High Resolution Photoluminescence Microscopy Images And Spectra Of Air-Suspended Single-Wall Carbon Nanotubes

Citation Author(s):
Matthias
Kastner
Submitted by:
Matthias Kastner
Last updated:
Thu, 12/12/2019 - 13:43
DOI:
10.21227/qc8f-3256
Data Format:
Igor Pro Data
processed to json
PDF
PNG
Links:
gitlab
github
thesis
License:
Creative Commons Attribution
616 Views
Categories:
Artificial Intelligence
Image Processing
Machine Learning
Image Fusion
Keywords:
confocal microscopy
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Abstract 

The dataset contains high-resolution microscopy images and confocal spectra of semiconducting single-wall carbon nanotubes. Carbon nanotubes allow down-scaling of electronic components to the nano-scale. There is initial evidence from Monte Carlo simulations that microscopy images with high digital resolution show energy information in the Bessel wave pattern that is visible in these images. In this dataset, images from Silicon and InGaAs cameras, as well as spectra, give valuable insights into the spectroscopic properties of these single-photon emitters. The source data is connected to a GitLab pipeline running on docker containers for data processing to various formats that are valid input to machine learning algorithms to further prove that there is information about the excitonic emission wavelength contained in the microscopic images.

Instructions: 

The dataset is generated with docker containers from the measurement data. The measured data is in Igor Binary Waves. The specific format can be read with a custom reader an processed with various tools.

Processing will be applied automatically to various output formats using docker containers.

 

See current development status and dataset description will be updated on

https://gitlab.com/ukos-git/nanotubes

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