Visualizing the Vapor Pressure of Minerals using Python
Visualizing the Vapor Pressure of Minerals using Python
Visualizing the Vapor Pressure of Minerals using Python
Process
Process
Annotated Bibliography
Analysis of C code
Python prototype creation
Usability Tests
Data Visualization
Code Documentation
Annotated Bibliography
Analysis of C code
Python prototype creation
Usability Tests
Data Visualization
Code Documentation
Annotated Bibliography
Analysis of C code
Python prototype creation
Usability Tests
Data Visualization
Code Documentation
My Role
My Role
Research Assistant
Python Developer
Research Assistant
Python Developer
Research Assistant
Python Developer
Timeline
Timeline
2 years (2020 - 2022)
2 years (2020 - 2022)
2 years (2020 - 2022)
Tools Used
Tools Used
Python
NumPy, Matplotlib
Anaconda + Spyder IDE
MS Excel
MS PowerPoint
Google Docs
Python
NumPy, Matplotlib
Anaconda + Spyder IDE
MS Excel
MS PowerPoint
Google Docs
Python
NumPy, Matplotlib
Anaconda + Spyder IDE
MS Excel
MS PowerPoint
Google Docs
The Project's Purpose
The Project's Purpose
When exploring the universe, many scientists look at spectroscopy data of different stars, planets, and other objects to determine that object's composition. But in order to know exactly what they are looking at, they first must have lab data to compare their observational data to. When looking at hot objects, this gets tricky (long story short, heat affects how the materials "look" to telescopes).
Most past studies look at materials at lower (near ambient) temperatures. In order to provide updated, comprehensive data, our lab conducted Thermogravimetric Analysis (TGA) experiments where we measured the mass-loss of various materials expected to be in these hot objects (namely exoplanets, hot Jupiters, and brown dwarfs) at those temperatures (sometimes over 1200 C!!). After collecting this data, the Python code I developed calculated the mineral's vapor pressure, and displayed it against other studies, as well as other runs of the same mineral.
When exploring the universe, many scientists look at spectroscopy data of different stars, planets, and other objects to determine that object's composition. But in order to know exactly what they are looking at, they first must have lab data to compare their observational data to. When looking at hot objects, this gets tricky (long story short, heat affects how the materials "look" to telescopes).
Most past studies look at materials at lower (near ambient) temperatures. In order to provide updated, comprehensive data, our lab conducted Thermogravimetric Analysis (TGA) experiments where we measured the mass-loss of various materials expected to be in these hot objects (namely exoplanets, hot Jupiters, and brown dwarfs) at those temperatures (sometimes over 1200 C!!). After collecting this data, the Python code I developed calculated the mineral's vapor pressure, and displayed it against other studies, as well as other runs of the same mineral.
When exploring the universe, many scientists look at spectroscopy data of different stars, planets, and other objects to determine that object's composition. But in order to know exactly what they are looking at, they first must have lab data to compare their observational data to. When looking at hot objects, this gets tricky (long story short, heat affects how the materials "look" to telescopes).
Most past studies look at materials at lower (near ambient) temperatures. In order to provide updated, comprehensive data, our lab conducted Thermogravimetric Analysis (TGA) experiments where we measured the mass-loss of various materials expected to be in these hot objects (namely exoplanets, hot Jupiters, and brown dwarfs) at those temperatures (sometimes over 1200 C!!). After collecting this data, the Python code I developed calculated the mineral's vapor pressure, and displayed it against other studies, as well as other runs of the same mineral.
Learning About the Project
Learning About the Project
My first task when starting this project was to understand the significance of the project and learn about the current state of the field (aka what other work is being done?) To do this, I completed various annotated bibliographies covering relevant topics/keywords such as "Vapor Pressure", "Optical Properties", "High-temp Thermodynamic Properties", and "Spectra of Exoplanets". An example of one of these annotated bibliographies can be viewed here.
After learning about the project, I was often in the lab, performing the experiments. I prepared, ran, and recorded the TGA experiments myself. This includes creating the cells used to hold the powdered minerals, pictured below.
My first task when starting this project was to understand the significance of the project and learn about the current state of the field (aka what other work is being done?) To do this, I completed various annotated bibliographies covering relevant topics/keywords such as "Vapor Pressure", "Optical Properties", "High-temp Thermodynamic Properties", and "Spectra of Exoplanets". An example of one of these annotated bibliographies can be viewed here.
After learning about the project, I was often in the lab, performing the experiments. I prepared, ran, and recorded the TGA experiments myself. This includes creating the cells used to hold the powdered minerals, pictured below.
My first task when starting this project was to understand the significance of the project and learn about the current state of the field (aka what other work is being done?) To do this, I completed various annotated bibliographies covering relevant topics/keywords such as "Vapor Pressure", "Optical Properties", "High-temp Thermodynamic Properties", and "Spectra of Exoplanets". An example of one of these annotated bibliographies can be viewed here.
After learning about the project, I was often in the lab, performing the experiments. I prepared, ran, and recorded the TGA experiments myself. This includes creating the cells used to hold the powdered minerals, pictured below.
The cell has a small hole drilled into the front to allow vapors to escape of which the size is measured. It is made using alumina tubes, sealed with high temperature cement.
The cell has a small hole drilled into the front to allow vapors to escape of which the size is measured. It is made using alumina tubes, sealed with high temperature cement.
The cell has a small hole drilled into the front to allow vapors to escape of which the size is measured. It is made using alumina tubes, sealed with high temperature cement.
