J-V Baseline Data Collection — Colab Notebook
- Team Name:
[Determine a name for your team for the rest of the semester.] - Authors:
[Write in the names of the authors of this notebook.] - Apparatus # and Cell #:
[Write in the number of your apparatus (JV1, JV2, or JV3) that you used for your measurements, as well as your cell number.]
Reminder. To maintain consistency in your notebooks between team members, it is important to add markdown cells to discuss what you are doing and answer the questions. Also, make sure to put inline comments in your code.
1 Analysis
1.1 Plot J-V Curves
Plot the forward scan J-V curves for all eight pixels.
- Remember you can copy and paste code from your Python tutorial - in fact it is encouraged!
- The apparatus measures current (I) versus voltage and saves data files with an
IV_prefix. To convert to current density, divide by the pixel illuminated area (0.14 cm²): J = I / area. We refer to these as "J-V" measurements throughout the course.
# Your code hereQuestion 1: Discuss what you observe from comparing all eight J-V curves.
1.2 Calculate PCE
Calculate the Power Conversion Efficiency (PCE) for each pixel using the forward scans.
- Determine \(J_{sc}\), \(V_{oc}\), \(J_{pmax}\), and \(V_{pmax}\).
- Use \(P_{in} = 99.8\ \text{mW/cm}^2\).
# Your code hereQuestion 2: Compare your PCE values to Figure 4b in Tirawat et al. (2024), linked on this week's Canvas page.
3 Use of AI (required)
- How your team used AI tools: Describe the specific tasks where AI-assisted tools were involved. For example, did AI help with writing, debugging, optimizing, or refining your code? Which components of the analysis did your team use AI on?
- When your team used AI tools: Specify at what stage(s) of your programming process you used AI. Was it during initial code development, troubleshooting, etc.?
- Which AI tools your team used: Identify the AI tools or platforms your team consulted (e.g., ChatGPT, GitHub Copilot, etc.).