 When one fluid, a gas or a liquid, is brought into contact with another fluid, they diffuse into one another. You see this when food colouring is dropped into water, and you also know that if gas or smoke is released it will mix with air. Both of these are diffusion processes. I'm going to show you a simulation from FET that represents this diffusion process, and as you think about what's going on I want you to keep in mind the concept of probability. You start off with a population of particles contained on the left hand side of a divider. The particles are all moving around randomly, bumping into one another. Notice that when they collide they change direction, like billiard balls. When we remove the divider they're going to continue this behaviour, but each particle will now have the chance to randomly make its way through collisions into the other half of the container. The arrows at the bottom are going to show the flow of particles from one side of the container to the other. Okay, let's remove the divider. There's the flow arrow at the bottom. At the start the particle flow is only from left to right. That's because there aren't any particles on the right that could flow to the left. However, as time goes on and more particles make their way across to the right hand side, some of those can then move back to the left, and so the left hand flow arrow grows. Let's watch that again. This time watch the data box at the top, which shows how many particles are on each side. As long as there are more particles on the left, the chances of a left hand particle moving right outweighs the chance of a right hand particle moving left, so the right hand flow arrow is bigger. After the particles have been diffusing for a while, the number of particles on each side is about equal, which means there's an equal chance of a particle moving from left to right or from right to left. The arrows are now on average the same. Now you will see fluctuations, the arrows are not exactly the same all the time, but these are a natural result of the randomness in the system, and it's exaggerated in this simulation by the fact that it has a relatively small number of particles. At this point, when the left and right flow rates are equal, the system is said to be in equilibrium. Specifically for a chemist, it's in dynamic equilibrium. There are two key points here. The first is that looking at the system as an average, for instance, if you focus on the number of particles on each side, the system doesn't appear to be changing. There are those little fluctuations, but on average it's steady. Remember the larger the system, that is the more molecules that are involved, the truer this becomes. Because this simulation is looking at a very small number of particles, the fluctuations are more obvious. So on average things aren't changing. But the second key point is that if we look at the individual particles within the system, they're in constant motion, moving from one side to the other. This example is a simple physical system, no chemical reaction is occurring. It's merely gas atoms bumping around in a container. But the idea of dynamic equilibrium can also be applied to chemical reactions.