Creating the Python Script
Creating the Python Script
After running lab experiments, we then needed to process the data using Python scripts. To create the Python script used to calculate the vapor pressure of the minerals used, I had to meet certain requirements:
After running lab experiments, we then needed to process the data using Python scripts. To create the Python script used to calculate the vapor pressure of the minerals used, I had to meet certain requirements:
After running lab experiments, we then needed to process the data using Python scripts. To create the Python script used to calculate the vapor pressure of the minerals used, I had to meet certain requirements:
Translate C code functions to Python
Translate C code functions to Python
Translate C code functions to Python
Must be able to compare different runs
Must be able to compare different runs
Must be able to compare different runs
Calculate and include error bars
Calculate and include error bars
Calculate and include error bars
Perform simple linear regression to output vapor pressure equation
Perform simple linear regression to output vapor pressure equation
Perform simple linear regression to output vapor pressure equation
The Python program evolved as the project did, with more features being added as the amount of experimental runs being done increased. But the four basic functionalities listed above were always present.
The Python program evolved as the project did, with more features being added as the amount of experimental runs being done increased. But the four basic functionalities listed above were always present.
The Python program evolved as the project did, with more features being added as the amount of experimental runs being done increased. But the four basic functionalities listed above were always present.
Usability Testing
Usability Testing
To test the program, I met with the primary user (the project's primary investigator) a few times a week to update them on the changes made, perform some testing using data from experimental runs performed that week, and collected their feedback on what to add or change next. These tests were done by comparing the plot of our runs to data found from other studies, with an example shown below.
To test the program, I met with the primary user (the project's primary investigator) a few times a week to update them on the changes made, perform some testing using data from experimental runs performed that week, and collected their feedback on what to add or change next. These tests were done by comparing the plot of our runs to data found from other studies, with an example shown below.
To test the program, I met with the primary user (the project's primary investigator) a few times a week to update them on the changes made, perform some testing using data from experimental runs performed that week, and collected their feedback on what to add or change next. These tests were done by comparing the plot of our runs to data found from other studies, with an example shown below.
The data is plotted temperature vs. vapor pressure with a fitted line for our data and a solid line showing a different study's results.
The data is plotted temperature vs. vapor pressure with a fitted line for our data and a solid line showing a different study's results.
Presenting the Findings
Presenting the Findings
After creating several plots with our data, we were prepared to share our findings with fellow members of the planetary science community. We did this by presenting posters at the American Geophysical Union 2021 Conference in New Orleans, LA. The AGU conference is the most influential event in the world dedicated to the advancement of Earth and space sciences and had over 10,000 attendees in December 2021. We were able to share info about our lab, our process, and our current findings in the poster I created, shown below.
After creating several plots with our data, we were prepared to share our findings with fellow members of the planetary science community. We did this by presenting posters at the American Geophysical Union 2021 Conference in New Orleans, LA. The AGU conference is the most influential event in the world dedicated to the advancement of Earth and space sciences and had over 10,000 attendees in December 2021. We were able to share info about our lab, our process, and our current findings in the poster I created, shown below.
After creating several plots with our data, we were prepared to share our findings with fellow members of the planetary science community. We did this by presenting posters at the American Geophysical Union 2021 Conference in New Orleans, LA. The AGU conference is the most influential event in the world dedicated to the advancement of Earth and space sciences and had over 10,000 attendees in December 2021. We were able to share info about our lab, our process, and our current findings in the poster I created, shown below.
Program Documentation: Tutorial and Troubleshooting
Program Documentation: Tutorial and Troubleshooting
At the end of my work on the project, I was tasked in creating some "how-to" documents, including some troubleshooting help for current and future users. The entire project consisted of several python programs that each fulfilled a specific purpose, so a "how-to" was written for each .py file, listing steps on how to process the lab data. Along with these files, there was also ample comments within the python programs to guide the user.
At the end of my work on the project, I was tasked in creating some "how-to" documents, including some troubleshooting help for current and future users. The entire project consisted of several python programs that each fulfilled a specific purpose, so a "how-to" was written for each .py file, listing steps on how to process the lab data. Along with these files, there was also ample comments within the python programs to guide the user.
At the end of my work on the project, I was tasked in creating some "how-to" documents, including some troubleshooting help for current and future users. The entire project consisted of several python programs that each fulfilled a specific purpose, so a "how-to" was written for each .py file, listing steps on how to process the lab data. Along with these files, there was also ample comments within the python programs to guide the user.
A full pdf of the "How-to's" can be viewed here.
A full pdf of the "How-to's" can be viewed here.
A full pdf of the documentation can be viewed here.
Lessons Learned
Lessons Learned
When working on this project, I was introduced to many new libraries within Python, and it helped me sharpen my Python skills, as well as my coding skills in general. Because of this work, I am more confident in my abilities to learn more coding languages and work on complex quantitative projects.
It has also inspired me to adopt coding languages such as HTML, CSS, and JavaScript, so that I can have both front-end and back-end languages in my repertoire, making me a more well rounded developer.
When working on this project, I was introduced to many new libraries within Python, and it helped me sharpen my Python skills, as well as my coding skills in general. Because of this work, I am more confident in my abilities to learn more coding languages and work on complex quantitative projects.
It has also inspired me to adopt coding languages such as HTML, CSS, and JavaScript, so that I can have both front-end and back-end languages in my repertoire, making me a more well rounded developer.
When working on this project, I was introduced to many new libraries within Python, and it helped me sharpen my Python skills, as well as my coding skills in general. Because of this work, I am more confident in my abilities to learn more coding languages and work on complex quantitative projects.
It has also inspired me to adopt coding languages such as HTML, CSS, and JavaScript, so that I can have both front-end and back-end languages in my repertoire, making me a more well rounded developer.
