage in at least one respect. The components, particularly the source and detector, are difficult or impossible to view and understand individually. Students may regard such black boxes as magic, without ever really trying to understand their function or operation. Our system allows each component to be easily considered on its own and for evaluation of which properties are necessary for its purpose. The lower precision of our instrument also facilitates discussion of relevant statistical concepts.

Although we have just scratched the surface, we have shown that our approach is suitable for a variety of methods. Future work will involve expanding our toolbox and investigating more scientific questions than the demonstration projects shown here.

Red Cabbage IndicatorSmall cuvettes were prepared by first adding 1 ml of the indicator, followed by water, and ammonia or vinegar, to a total volume of 11 ml per cuvette. Very small volumes of acid or base were added with the eye dropper, assuming approximately 30 drops per ml. Solutions were mixed by placing a gloved finger over the opening and lightly shaking. The water-indicator solution was light pink. Additions of base changed the color to blue, then green, and finally to yellow. Additions of acid deepened the pink color until it turned red. Work is continuing to convert these absorbance measurements to pH.

Vegetable Oil ClassificationApproximately 50 ml of each vegetable oil was added to a large sample cuvette, and CVS pharmacy Mineral Oil USP was used as the blank. Extra virgin olive oils (EVOO) were easily distinguished from the others by their blue channel absorbance. Other oils were not distinguishable with the current three channel limitation. Multichannel measurements are planned.

Alyona, a sixth grade student at Tuckahoe Middle School, prepared the solutions and took the pictures for this portion of the work. Above she is shown analyzing the basic solutions. Alyona said, “It was interesting how things mixed together. It was fun, but also a little bit stinky.”

Several blue-yellow mixtures were made, and a model,

Concentrations = Absorbances * B

was created using these in addition to the pure component data. The regression parameters, B, were estimated using Octave. The leave-one-out test set errors (RMS) were about 1 unit for the blue color and about 0.5 units for the yellow color. The validation set errors are consistent with these results.

Bleaching KineticsOur procedure was adapted from materials for the Royal Society of Chemistry's Spectroscopy in a Suitcase (SiaS). We doubled the volumes to adequately fill our small cuvettes. A picture was taken as the bleach was added to record the camera time at t = 0 s. Solutions were mixed by placing a gloved finger over the cuvette opening and inverting a couple of times after the bleach addition. The cuvettes were then quickly moved into the spectrometer and pictures were taken at varying intervals depending on the speed of the reaction. The timestamps from the picture metadata were used to construct the kinetic plots. Only the red channel absorbance data was analyzed based on the earlier Beer's law results for the blue food coloring. Some photos could not be used because insufficient time was allowed for automatic exposure metering prior to photo acquisition. This resulted in overexposed or saturated photos and no way to determine I

blank. The “hole” at about 40 seconds in our data is due to this

error.

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ate r

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Circles - LOO TestStars - Validation

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The kinetics with respect to the dye and to the bleach are both first order giving an overall second order reaction rate. While our data is clearly less precise than the SiaS sample data, it is also clearly more than sufficient for teaching purposes. In fact, our bleach kinetics data is remarkably similar to the SaiS data given the differences in materials and equipment. The SiaS results were obtained with a Biochrom WPA Lightwave II UVVis Spectrophotometer costing nearly $5000.

0 50 100 150 2000

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Food Color6 ml Dye; 2 ml Bleach; 1 ml Water

Our DataSaiS Group 3 Data

Seconds

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a nce

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0Dye Kinetics

Our Datak = -slope = 0.02684 per sSaiS Group 3 Datak = -slope = 0.01498 per s

Seconds

ln(A

bso

rban

ce)

All data, notes, and initial calculations were recorded in a shared Google Docs Collection to facilitate access and collaboration. LibreOffice Calc and Impress were used when Google Docs was not adequate. All matrix calculations were handled with GNU Octave 3.2.3.

Jim Quagliano is a ninth grade student at St. Christopher’s School. His favorite science is biology, and he is currently in the honors class. He is also taking Algebra II. He plays the electric guitar and loves classic rock. Jim enjoys editing home videos with friends. He also plays Call of Duty: Modern Warfare 3 and NBA 2K games. He participates in baseball, basketball, and rock climbing. He is the nephew of his coauthor.

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