Author Archives: juriley

Group 9: Results and Conclusions

The bar chart below displays the adjusted opacity values of our samples.  The longer the bar, the more transparent the liquid, and hence, the lower the opacity.

Adjusted Opacity Values

We expected our opacity readings to be strongly correlated with our spectroscopic data, but this was not always the case.  For example, Axe Shower Gel had a high opacity (low lux reading) and had full absorbance (to the limit of the spectrometer) across the visible spectrum.

axe shower gel graph

Coffee, on the other hand, was the most opaque sample we measured, but only displayed full absorbance from 400-580 nm.  We did not expect this result, and are not sure why this is the case.  Maybe because the light which is absorbed is all higher energy wavelengths?

coffee graph

The most transparent liquids all had very low absorbances across the spectrum, which is what we expected.  Locations of minor spikes in absorbance varied, but this did not affect opacity because the lux readings covered the entire visible spectrum.

Many of the liquids were colored, and these colors were based on their absorbance patterns.  Coffee, for example, absorbs everything up to  580 nm, and then trails off, which means it reflects light in the red to orange area of the spectrum, giving it its brown color.

We also diluted coffee with unknown pineapple juice (what pineapple juice does the Deece use?) and found that the mixture had some yellow and green absorbance readings as well.  The problem is that since we don’t have the spectrum of pineapple juice, we can’t determine whether the yellows and greens are due to the pineapple juice’s absorbance wavelengths, or simply through the dilution of coffee.

coffee and unknown pineapple juice graph

Orange juice absorbs everything in the visible spectrum except the wavelengths from 640 to 700 nm.  From 640 to 700 nm the absorbance varies, but it is never completely saturated.  Thus its orange color.

orange juice

The spectroscopic readings for Axe Shower Gel were fully saturated, but when we mixed it with the almost completely transparent listerine, we wound up with an interesting spectrum.  Since the two substances did not react chemically, the spectrum produced is most likely a reflection of the spectrum of Axe Shower Gel.

listerine and axe shower gel

This project gave us a better grasp of the principles of atomic spectroscopy.  At the risk of over-simplifying, a spectroscope shines light through the sample, and then measures how much is absorbed at each wavelength.  Since each element only absorbs certain wavelengths, the spectrographic measurement of a substance is akin to a fingerprint, although it requires a trained spectroscopist to analyze it accurately.  We utilized the spectroscope to examine the absorbance properties of our samples, and compared that to the overall opacity of the samples.

If we had this project to do over, we would make a few corrections to our approach.  We would record the concentrations of each liquid in our mixtures, and vary the concentrations to examine the difference in absorbance.  We would handle the cuvettes with more care, because fingerprints on the cuvettes could subtly alter the spectroscopic readings.

If we had another six weeks, we would dilute all of our fully absorbent liquids with water (since water would not cause much interference, as a relatively clear, non reactive, liquid) so we could measure their absorbances.  We really liked the idea of analyzing the composition of sunset lake.  We would like to suggest hiring a trained spectroscopist to work with us to help us interpret the spectroscopic readings.  😉

Group 9 Data (Spectroscopic and Light Sensor)

We gathered samples of multiple liquids, including mixtures of a few of them, and analyzed them using two separate instruments; a light sensor, and a portable spectrometer.

To begin with, we shined light through our samples and measured their opacities using the light sensor.  We took the data in a dark room, holding the samples against the light sensor and exposing it to only one source of light at a constant distance and intensity.  We used a cell phone flashlight.  This is a picture of our experimental setup.

setup 1

The light sensor we used had a slight systematic error of about 2.4 lux, that is, it measured 2.4 lux when completely covered.  We have adjusted for that in the table below.

Liquid Adjusted Opacity Values (Lux)
Water 67
Orange Juice 3.6
Extra Virgin Olive Oil 50
Listerine 63.6
Axe Shower Gel 1.3
Hand Sanitizer 66.8
Sprite 69
Coffee 0.4
Coffee plus Unknown Pineapple Juice 8.9
Shower Gel plus Listerine 19.6
Fireball Cinnamon Whiskey 59
Everclear Grain Alcohol 68.6
Orange Juice plus Oil 5.3
Low Fat Soy Milk 1.1
Whiskey plus Low Fat Soy Milk 3.6
Water plus Low Fat Soy Milk 3.4

Our second set of data was attained by analyzing our samples through a portable spectrometer.  It also had a small systematic error, which we have accounted for.  The absorption readings were displaced on the y-axis by about 0.5, giving negative absorption readings.  In our graphs, we have displayed the y-axis from -0.5 to 3, which should be read as 0-3.  3 is the maximum opacity that this spectrometer can measure.  The y-axis records absorbance, while the x-axis displays wavelength.  The picture below is of our setup, showing the spectrometer and all the liquid samples we used.

setup 2

The spectrometer shines light through the samples, and records the absorbance on the wavelengths of the visible spectrum.  Below are our graphs of the data.

axe shower gel graph Axe Shower Gel

coffee and unknown pineapple juice graph  Coffee and Unknown Pineapple Juice

coffee graph  Coffee

everclear grain alcohol graph  Everclear Grain Alcohol

extra virgin olive oil graph Extra Virgin Olive Oil

fireball cinnamon whiskey  Fireball Cinnamon Whiskey

fireball whiskey and soy milk graph Fireball Whiskey and Soy Milk

hand sanitizer graph Hand Sanitizer

listerine and axe shower gel Listerine and Axe Shower Gel

listerine graph Listerine

low fat soy milk graph Low Fat Soy Milk

orange juice  Orange Juice

orange juice and oil graph Orange Juice and Oil

soy milk and water graph Soy Milk and Water

sprite Sprite

watergraph Water

 

Group 9 Project Plan: The Role of Contaminants in the Opacity of Liquids

     Our project involves the analysis of different liquids spectroscopically. We will also measure the opacity of the same liquids. We want to analyze which contaminants have a stronger impact on opacity. Can we tell the difference between liquids contaminated with different substances based on their opacity? The data obtained using a spectroscope will allow us to determine the compositions of different liquids. We would like to examine any correlations between the spectroscopic data and the opacity measurements we take for the same liquids.
     The equipment we hope to have access to is a spectrometer and any kind of light sensor such as the sensor drone. Spectroscopy works by analyzing the wavelengths of light that are either emitted or absorbed by a substance. Because each element possesses a unique pattern of wavelengths, we can determine the composition of different substances.
      We will be collecting any and all kinds of liquids that we have access to (coffee, juices, alcohol, sodas, etc.). We will certainly use different kinds of water (tap, mineral, distilled, sparkling, etc.) and also water that we contaminate with various substances (salt, fertilizer, spices, chemicals, etc.). In terms of supplies, we will need multiple containers to hold the liquids. The experiment will be done using only one transparent jar which will house the liquids so as to keep the effects of the jar constant. The sides of the jar will be covered in a way that no light escapes and we will create a setup allowing us to place the light sensor under the jar. A constant source of light such as one flashlight will shine at the top of the setup. The light sensor placed under the jar will be housed in a small cardboard box having a hole in it. This will ensure that no other light interferes with the sensor’s measurements.
     As far as roles are concerned, all 3 of us will collect as many different containers, liquids and contaminants as we have access to and we will all be present for the data collection. This is the most efficient way to go about our project because all our data can be collected in one place. We are meeting every Friday at 11 am to discuss the project and carry out any necessary research, data collection or other activities. We will set additional meeting times when necessary. We will also be doing every write-up (such as this one) together.
     All in all, we expect some correlation between contaminants and opacity. However, we are unsure of what to expect without analyzing the data.