Data · dataset · 2025
Quantifying non-Gaussian diffusion in transient microscopy using excess kurtosis
Listed in e-cienciaDatos
Coprehensible analysis of anomalous diffusion in transient microscopy.
Description
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: 1. Power dependent measurements.
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TScM measured at different injected carrier densities. 2. Repetition rate dependent measurements. TScM measured at different laser repetition rates, keeping fluence unalttered. 3.
Results from numerical simulations. 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. 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.
Links
Where it is published
- Dataverse dataset page edatos.consorciomadrono.es/dataset.xhtml?persistentId=doi%3A10.21950%2F2TSJNP ↗
landing page · from edatos consorciomadrono es
- DOI doi.org/10.21950/2tsjnp ↗
DOI / persistent id · from edatos consorciomadrono es
Catalogue records · 1
- Dataverse API edatos.consorciomadrono.es/api/datasets/:persistentId/?persistentId=doi%3A10.21950%2F2TSJ… ↗
metadata API · from edatos consorciomadrono es
Topics
- Stated by source
- Física
- From keywords
- Energy · Engineering
- Inferred from text
- Microscopy 75% · Nanotechnology 73%
Provenance · 1 source records, 11 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| e-cienciaDatos | doi:10.21950/2TSJNP | 12 d ago | JSON v1 |
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|---|---|---|---|
| concepts[field].anzsrc:group:4018 | enrichment · edatos consorciomadrono es | taxonomy-embedding@1.1.0 | title+keywords+description (73%) |
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| concepts[field].local:field:energy | mapping · edatos consorciomadrono es | connector:edatos_consorciomadrono_es@1.0.0 | /subjects |
| concepts[field].local:field:engineering | mapping · edatos consorciomadrono es | connector:edatos_consorciomadrono_es@1.0.0 | /subjects |
| concepts[modality].local:modality:microscopy | enrichment · edatos consorciomadrono es | keyword-concept-rules@1.0.0 | title+description (75%) |
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