In this lesson you will observe a gaseous phenomenon. You will then be asked to create a model of the phenomenon in order to explore different gas variables that give rise to that phenomenon.

Watch the video of the gaseous phenomenon and then read the information below that explains the events that led up to the incident.

On Thursday, April 4, 2019, a Burlington Northern train unloaded its cargo in Union Station’s railroad yard. As with all train cars after being unloaded, the local railroad crew was assigned the task of cleaning the interior of each car. Since the train cars were not unloaded until near the end of the evening working shift, the crew members were rushed to finish the job.

With cleaning equipment in hand, each worker steam cleaned the inside walls of each train car. Once completed, the tanker car was sealed. Since it was already 9 PM, each worker was eager to “clock out” and return home for the night. The tanker car sat sealed overnight.

When the Burlington Northern employees returned to work the next morning, all employees were required to gather, view, and record a video of a safety training procedure with the tanker. However, to the surprise of everyone, something dramatic happened and was captured on video. The video shows the very tanker that was cleaned and sealed the night before imploding before their eyes. The overwhelming question among the Burlington Northern employees is what had happened to the tanker?

How could a train car with a steel plate thickness of 1.11 cm suddenly collapse overnight? It is hard to imagine the forces it took to do this much damage, to such a large steel object. As a Chemistry Safety Engineer for Burlington Northern, your task will be to determine what happened on the morning of April 5, 2019 to the imploded tanker.

On the previous page you explained why you believe the gas tanker imploded; your answer is referenced below. Now each member of your group will share their explanations in order to come to a consensus as a group. Your group must agree on an explanation before proceeding to model creation below.

In order to create a model, the events from that night in April 2019 will be broken down to four distinct moments in time. The first moment is the gas tanker sitting open prior to cleaning. The second moment is during the steam cleaning, again with the lid still open. The third moment is after the steam cleaning with the lid closed while the tanker sits overnight; this actually spans the greatest amount of time as the tanker sitting all night needs to be considered here. The final moment is the gas tanker imploding with the lid still closed.

As most students surmised, pressure is involved in the implosion of the gas tanker. In this lesson, we will conduct a variety of hands-on investigations to explore the relationship between pressure and volume.

You will need the following resources to complete this assignment.

• Pressure-Volume Investigations

Typically in chemistry we cannot directly observe what is happening because it is occurring on a microscopic level. In order to better understand the cause of our macroscopic observations, we will need to examine microscopic particle behavior and create models to represent what we cannot see.

You will observe food coloring added to both hot and cold water.

In the question below you will be asked to make a prediction about the speed of the spread of the food coloring in both temperatures of water. 

Three trials of the experiment are shown below, view each one separately. You will be recording both qualitative and quantitative measurements for each trial below the videos.

Trial 1

Trial 2

Trial 3

In chemistry class, when we answer a question, we call that answer a "claim". You may have heard this term before, in relation to the explanation structure Claim-Evidence-Reasoning. A claim states the relationship between your independent variable and your dependent variable. You do not provide any data or explanation of why this relationship exists. 

Evidence is data that we gather in class, organized to support a claim. It is important that you realize that the data you record from an experiment in class is not automatically evidence. To produce evidence, you will pull two data points from your raw data to support the relationship stated in your claim. For a lab report, you will be required to compose evidence with multiple data point sets. Quantitative data is prioritized over qualitative data if available.

Reasoning is the explanation of why the data is appropriate (i.e., why is this data relevant?) and how the data support the claim. This is where you explain the science behind why your evidence supports your claim.

You already made a claim to answer the question: "In which temperature water did the food coloring spread faster?" on the previous page. It was clear in the experimental video that the food coloring spread faster in hot water. Below, you will be asked to support that claim with evidence and to explain why your evidence supports that claim with reasoning.

If we were to write a claim evidence reasoning statement to answer the question "In which temperature water did the food coloring spread faster?", it would look something like this: 

Claim: The food coloring spread faster in hot water than it did in cold water.

Evidence: In hot water, food coloring took X seconds to hit the walls of the container. In cold water, food coloring took X seconds to hit the walls of the container.

Reasoning: Hot particles move faster than cold particles. As temperature increases, so does the speed of particle movement.

