Introduction: (Initial Observation)
Crystallization is the final step in production of many chemicals. So it is important to make more crystals, larger crystals, in the least possible time. Larger crystals also indicate the purity and quality of many products.
Manufacturers and scientists perform many different experiments in order to identify the best conditions to grow crystals.
Such experiments is being repeated for different chemicals as well as different mixtures of chemicals. Obviously every chemical requires a different set of conditions to grow large crystals in a short period of time.
Some of the crystals that may be available to you for crystallization experiments are: Copper Sulfate, Aluminum Sulfate, Iron Sulfate, Sodium Chloride (table salt), Sucrose (table sugar), Boric Acid.
Factors that may affect crystallization and are normally being tested are strength or concentration of the solution, temperature of the solution, pH of the solution, presence of electrical field, presence of certain impurities.
Please note that you will investigate only one factor for your project. If you want to investigate on more than one factor, you must do it in a separate project or separate set of experiments. So the title of your project may change based on the factor that you choose to investigate. For example your project title may be:
The effect of solution concentration
on the rate of crystallization of copper sulfate
Note: Sugar and salt crystals are quite hard to grow – sugar because its very soluble , salt because the solubility curve is quite flat. If you want to grow things quickly try dissolving a lot of alum in hot water , getting it saturated and then growing onto a seed crystal , only putting it in the fridge – you’ll get a massive lump in a few hours.
This also works well with washing soda – sodium carbonate.
Find out about what you want to investigate. Read books, magazines or ask professionals who might know in order to learn about the effect or area of study. Keep track of where you got your information from.
For the purpose of crystallization research, you need to have information about the solubility curve of the substance that you are investigating. Solubility information can be found on the Internet or you may need to perform some initial experiments and record the solubility of the substance at different temperatures.
If you search for “copper sulfate solubility” or “copper sulfate solubility graph“, you will find the following information:
Copper (II) sulfate solubility in water
|water temperature (degrees C)||mass solute dissolved (grams)|
The above table and graph shows that the solubility of copper sulfate increases by increase of temperature and maximum solubility of copper sulfate is about 114 grams per liter. We will use these information in designing our experiment.
What do you want to find out? Write a statement that describes what you want to do. Use your observations and questions to write the statement.
The purpose of this investigation is to determine the effect of concentration of copper sulfate solution on the rate of crystallization.
When you think you know what variables may be involved, think about ways to change one at a time. If you change more than one at a time, you will not know what variable is causing your observation. Sometimes variables are linked and work together to cause something. At first, try to choose variables that you think act independently of each other.
Independent variable for our experiment is the strength or concentration of copper sulfate.
Dependent variable is the rate of crystallization in a certain period of time.
Controlled variable is the temperature.
Constants are the size of containers and the volume of solutions.
Based on your gathered information, make an educated guess about what types of things affect the system you are working with. Identifying variables is necessary before you can make a hypothesis.
I think higher concentration of copper sulfate will yields a higher rate of crystallization.
Design an experiment to test each hypothesis. Make a step-by-step list of what you will do to answer each question. This list is called an experimental procedure. For an experiment to give answers you can trust, it must have a “control.” A control is an additional experimental trial or run. It is a separate experiment, done exactly like the others. The only difference is that no experimental variables are changed. A control is a neutral “reference point” for comparison that allows you to see what changing a variable does by comparing it to not changing anything. Dependable controls are sometimes very hard to develop. They can be the hardest part of a project. Without a control you cannot be sure that changing the variable causes your observations. A series of experiments that includes a control is called a “controlled experiment.”
In this experiment we crystallize different solutions of copper sulfate with different concentrations to see which concentration yields a better result.
