Instructional Activities:

This lesson serves as the conceptual underpinning for understanding how light behavior can be used to measure concentrations with a spectrophotometer. Students should frame their observations around “particles" of light interacting with material in three observable ways: that light can pass through, bounce off, or be taken in by materials. Light from an incandescent bulb shown through a Lucite box with increasing amounts of milk fat can be seen to cause transmission, scattering, and absorption respectively. The behavior of differing wavelengths of light can explain the red and blue shift observable on the long and short sides of the box at higher concentration-similar to sunsets reds or deep sea underwater blues. The introduction to the activity can be modified based on students previous experience with the nature of light. The 'engage' and 'explore' activities (below) assumed no previous background.

Materials list (for demonstration):

• 2% Milk
• Stir Rod of any type
• Plastic box or glass tank
• Graduated Beral pipet (eye dropper)
• light source (incandescent bulb, laser pointer, flashlight masked to make a beam)

1. ENGAGE

Questions to pose to students: How does light behave? We see objects in our surroundings because of some interaction with light. What are the plausible interactions when light interacts?
Student response: … Surfacing that the light can bounce off the object, it might pass through the object, not all the light goes through …

Push for several examples of each.
What happens to the light not going through?

Surfacing it may be scattered or absorbed …

Push for several examples of each.

Introduction of vocabulary: Reflection, Transmission, Scatter, Absorption
(Detail here guided by teacher need)

2. EXPLORE

A classwide discussion using the a glass or Lucite tank filled with water set up as a demo. An incandescent light source should be on one side, a paper “screen" on the other.

• Let’s consider the case of light entering water: Here is a container of water. What seems to be the case for this interaction between the light and the water?
  … Transmission What evidence do you have for this interaction?
  …we can see light reaching the far end of the box if we hold up a "screen" of paper on that end
  What could be changed to affect this interaction?
  Add something to the water; make the pathway longer …
• At this point, the classwide conversation can continue as the teacher adds droplets of milk .

  Describe the impact of adding more “stuff" (milk") to the light reaching the other side.
  --more milk, less light passing through, more light observed from sides of container, color of light at sides bluish, light at end ‘shifting’ redish

  What factors determine the amount of light passing through the box?
  --length of path, # of particles, size of particles

  If we consider the light source as the 100% amount, the light passing through to the other end is the % transmitted. What happens to the rest of the light?
  --It is scattered.
  How do you know that?
  --We see the light from the sides of the container.
  So the transmitted light and the scattered light should be equal to the light energy from the source?
  ………. Not necessarily, some light might be absorbed.

  What is some way that we might measure the light energy?
  …. solar cell responds to light intensity; if we measure output we could translate output energy to light intensity

3. EXPLAIN (PowerPoint)

Lead students through the explanatory powerpoint for Beers Law found here.The powerpoint on light and milkfat interaction (slide 2) introduces Beers Law (slides 3 & 7) and describes the two types of interactions causing notable decreases in transmitted light intensity. The first is absorption such as that seen in sea water (slides 4-6) and the second is the scattering responsible for blue skies and red sunsets (slides 8-12). The distribution of fairly regularly sized milk fat globules responsible for the scattering of light observed by the students is described (slides 13-15). Milk fat globules are similarly sized to typical microbes, making them a good substitute to study how they scatter light. The final slide (16) introduces the idea of using the transmitted light as a proxy variable to detect changes in concentration.

**Teacher Background note. In research, it is common to choose the wavelength on the spectrophotometer to ensure that deceases in light transmission are caused by scattering phenomena rather than absorption since some microbes express colored pigments differently depending on environmental conditions.

4. ELABORATE

In the next lesson, students will use milk fat concentration data to create a calibration curve.

Instructional Activities:

This lesson introduces students to making quantitative inferences from proxy variables via calibration. The concepts of standards, calibration curves, and offsets are introduced through a familiar device, the spring scale. Students then develop a calibration process using light properties. Using varying milk fat concentrations, the class will use a photoresistor apparatus to make a standard (calibration) curve which is then used to identify an unknown sample.  (This is how population density will be determined in lesson 6.)