The following image shows food coloring particles in hot water vs cold water, according to how we will model things in our class. Examine the model and answer the questions below.

In the last lesson, we made a claim about temperature and particle motion after observing that hot particles move faster than slower ones. In this lesson, we will begin to focus on gaseous particles by exploring the effect that temperature has on a volume of gas.

Watch both videos below and then answer the questions that follow.

The simulation below shows gas particles inside a container with a moveable lid.

Begin the simulation by hitting "setup" and then “go/stop”. Observe the gas particles as they move around the inside of the container. You have control over the temperature inside the container which can be adjusted by moving the slider bar labeled "gas-temperature".

As soon as you feel comfortable with the functionality of the simulation, move on to answer the questions below.

Now you will acquire data and create a graph using the same simulation integrated with an online data analysis platform called CODAP. Below, you will see a CODAP workbench. CODAP will allow us to visualize our data immediately upon entering it into the platform.

Let's begin with familiarizing ourselves with the CODAP environment:

1. The platform is below these instructions. Notice the starting volume at room temperature of 23°C has been entered for you.
2. Adjust the slider bar labeled "gas-temperature" to a temperature other than the starting temperature.
3. Begin the simulation by hitting "setup" and then “go/stop”.
4. Allow the simulation to run for 100 ticks before pressing the "record-data" button. Notice that your data will appear in both the data table as well as create a data point on the graph at right.
5. Record volume measurements at 3 additional temperatures (for a total of 4 temperatures as 23°C has been entered for you), waiting 100 ticks after changing the temperature to click "record-data" (one should be the minimum temperature and one should be the maximum temperature on the gas temperature slider bar).
6. Observe the resulting plot. Then answer the questions below the CODAP workbench.

You created a graph of volume versus temperature on the previous page. We are going to use that graph to determine the relationship between volume and temperature. First we will go over the different types of data relationships.

If you observe your independent variable increasing as your dependent variable increases (or if one variable decreases as the other decreases) your variables are said to have a direct relationship. A graph of two variables (A and B) with a direct relationship is shown below.

If you observe your independent variable increasing as your dependent variable decreases (or if the independent variable decreases as the dependent variable increases) your variables are said to have a inverse relationship. A graph of two variables (A and B) with an inverse relationship is shown below.

In lesson 2, we concluded that hot particles move faster than colder ones. We reviewed a model of that movement shown below:

This model shows faster moving particles drawn with longer arrows than those that are moving more slowly.

Use this same convention of shorter arrow = colder particles, and longer arrow = hotter particles to complete the model below.

So far in this unit, we have begun to establish basic relationships between gas variables, and we have also agreed on conventions to use for modeling gas particles. In this lesson, we will focus exclusively on gas particle behavior.

Kinetic molecular theory explains microscopic particle behavior based on the macroscopic properties of gases. The goal of this lesson is to understand how gas particles move, and how their microscopic movement is connected to the macroscopic observations of temperature and pressure.

You will explore gas particle motion using the simulation below.

• Select the "Ideal" option at left.
• Pump the pump once and observe the gas particles enter the box. Describe the movement of the particles below.
• Now choose an individual particle to focus on. Follow that particle's movements. Describe the movement of that single particle below.

Imagine you were the computer programmer that wrote the simulation. The programmer had to provide a set of rules for the movement of the gas particles that they obey in every possible circumstance within the simulation.

The simulation is again shown at right, click on "Ideal", then pump a single pump of gas and let the simulation run.

• Together with your lab table group, you will write out a set of rules that you believe gas particles are following in the simulation. Be as specific as possible and be prepared to share your rules with the class.

Now you will use your rules for particle movement  from page 2 (they are referenced on this page below) to help you program your own simulation using NetTango.

NetTango is a tool that uses a programming language called NetLogo in preprogrammed blocks. You will be asked to use these blocks to create a working model that best reflects the movement of gas particles you observed in the PhET simulation.

Watch the video that demonstrates how to use the blocks to program gas particle behavior at right.

Start programming!

A few quick points:

• Click  to reset the model and click  to run your model.
• Your code should always start with the  block, or the model will not know what to do.
• Your code will be performed by the particles continuously.
  • For example, if you wrote that "each particle + moves zig-zag", each particle in the model will move one step forward doing a zig-zag movement and then move one more step forward the same way, and so on. This will keep going on as long as the GO button is pressed.

