What a student working in CLEAN does
Frequently students ask this question: "what will I do working in the group?". The following should give you some sense of the process involved in the various projects we work on:
- Find an experimental or design problem in renewable energy where computation and modelling can play a useful role.
- Speak with experimentalists to understand what kind of system they are working on, what they are trying to achieve, what they can measure, and what they understand or do not understand. While we don't do experiments in our group, we do have several close international collaborations with groups in chemistry, physics, and material science.
- Based on the discussion above, understand what _level_ of theory one must use to simulate an experiment on a computer. For example, if an experimentalist is trying to measure the equation of state of helium (not sure why you would bother, but bear with me), perhaps the ideal gas law is a reasonable level of theory to model that system. If that's the case, we can either write some computer code to numerically solve the model for the experimental conditions, or use some existing open source packages that have that functionality. If the system is more complicated (and they always are), we'll need to use a higher level of theory (like quantum mechanics) to model the system.
- Visualize/ analyze/ quantify the results from the simulation to compare with the experimental data.
- Once we are satisfied we can accurately model what is going on, we can use this understanding to:
- Provide a physical explanation for an effect (or at least confirm or disprove an experimentalists hypothesis for what is going on)
- Make predictions for _new_ experiments. This is important because it can save a lot of time. Experiments are difficult. They take time and money. If we can tell someone which material or molecule they should look at (because we think it will result in a more efficient solar cell, catalyst, etc), we can save a lot of time and money. For renewable energy, this is very important because there is a limited amount of time to find a solution, and a limited number of resources available to try and solve the problem.