- Get five one-liter glass* beakers
- Weight and add dry anhydrous copper sulfate to each beaker. The amounts will be 110 grams, 100 grams, 90 grams, 80 grams and 70 grams. Note that dry anhydrous copper sulfate is almost white powder. Blue crystals have five water molecules. If you are using blue crystals you need to multiply the above numbers by 1.56. (Why?: Each 240 grams of copper sulfate blue crystals contains 90 grams of water and 160 grams of copper sulfate. You can calculate it yourself. Formula of copper sulfate crystals is CuSO4, 5H2O)
- Label each beaker with the amount of copper sulfate in that beaker
- Add water to the beakers to the level of 1 liter
- Heat up all beakers to the same temperature and stir until all copper sulfates are dissolved.
- Leave all beakers in a cold room for crystallization
- After 7 days, remove the crystals of each beaker and weight them.
- Record the results in a table
- Divide the weight of crystals in each beaker by 7 (days) to calculate the daily rate of crystalization.
* If you don’t have glass beakers, make the solutions in aluminum or steel pots. Then transfer them to plastic containers for crystallization.
Materials and Equipment:
Following is a list of material that you need. They often can be substituted by other material or equipment.
- 1Kg of copper sulfate crystals or 500 grams of anhydrous copper sulfate
- Electric heater
- 5 one liter Glass beakers or similar plastic container
- One thermometer
Copper sulfate can be purchased from hardware stores as well as pool suppliers. Make sure that you buy pure copper sulfate, not those that are mixed with other chemicals to be used as pesticides.
Results of Experiment (Observation):
Experiments are often done in series. A series of experiments can be done by changing one variable a different amount each time. A series of experiments is made up of separate experimental “runs.” During each run you make a measurement of how much the variable affected the system under study. For each run, a different amount of change in the variable is used. This produces a different amount of response in the system. You measure this response, or record data, in a table for this purpose. This is considered “raw data” since it has not been processed or interpreted yet. When raw data gets processed mathematically, for example, it becomes results.
The results table will look like the following:
Copper sulfate crystallization rate for different solution concentrations.
|Beaker 1||Beaker 2||Beaker 3||Beaker 4||Beaker 5|
|Concentration||110 g/L||100 g/L||90 g/L||80 g/L||70 g/L|
|or CuSO4 + 5H2O||172g||156g||140g||125g||109g|
|Total solution volume||1 liter||1 liter||1 liter||1 liter||1 liter|
|Rate of crystal production|
The only calculation that we do in this project is to calculate how much copper sulfate crystals we should use to be equivalent to the amounts of anhydrous copper sulfate that we want to use.
Summary of Results:
Summarize what happened. This can be in the form of a table of processed numerical data, or graphs. It could also be a written statement of what occurred during experiments.
It is from calculations using recorded data that tables and graphs are made. Studying tables and graphs, we can see trends that tell us how different variables cause our observations. Based on these trends, we can draw conclusions about the system under study. These conclusions help us confirm or deny our original hypothesis. Often, mathematical equations can be made from graphs. These equations allow us to predict how a change will affect the system without the need to do additional experiments. Advanced levels of experimental science rely heavily on graphical and mathematical analysis of data. At this level, science becomes even more interesting and powerful.
Using the trends in your experimental data and your experimental observations, try to answer your original questions. Is your hypothesis correct? Now is the time to pull together what happened, and assess the experiments you did.
Related Questions & Answers:
What you have learned may allow you to answer other questions. Many questions are related. Several new questions may have occurred to you while doing experiments. You may now be able to understand or verify things that you discovered when gathering information for the project. Questions lead to more questions, which lead to additional hypothesis that need to be tested.
If you did not observe anything different than what happened with your control, the variable you changed may not affect the system you are investigating. If you did not observe a consistent, reproducible trend in your series of experimental runs there may be experimental errors affecting your results. The first thing to check is how you are making your measurements. Is the measurement method questionable or unreliable? Maybe you are reading a scale incorrectly, or maybe the measuring instrument is working erratically.
If you determine that experimental errors are influencing your results, carefully rethink the design of your experiments. Review each step of the procedure to find sources of potential errors. If possible, have a scientist review the procedure with you. Sometimes the designer of an experiment can miss the obvious.