Kinetic Molecular Theory is a set of rules used to describe gas particle movement. Scientists assume that all gas particles behave in this manner unless stated otherwise. These rules are as follows:

• Gas particles are in constant random motion.
• Gas particles are so small that they may be considered to have no volume relative to the empty space that surrounds them.
• Collisions with the walls of the container are perfectly elastic. An elastic collision is one in which there is no overall loss of kinetic energy. This means that gas particles do not lose kinetic energy after they collide with the walls of their container.
• Collisions between particles are also perfectly elastic. Kinetic energy may be transferred from one particle to another during an elastic collision, but there is no change in the total energy of the colliding particles.

You will model each of these rules in the questions below.

On the previous page, you were asked to model the rules of Kinetic Molecular Theory. Below are images showing how those models should appear. Your responses from the previous page are included here so you can compare and contrast them with the correct models.

Rule 1:

Rule 2:

Rule 3:

Rule 4:

Within this unit, we have examined several gas variables in relation to gas particle behavior including temperature, volume, and pressure. In this lesson, we will examine a fourth variable, number of particles.

We will specifically study the effect of two different variables on pressure; we will investigate how changing the number of particles affects pressure, and how changing volume affects pressure.

Feel free to play around with the simulation, but make sure to refresh your browser before working through the following steps in order to learn how to manipulate the simulation for this lesson. 

1. Click "Ideal"
2. Particles Menu
   • Click the green plus sign next to particles
   • To subtract or add 1 particle or 50, click the arrows to the left and right of the number of particles
3. Reset button
   • Click the white button to the left of the pump to reset the simulation. 
4. Particle Pump
   • After resetting the simulation, drag the handle of the pump up and down to add a more random number of particles. 
5. Pause button
   • After adding some particles to the chamber, click the pause button on the lower left side of the screen to pause the simulation.
6. Play simulation / one frame forward
   • After clicking pause, you'll notice that the pause button turns into a play button. Click the play button to restart the simulation.
   • Pressing pause also lights up the smaller button to the right of the pause button. This smaller button allows particles to shift one frame forward.

Let's look at a GIF of the simulation we just used so we can understand what causes pressure on a microscopic level.

The pressure gauge remains at 0.0 atm until the moment a particle collides with the wall of the container. The pressure gauge then reads a pressure, but goes down again until another particle collides with the wall.

Pressure can be defined as the frequency and force with which gas particles collide with the walls of their container.

Since we are examining pressure and number of particles in this simulation, we need to make sure that the other two variables (volume and temperature) are held constant. 

This is the set-up you will need to complete the data table below: 

1. Click "Ideal".
2. Under "Hold Constant", click "Volume (V)". The program does not allow you to hold two things constant at the same time, but as long as you do not manipulate the "hot-cold" switch the temperature will remain at 300 K.
3. Click the green plus sign next to particles.
4. Click the double rightward facing triangle below "Heavy" to add 50 heavy particles at once.
5. Wait until all particles from the pump have had a chance to hit a wall of the container, then record the highest pressure observed.
6. Press the reset button, then repeat steps #2-5 two more times.
7. Complete steps #2-6 for 100 heavy particles and 150 heavy particles.

If we graph the data we acquired on page 3 (your data is shown on this page for your reference), our graph would look something like this:

The graph pictured above shows a direct relationship between the two variables (number of gas particles and pressure), that is, as number of particles increases, pressure also increases.

Now we will examine how volume affects pressure. Again, we need to make sure that the other two variables (number of particles and temperature) are held constant. 

This is the set-up you will need to complete the data table below: 

1. Click "Ideal".
2. Click the green plus sign next to particles.
3. Click the double rightward facing triangle below "Heavy" to add 50 heavy particles at once.
4. Under "Hold Constant", click "Temperature (T)".
5. In order to adjust the container's volume, click "Width" and you will see a ruler appear under the container. Reduce the width to 5.0 nm, then record the highest pressure observed.
6. Press the reset button, then repeat steps #2-5 two more times.
7. Complete steps #2-6 for widths (volumes) of 10.0 nm and 15.0 nm.

