Here I combine my knowledge of electrochemistry and coding. Students will be given a set of battery parameters (ie, temperature, cycling, battery chemistry) and use machine learning to find the best combination. Depending on the student's knowlege the ML algorithms can be as simple or as complicated as they would like. Students should have some basic coding knowledge in python.

Machine learning to predict battery behavior

I should start off by saying this porject would cost money, presumably around $1500. It is also fairly ambitious and would require a decent amount of time, which is why I am listing it as a second project idea. If a student is interested in this and has experience with electronics, I would be willing to apply for funding from external sources for this. This project has been done by other high school students before. 

Materials for the low cost AFM are: 
1. OPU disassembled from a DVD ROM
2. Piezo speakers
3. Signal connector 
4. Precision screws 
5. Circuit boards
6. AFM probes

The tools needed are: 
1. A soldering iron 
2. Solder 
3. Quick-dry adhesive 
4. Epoxy 
5. Magnets 
6. Screw driver. 

For more information I've included the following sources:

1. https://www.nanoandmore.com/what-is-atomic-force-microscopy

2. Grey, F. Creativity unleashed. Nature Nanotech 10, 480 (2015). https://doi-org.prox.lib.ncsu.edu/10.1038/nnano.2015.95

3. https://www.instructables.com/A-Low-Cost-Atomic-Force-Microscope-%E4%BD%8E%E6%88%90%E6%9C%AC%E5%8E%9F%E5%AD%90%E5%8A%9B%E9%A1%AF%E5%BE%AE%E9%8F%A1/

Build a DIY AFM

This would be a research paper looking at how science is used in our communities. How are new scientific findings disseminated to the public? What is the relationship between public use and public funding for science. Should scientific data be made fully transparent? (ie, should scientists be required to disclose all their data in an experiment?)

Is "scientific research" relevant to what we use in our daily lives?

Students will learn how to gather football statistics from online sources. They'll use machine learning to draft the best player combinations for an 8-team fantasy football league, with each team having 15 players. Depending on the student's knowlege the ML algorithms can be as simple or as complicated as they would like. They can also explore using the algorithm to set weekly lineups. Students should have some basic coding knowledge in python.