IV Analysis and Visualization Tool

(last updated September 9, 2025)

This Python codebase is designed to process, analyze, and visualize current-voltage (I_D-V_G) sweep data collected from a semiconductor probe station (e.g. micromanipulator3000). It is primarily used for the investigation of electrical characteristics of devices with varying design parameters — such as well width/length (W/L) ratios, structural differences, concentrations of dopamine, and/or other fabrication design configurations.

Features

• Automated Parsing of IV Sweep Data
  Takes in semi-raw .csv files containing multiple device sweeps and extracts blocks of measurement data based on user-defined parameters. For dataset comparisons, users must make multiple .csv files from the raw file to separate each configuration.

• Parameter Extraction
  For each device sweep, it computes key transistor characteristics including:

  • Threshold voltage (V_th)
  • Transconductance (g_m)
  • Subthreshold swing (SS)
  • Locally minimum current from the positive side (I_min)

• Data Filtering and Plotting
  Supports plotting both raw and log-scale I_D-V_G curves. You can filter the datapoints with the IV_filters.py module.

• Comparative Boxplots
  After collecting parameter data across devices, the tool generates boxplots for visual statistical comparison of configurations (e.g., W/L ratios, structural variations like nanowells, etc.) of the most recent two configurations you have inputted.

How It Works

1. CSV Input
   You provide a CSV file containing multiple blocks of device sweep data. Each block corresponds to one sweep of V_G.

2. Interactive Configuration
   At runtime, you're prompted to specify:

   • Number of configurations to compare (at zeroth iteration only)
   • CSV file path (repeated)
   • Block size (lines per measurement block, repeated if necessary)
   • Number of graphs (device sweeps) to analyze per configuration (repeated if necessary)

3. Graphing & Analysis
   The script parses each block, generates a log-scale and/or a non-log I_D-V_G plot, computes characteristic parameters, and stores the results in a console-printed format.

4. Visualization Summary
   Once all configurations are processed, the tool creates scatter plots comparing each extracted parameter across the different configurations.