Class Set: Please do not write on this sheet

Unit 3: Atoms Beanium Laboratory Purpose-  To analyze the isotopes of Beanium and calculate its atomic mass.

Materials-  Sample of Beanium  Balance  Pencil  Paper

Procedure- 1. Make a table similar to Figure A to record your data, and record your calculated values 2. Obtain a sample of Beanium. 3. Separate the three isotopes (black, white, red) and measure the mass of each isotope. 4. Count the numbers of black, white and red beans 5. Repeat steps 2-4 one more time.

Black White Red Totals Total Mass (Grams) Number Average Mass (Grams) Percent Abundance Relative Abundance Relative Mass

Figure A Calculations- (All Calculations must be shown to receive full credit for the laboratory) 1. Calculate the average mass of each isotope by dividing its total mass by the number of particles in the isotope. 2. Calculate the percent abundance of each isotope by dividing its number of particles by the total number of particles and multiplying by 100. 3. Calculate the relative abundance of each isotope by dividing the percent abundance from step two by 100 4. Calculate the relative mass of each isotope by multiplying its relative abundance from step three by its average mass. 5. Calculate the average mass of all Beanium particles by adding the relative masses. The average mass is the atomic mass of Beanium. Class Set: Please do not write on this sheet

Analysis-

1. Explain the difference between percent abundance and relative abundance. What is the result when you total the individual percent abundances? The individual relative abundances? 2. The percent abundance of each kind of bean tells you how many of each kind of bean there are in every 100 particles. What does relative abundance tell you? 3. Compare the total values for row three and row six in the table. Why can’t the atomic mass of row six be calculated the way the total for row three is calculated? 4. Explain any differences between the atomic mass of your Beanium sample and that of your neighbor. Explain why differences would be smaller if larger samples were used.