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Coprehensible analysis of anomalous diffusion in transient microscopy. We introduce the parameter of kurtosis to quantify deviations from a Gaussian shape of the exciton distribution. As a case example we emply transient scattering microscopy (TScM, or stroboSCAT) in bulk tungesten diselenide (WSe2) revealing that exciton populations drastically deviate from pure Gaussian diffusion. Numerical simulations suggest that the origin for these deviations arise from the coexistance of multiple populations at short times, while after a few ns the crucial factor become trap states.
The full dataset consists of three complimentary datasets:
All the data is collected in the same WSe2 flake. The data acquisition was done using custom python code and the analysis is performed using custom python code which can be found in GitHub. https://github.com/EaRodriguez3/TM_kurtosis
For more information about the dataset and the techniques consult the related publication (to be added at a later date) or contact us.
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Contains many directories with the power of the laser in uW as the name, the github code transforms the power to laser fluence. Each directory has all the differential images files and a 'analyzed_dataset.npy' file obtained by performing the analysis depicted in the Github code. For simplicity the files have a corresponding metadata file with the experiment parameters. The files are in -npy format albeit the calculated final dataset is also found in .hdf5 format for non-python users.
Same as power_dep files, this time the directories have the repetition rates in MHz.
Only simulation results can be found here. A total of 94 files can be found here. All files are .dat files and are structured in pairs. Each pair constitute the result of a simulation for specific parameters, determined in the name of the file. In a pair there is a file containing time (column 1), intensity (column 2 and 3) and variance (column 4), the other file contains the kurtosis, time (column 1), kurtosis (column 2).
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