Pressure in the Diet CokeTM & MentosTM Reaction

Objective

Perform a series of experiments on the reaction between Diet CokeTM and MentosTM candies. Use the data to estimate what the pressure would be inside a sealed 2 L bottle of Diet Coke with 5 Mentos mints.

Plan

Your plan should include the following information, but in your own words.

1. Make a Diet Coke & Mentos fountain.
2. Set off your fountain & measure the height of the spray.
3. Repeat with caps that have different size holes.

Procedure

Write out your detailed procedure. Be sure to descrbe how you made the fountain (include a labeled diagram, the size of the bottle of Diet Coke, number of Mentos and how you attached them together, etc.):

and how you measured the height of the spray, using a ruler as a scale hypsometer.

(In the above example, the height of the spray would be 4.5m.)

Data & Observations

Here are data for each of the honors Physics classes:

 Block Diameter of hole(mm) Dist. to 2m mark(cm) Height of 2m mark(m) Dist. to top of spray(cm) Height of spray(m) Pressure(Pa) A 4.0 11.5 2.0 40.0 A 4.8 9.0 2.0 34.0 A 4.8 11.5 2.0 39.0 A 5.6 12.0 2.0 36.0 E 4.0 OOPS 2.0 39.0 E 4.0 14.0 2.0 42.0 E 4.8 8.0 2.0 28.0 E 4.8 12.0 2.0 32.0 E 5.6 11.5 2.0 37.5 E 5.6 13.5 2.0 42.0

Analysis

Calculate the pressure in each bottle using the equation P = Ïgh, with Ï = 998 kg/m3, g = 9.8 m/s2, and h as calculated from your measurements. Use the data from your class. If you choose to leave out one or more data points, be sure to include an explanation!

Plot a graph of pressure vs. diameter of the opening. Draw a best-fit line and extrapolate to an opening of 0 mm to find the pressure that would be present in a bottle with no opening.

An example graph with sample data is shown below:

Because you are calculating the pressure with no opening as the y-intercept of your best-fit line, you must either:
• Calculate the y-intercept graphically, plotting your data points accurately on graph paper and drawing the best-fit line with a straightedge.
• Calculate the best-fit line and y-intercept statistically, using linear regression. If you do this, be sure to provide the slope, intercept, and correlation coÃ«fficient.
Remember to include possible sources of uncertainty/error.