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What is Data Science?
What is Data Science?
As my other cohorts have already gone over, Data Science is the study of collecting, storing, and analyzing datasets, so that people are able to make meaningful conclusions from them. On the upper left-hand side, shows the Lebombo bone, a baboon's fibula with 29 notches on it, dating back to 35,000 BCE. It is hypothesized to be used as a lunar phase counter, with the marks acting as tally marks. On the upper left-hand side, shows the Jupyter Notebook logo, an open source, web based application for sharing code and text.
What is the Materials Project?
What is the Materials Project?
The Materials Project is an organisation that hopes to discover the properties of all known materials using data science, supercomputer calculations , and experimentation. Currently, they have analyzed more than 130,000 inorganic compounds. With this knowledge, people are able to understand and use materials more efficiently
Designing a Phone
Designing a Phone
The Phone Project is a mini lesson which uses materials from the Materials Project Database to build the components of a mobile phone. The database is useful here as it has lots of properties of many different materials, so we are able to find the materials with properties we want, on our phone.
The Electric Car Project
The Electric Car Project
Similar to the Phone Project, I will also be doing a mini project where, using the materials from the Materials Project Database, I will be building my own electric car. In an electric car, I would to prioritize the strength of the exterior of the car, the transparency of the car windows and the capacitance and voltage of the car battery, while making sure the cost and density is low, so the car will be cheaper and lighter.
The Process
The Process
Using Jupyter Notebook
Using Jupyter Notebook
Using JupyterNotebook, I imported the dataset for all the materials
Cost Per Volume
Cost Per Volume
I then needed the cost per volume for each material. This was done using the equation: cost per volume = cost per mass x density.
Python Code
Python Code
Using python code, I imputed a series of instructions which stated the requirements each material needed to have for each component of the electric car.
Results
Results
MP-1639 BN, the hardest material available in our search, with an average density, and below average volume cost.
MP-625998 LiHO, one of the most transparent material and cheap materials shown.
MP-755882 MnAl2O4 , has a very large capacitance, with low voltage and volume cost.
Conclusion
Conclusion
In summary, I was able to learn many new concepts and terms in data science, and utilized code and material datasets in order to create a my own project. Using this experience, I am now able to apply these skills my future problems and obstacles. I thank all the staff and volunteers who helped me and other cohorts in order for this amazing experience to happen.
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