Introduction (PowerPoint)

The guiding question for this lesson is: How could we use the observed light properties to create an accurate measuring device? (slide 2)

1. Calibration & Accuracy for A Spring Scale (PowerPoint)

• How do we know our measuring devices are accurate? (slides 3-11)
  “How do we know our spring scales are accurate?" What does it mean for the scale to be accurate? Student answers may lead to comparison to a standard (the SI kilogram). In order to be sure the instrument is accurate, it must:
  • read zero (a “blank", tare) as an offset.
  • have a set reading matching a standard (a fixed benchmark)
  • demonstrate a predictable pattern in between and beyond the standard benchmark (often linear) so that other benchmarks can be included.
• How can we use a calibration curve? (slide 12)
  If the measuring device demonstrates a predictable pattern, we can develop a mathematical relationship between the observed proxy variable and the standard to which we are inferring a relationship. This “curve" can be used to determine unknown samples by measuring the proxy variables.  *Point out the term 'curve' may refer to a straight line.

2. Can we create a calibration curve using our observed properties of light? 

• What is needed to generate a calibration curve? (slide 13) Students should brainstorm in groups what would be needed to generate an accurate calibration curve for a photoresistor apparatus they will build. As their answers are discussed, a point by point comparison to the spring scale example could lead them to the realization that they need:
  • to determine the offset or “blank" value (a reading of the tank with the solvent—in our case water)
  • a standard for comparison (an accepted value for milk fat concentration that will be provided to them)
  • a predictable pattern between the milk concentration and the reading from the photoresistor
• What is a standard for milk? A blank? (slides 14-16) Homogenization of milk results in relatively similarly sized milk fat globules dispersed throughout the milk. Using manufactured 2% milk, we can assume the density of milk fat globules can be used as a standard. These globules are similar in size to most microbes, making them convenient as a standard. Students should be made aware that an offset condition, the “blank", should be determined for the solvent devoid of milk fat globules—water.
• How would we create a calibration curve? (slide 17-18) From the properties of light activity, students should be able to predict that the light intensity reaching the photoresistor decreases when the milk fat density increases. They can be prompted to list the quantity actually being measured and what it is being inferred to represent (ie measure voltage, infer light intensity or measure drops or volume of milk and infer population density) to lead them to what quantitative values should actually be on the graph.
• How will the calibration curve compare for similar devices? (slides 19-21) Students will be comparing their data to others in class. Error bars on their curve will indicate how well the devices are working.  Discussion of various instruments (such as Vernier probes) available would be helpful.

3. Building and Calibrating the Devices (Student Activity)

• Materials list per group:
• 5 ml of 2% milk
• water
• graduated Beral pipet (dropper, or micropipetor)
• 5-8 test tubes of the same size
• test tube rack
• 9v battery
• wire or alligator clips (see powerpoint directions)
• photo-resistor
• resistor (100-300 ohm)
• multimeter
• tape (electrical, masking)
• LED (light emitting diode)

Before beginning, have students decide on how they will make dilutions and show them how to build the photoresistor (ppt. or demonstrate).

• Recording the Data:  Students should graph their data in excel or LoggerPro to generate calibration curves.  Have students add error bars.  Sample Graphs for some differing devices can be found here Milk Fat Sample Calibration Data.
• Teacher directions for graphing in Excel, with error bars.  For students who have not worked with error bars, this worksheet leads them to assess their importance and give them practice with sample data.
• Determining an Unknown:  Once students have completed their calibration curves with error bars inserted to indicate an appropriate level of uncertainty, each group should be given the same unknown concentration to measure falling within the 0 to 10⁷ globs/L range that they have measured. An intermediate value, such as 250 uL of milk added to a liter of water, should be used. The milk fat concentration should be identified using their calibration curves. The class should share their results so students can evaluate their findings. The final instrumentation focused assessment for the students is the individual written report on the determination of the unknown concentration using this student assignment Identifying an Unknown.