Tools used for researching luminescent nanoparticles
Python >= 3.8
You may instead install miniconda and it will take care of installing python when creating an environment. https://docs.conda.io/en/latest/miniconda.html
It is recommended to first create an isolated python environment.
$ conda create -n ki python=3.8
$ conda activate ki
Then install the repo as a python package called 'kira'.
$ pip install git+https://github.com/fcossio/nanoparticle-characterization
This repo has 2 specific use-cases:
Estimate the radius of a nanoparticle based on the measurement of BET specific surface area analysis, assuming a spherical morphology of the nanoparticle.
It can be used as a python method:
>>> from kira.bet.radius import BET_radius
>>> surface, surface_err = 20.5, 0.1 # (m²/g)
>>> density = 6.02 # (g/cm³)
>>> radius, radius_err = BET_radius(surface, surface_err, density)
>>> print(f"Estimated radius = {radius:.2f} ± {radius_err:.2f} nm")
Estimated radius = 24.31 ± 0.12
This method has been wrapped in a CLI command for ease of use directly on the terminal:
$ bet <surface> <surface_err> <density>
The idea is that many different nanoparticles will be measured in the spectophotometer along with a reference. Multiple runs of the same measurement may be performed in order to estimate the error. Then, the different nanoparticles and runs need to be be compared through plots. See example
Read multiple measurements and average them.
Compare multiple nanoparticles with different reference measurements and standard deviations.
Obtain Area Under the Curve.
