ofet_import

Import characterisation data from Organic Thin Film Transistors (O-FETs) from available online sources, into a common python data structure.

Supports the following data sources:

flexterra_2021: https://zenodo.org/records/17701094 purdue_2022: https://github.com/yeeyoung/TCASi-ONC iit_cnr_2025: https://zenodo.org/records/17274644

Usage

import os

import iit_cnr_2025 
transistors = iit_cnr_2025.import_transistors(r"path/to/data")

Then consider using https://github.com/event-driven-robotics/ivplot to plot the transistors, example code:

from ivplot import ivplot

for transistor_name, transistor in transistors_purdue_2022.items():
    label = '_'.join(('purdue', transistor_name))
    fig = ivplot(transistor['sweeps'], marker='o', label=label, markersize=6)

##Description

Each script is an importer for a different source of raw data.

Each script describes where to download the raw data, and exposes a function import_data, which returns a dict in this form:

{
    "<transistor_name>": {
        "sweeps": [...],
        "params": {...},
        "data": pandas.DataFrame(...)
    },
    ...
}

Each sweep in the list of 'sweeps' is a dict in this form:

{
    'datetime': str, # in form 'YYYY_MM_DD_HH_MM_SS'
    'type': str,     # 'g' for Vg sweep or 'd' for Vd sweep, or 'both' for mixed data.
    'data': df       # DataFrame with columns ['vgs', 'vds', 'ids']
}

'params' may look like:

transistor['params'] == {
    'length': <float or '?'>,
    'width': <float or '?'>,
    'polarity': 'p' or 'n' or '?',
    'permittivity_insulator_relative': 3.15,
    'thickness_insulator': 700e-9,
    'temperature': 290,
}

Units are always SI units: metres, Kelvin etc.