Independent Variable
, , ,
Dependent Variable
,
Controlled Variables
, ,
Hypothesis
By varying the independent variables, we can get different values of , and thus produce varying but similar values for . Then by taking the mean value of all trials, we can obtain an experimental value of . This value can then be matched with the density to published values to conclude the material.
Method
List of Materials
→Electronic balance, thermometer, graduated cylinder
→Tin foil, bubble wrap, styrofoam insolation
→Electric kettle
→2 Calorimeters
→Enough water to immerse the unknown material compeletly
→Unknown Material
Diagram of Apparatus
Measuring the Variables
The independent variables, masses, will be measured by electronic balance. The temperatures will be monitored by a thermometer.
The dependent variable, the final temperature will be measured by thermometer after thermal equilibrium is reached.
Controlling Variables
Masses and Specific Heat Capacities will be controlled by using the same materials. will be monitored in a insolated Styrofoam cup until desired temperature is reached.
Collecting Data
Procedure
1) Setup data table for finding . Hang unknown material in the Styrofoam calorimeter so it doesn’t touch the walls. Measure mass of unknown material.
2) Start boiling water. Better insolate the calorimeters with tin foil and bubble wrap.
3) Measure mass of water, empty calorimeter and unknown material and record.
4) Fill calorimeter with cold water, measure temperature after equilibrium.
5) Pour hot water into second insolated cup, and monitor until a desired temperature.
6) Pour the hot water into first calorimeter and seal opening with another Styrofoam cup.
7) Stir the water mixture slowly and measure final temperature at equilibrium.
8) Pour out water, cool down calorimeter, material and thermometer and reset.
9) Repeat 4) – 8) for 5 trials. Record all relevant data.
10) Setup data table for finding . Repeat 4) – 8) without the unknown material in the calorimeter 3 times to determine the heat capacity of the calorimeter.
11) After finishing with calorimeter, cool down unknown material to room temperature.
12) Measure volume using water displacement; immerse unknown material in a half-filled graduated cylinder and reading how much water is displaced by the addition of the material.
13) Repeat steps 12) 5 times.
14) Clean up.
Results
Raw Data Table formeasurements
Raw Data Table formeasurements
Raw Data Table for Volume measurements
Mass of unknown material: .
Processed Data
Calculation:
Calculation:
Density Calculations:
, , ,
Conclusion
Based on the specific heat capacity obtained , the most likely material, given that it is a solid, shiny metallic material, is iron with a C of . (Source: Wikipedia, 2009) This value is within the uncertainty trials, this gives a percent error of only 13% higher than published value. Confirmation with density also point to iron, which has a density of (Source: Wikipedia, 2009), which fall within experimental uncertainties and produces 5% above published value. Another major part of identifying the unknown material is the fact that rust resulted after the first few days of the lab. This further confirms that it is iron. The difference in specific heat capacity can be attributed to experimental errors and inherent impurities in the material.
Errors
The largest error is the temperature measurement, contributing more than error in some cases on its own. This is due to parallax reading errors and difficulty to determine when equilibrium has occurred. The effect of slight temperature differences (0.1) often resulted in C differences of 100. Also, due to the high temperature difference between the hot water and environment, heat loss occurred despite attempts for insulation. The formation of rust also affected final result since iron oxide has a different specific heat capacity.
Evaluation
The first design for this lab used an immersion heater and monitoring the power usage with an ammeter and voltmeter. This design involved using the relation,
,
And then graphing vs. to obtain as part of the slope. However, due to the inefficiencies of the immersion heater and the complexity of timing and monitoring temperature and recording data all at the same time, the results ranged from -10 to over 10000. Thus, all the procedures must be changed to using the hot water method currently outlined.
Improvement
Further improvements include using better insulation, to reduce heat loss; this also provides more time to wait for thermal equilibrium to take temperature measurements. Also, by reducing the hot water temperature, the effect of conduction and convection would be reduced. A digital thermometer will greatly improve the errors in temperature measurements as it avoids reading error and great uncertainties. By sanding off the rust flakes that form on the surface, we can also reduce the effect of having impurities in the metal.