If we graph the data we acquired on page 5 (your data is shown on this page for your reference), our graph would look something like this:

The graph pictured above shows an inverse relationship between the two variables (volume and pressure), that is, as volume increases, pressure decreases.

In our last lesson, we began to explore pressure. We observed how changing both the number of particles and volume affected pressure. We saw that the number of gas particle and pressure have a direct relationship, while volume and pressure have an indirect (or inverse) relationship.

In this lesson, we will examine the effect of temperature on pressure.

We will also be introduced to a new temperature scale in which we will record the temperature of a gas.

Below is a video of your instructor measuring the pressure of a sample of room temperature gas inside a flask. Pressure will be measured in units called kiloPascals (kPa). Watch the video and then answer the questions below.

Now your instructor will measure the pressure of a sample of gas inside a flask when the flask in submerged in both hot water and cold water. Pressure will be measured in units called kiloPascals (kPa). Complete the data table below after you view the video.

In order to analyze your acquired data, you will use Google Sheets. A template for Google Sheets has been created for you and can be found on Google Classroom.

1. Notice the data table has already been created for you. Enter the temperature data at room temperature.
2. Now enter temperature data for both cold/ice water and hot water.
3. Now enter pressure data for all temperatures. A graph should appear in a box that previously said "No data".
4. Add a trendline to the graph by opening the chart editor and clicking on “series” and clicking the “add trendline” box. The default trendline is linear which is what you want.
5. Then answer the questions below.

The graph you created on the last page should look very similar to the one shown below.

Notice the approximate temperature where pressure equals zero is -273 ^oC, this is no coincidence. -273 ^oC = 0 Kelvin, which is also known as absolute zero.

Absolute zero is the lowest theoretical temperature possible;  it is the temperature at which all particles cease movement. If particles are not moving, they cannot hit the walls of their container and therefore also have no pressure.

The Kelvin temperature scale is used when describing gases.  This is because the Kelvin scale is directly proportional to the kinetic energy of the gas particles. Thus, 0 K (absolute zero) means no kinetic energy. If particles have no kinetic energy, then they are not moving and cannot cause any pressure inside their container. This is why absolute zero (0 K) is also where pressure equals zero.

This temperature scale will become especially important when we begin gas calculations. Gas variable relationships we have explored can be expressed as mathematical equations. For example, as temperature decreases, so does volume, so if temperature is cut in half, volume will also be cut in half. This mathematical relationship will only hold true if the temperature is in Kelvin.

The Kelvin scale has no negative temperature as there can be no negative volumes, no negative pressures, and no negative number of particles.

The formulas to convert from the Celsius scale to Kelvin and back again are shown below. You will need them to complete the questions at the bottom of the page.

Celsius to Kelvin: K = ^oC + 273

Kelvin to Celsius: ^oC = K - 273

In this lesson, you will design a procedure to test the independent variable of your choice to determine how that independent variable affects the overall percent crush (your dependent variable) of a pop can.

You will collect data in class over several class periods. You will create a graph of that data, analyze your graph, and use a simulation to check the validity of your data. After checking the validity of your data, you will compose a claim based on your data.

You will be asked to support your claim with evidence, and finally asked to explain why your evidence supports your claim using scientific reasoning.

Below is a video of your instructor crushing a can (this will also be demonstrated in class) and a video demonstration of the can crush simulation you will be using later in this lesson. Watch both videos and then answer the questions below.

Now you will plan a controlled experiment. A controlled experiment is one that has a single independent variable, a single dependent variable, and all other variables held constant (controlled).

You may choose any one of the following as your independent variable: initial water amount, water temperature, can volume (if different size cans are available), or the amount of time the can is left on the hot plate. Percent crush will be the dependent variable for every experiment as that is what is being measured.

Remember whatever independent variable you choose that all other variables must be held constant. For example: if you decide to manipulate the water temperature (in the bucket), that is the only variable that can be manipulated. So in this particular experiment, the initial water amount, the can volume, and the amount of time the can is left on the hot plate must be constant in every trial conducted.

Your experiment must consist of nine trials, three trials for each data point. You will then calculate the average of the three trials at each data point. So using the above example of changing the water temperature, your group would need to conduct three trials using an ice bath, three trials using room temperature water, and three trials using hot water (while measuring the actual temperature of each for each trial).

In order to begin, your group must successfully crush a can and measure all of your variables including: initial water amount, water temperature, can volume (if different size cans are available), and the amount of time the can is left on the hot plate. These settings should be used as constants for all variables that are not your independent variable in each and every trial.

Use your experimental design on page 2 to complete three trials for each data point you are testing for your independent variable.

In order to measure the volume of each can you will need to fill it with water, then measure that amount of water using a graduated cylinder. This measurement should be taken before (initIal volume) and after (final volume) each can crush trial.

The formula to use for percent crush is:

If your group makes any known errors during a trial, you should consider that trial an outlier and complete it again.

In order to determine the relationship between your independent and dependent variable, you will need to create a graph. In order to create a graph within this interface, we will employ the same online data analysis platform we utilized in Lesson 3 called CODAP. Below, you will see a CODAP workbench.

1. The platform is below these instructions. Start by typing your independent variable in the table where it currently reads "Replace with Independent Variable". (Your independent variable is one of the following: initial water amount, water temperature, can volume, or amount of time the can is left on the hot plate.)
2. In order to create a graph, drag your independent variable to the x-axis of the plot as shown in the GIF on the right; the example GIF uses water temperature as an independent variable.
3. Drag the % Crush variable to the y-axis of the plot as shown in the GIF on the right.
4. Observe the resulting plot. Then answer the questions below the CODAP workbench.

In lesson 4, we learned how to identify trends in a graph of two variables for both a direct relationship and an inverse relationship.

But what if your graph doesn't clearly exhibit either of the relationships in the graphs shown above? There is another possibility that we have yet to discuss, that is two variables exhibiting no relationship. If adding a trendline to your data displays a line with a slope close to zero (a horizontal line), then your variables are said to have a no relationship. A graph of two variables (A and B) with a no relationship is shown below.

You will now use a simulation to help determine the reliability of the data your lab group acquired during class.

Experiment with the simulation by manipulating any of the variables (initial water amount, water temperature, or can volume). Be sure to hit "setup" after adjusting these variables or the change will not be reflected in the simulation. Also consider amount of time the can is left in the fire as a variable.

After you feel you have learned all the features of the simulation move on to answer the questions below:

Use your experimental design on page 2 to complete three trials for each data point you are testing for your independent variable using the simulation below.

We will again utilize CODAP to create a graph of your simulation data.

1. Start by typing your independent variable in the table where it currently reads "Replace with Independent Variable". (Your independent variable is one of the following: initial water amount, water temperature, can volume, or amount of time the can is left in the fire.)
2. In order to create a graph, drag your independent variable to the x-axis of the plot as shown in the GIF on the right; the example GIF uses water temperature as an independent variable.
3. Drag the % Crush variable to the y-axis of the plot as shown in the GIF on the right.
4. Observe the resulting plot. Then answer the questions below the CODAP workbench.

Throughout the KMT unit, we have been presented with experiments that involve the following variables: temperature, volume, pressure, and number of particles. The Can Crusher is not different in this aspect. Temperature in our experiment is seen both in the water temperature, and in the amount of time the can is left on the fire. Volume is seen in both the can volume and in the measurement of percent crush. The number of particles is seen in the initial water amount added to the can to start the experiment, and finally, pressure is obviously a factor (though not measured directly) throughout the experiment.

What is different in the Can Crusher experiment is that none of the variables (temperature, volume, pressure, or number of particles) are actually held constant throughout the experiment. In this case, identifying a simple relationship between two variables is impossible. In other words, the can crushing cannot be explained by simply stating that as pressure increases, volume decreases. The temperature was not held constant and neither were the number of particles in the can (the can remains open to the air as it is being heated, so particles in the can are allowed to escape). Stating that as temperature decreases, volume decreases cannot explain the entire phenomenon either as pressure is also changing through the experiment.

Explaining the can crush will require that you focus on what particles are doing on a microscopic level throughout the entire process. The can crush simulation includes a check box labeled "see-inside"; the simulation is included again below so you can perform a trial (or trials) while this box is checked. Be sure to observe the particles in the can throughout the entire can crush, then answer the questions below.