Jülich DATA

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Jülich DATA is the central institutional repository for research data of Forschungszentrum Jülich.

It serves as a platform for all research data generated at Forschungszentrum Jülich or created in this context. Please feel welcome to index your research data here.

This service is managed by the Central Library. Please see our guide about how to use this service or feel free to reach out via email to forschungsdaten@fz-juelich.de.

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10,771 to 10,780 of 10,828 Results

713.png Aug 28, 2020 - ELPVPower: A dataset for large scale PV power prediction using EL images of cells PNG Image - 276.9 KB - SHA-256: 1cbb03c8ff19a0d795505e0ffbafe035bef64a66598991d93d608a7ebc140dbb
714.png Aug 28, 2020 - ELPVPower: A dataset for large scale PV power prediction using EL images of cells PNG Image - 282.3 KB - SHA-256: 27e5e8c827b1d744adbd2883a1920f1e5438c96fb3ea73146804b58badf0aba3
715.png Aug 28, 2020 - ELPVPower: A dataset for large scale PV power prediction using EL images of cells PNG Image - 301.6 KB - SHA-256: c7bb9d5c405cc417b0da5b7770cdac415a6755955cbda4ba220bc2a44ceedef0
716.png Aug 28, 2020 - ELPVPower: A dataset for large scale PV power prediction using EL images of cells PNG Image - 277.6 KB - SHA-256: 514055cda02a4f595552a04bbd2fbdbd7ec7d22e74554b48447659887c1314e9
717.png Aug 28, 2020 - ELPVPower: A dataset for large scale PV power prediction using EL images of cells PNG Image - 279.7 KB - SHA-256: 38e189f06e6acd5e768a63a77387cf57ef27ad4bcded41c7073657fa6b78621f
718.png Aug 28, 2020 - ELPVPower: A dataset for large scale PV power prediction using EL images of cells PNG Image - 277.1 KB - SHA-256: debf5453b6f70b079c82a9b39dcc88558581222a2dfae822398bfc25c70d7b15
data.csv Aug 28, 2020 - ELPVPower: A dataset for large scale PV power prediction using EL images of cells Comma Separated Values - 43.6 KB - SHA-256: 69d0ad11f6a0667d85dfef622a1f3ac67a7d6da908131d09c505ca5fcaccfa90
README.md Aug 28, 2020 - ELPVPower: A dataset for large scale PV power prediction using EL images of cells Markdown Text - 1.1 KB - SHA-256: 83f24cc1f9991283cc577965c054d18580a50f268e96c999f1db9caab234b20d
Data used in: Surfactant-Mediated Epitaxial Growth of Single-Layer Graphene in an Unconventional Orientation on SiC Aug 25, 2020 - Peter Grünberg Institut – Quantum Nanoscience (PGI-3) Bocquet, F. C.; Lin, Y.-R; Franke, M.; Samiseresht, N.; Parhizkar, S.; Soubatch, S.; Lee, T.-L.; Kumpf, C.; Tautz, F. S., 2020, "Data used in: Surfactant-Mediated Epitaxial Growth of Single-Layer Graphene in an Unconventional Orientation on SiC", https://doi.org/10.26165/JUELICH-DATA/VGEHRD, Jülich DATA, V1 We present here the raw data used to produce the figures in the publication Bocquet et al. Phys. Rev. Lett. 125 106102 (2020). Unless explicitly stated, all metadata necessary to analyze the data is included in the files (or filenames) themselves. The raw data are placed in a sep...
13_SiC_Coffee(GrR0)_165eV_x=23_y=17.5_z=277.5_theta=128_t=7ms_size=170_550points_I=1.05A_Corr_Full_02_Si(111)_Ceasar_165eV_x=21_y=20_z=277.5_theta=128_t=7ms_size=170_550points_I=1.05A_enzeert-2.png Aug 25, 2020 - Data used in: Surfactant-Mediated Epitaxial Growth of Single-Layer Graphene in an Unconventional Orientation on SiC PNG Image - 226.9 KB - SHA-256: 9c7d1d3391c3b39c92970e9ca6312a40afe9649cbdf23c61384d3cfcb362d801

713.png

Aug 28, 2020 - ELPVPower: A dataset for large scale PV power prediction using EL images of cells

PNG Image - 276.9 KB - SHA-256: 1cbb03c8ff19a0d795505e0ffbafe035bef64a66598991d93d608a7ebc140dbb

714.png

Aug 28, 2020 - ELPVPower: A dataset for large scale PV power prediction using EL images of cells

PNG Image - 282.3 KB - SHA-256: 27e5e8c827b1d744adbd2883a1920f1e5438c96fb3ea73146804b58badf0aba3

715.png

Aug 28, 2020 - ELPVPower: A dataset for large scale PV power prediction using EL images of cells

PNG Image - 301.6 KB - SHA-256: c7bb9d5c405cc417b0da5b7770cdac415a6755955cbda4ba220bc2a44ceedef0

716.png

Aug 28, 2020 - ELPVPower: A dataset for large scale PV power prediction using EL images of cells

PNG Image - 277.6 KB - SHA-256: 514055cda02a4f595552a04bbd2fbdbd7ec7d22e74554b48447659887c1314e9

717.png

Aug 28, 2020 - ELPVPower: A dataset for large scale PV power prediction using EL images of cells

PNG Image - 279.7 KB - SHA-256: 38e189f06e6acd5e768a63a77387cf57ef27ad4bcded41c7073657fa6b78621f

718.png

Aug 28, 2020 - ELPVPower: A dataset for large scale PV power prediction using EL images of cells

PNG Image - 277.1 KB - SHA-256: debf5453b6f70b079c82a9b39dcc88558581222a2dfae822398bfc25c70d7b15

data.csv

Aug 28, 2020 - ELPVPower: A dataset for large scale PV power prediction using EL images of cells

Comma Separated Values - 43.6 KB - SHA-256: 69d0ad11f6a0667d85dfef622a1f3ac67a7d6da908131d09c505ca5fcaccfa90

README.md

Aug 28, 2020 - ELPVPower: A dataset for large scale PV power prediction using EL images of cells

Markdown Text - 1.1 KB - SHA-256: 83f24cc1f9991283cc577965c054d18580a50f268e96c999f1db9caab234b20d

Data used in: Surfactant-Mediated Epitaxial Growth of Single-Layer Graphene in an Unconventional Orientation on SiC

Aug 25, 2020 - Peter Grünberg Institut – Quantum Nanoscience (PGI-3)

Bocquet, F. C.; Lin, Y.-R; Franke, M.; Samiseresht, N.; Parhizkar, S.; Soubatch, S.; Lee, T.-L.; Kumpf, C.; Tautz, F. S., 2020, "Data used in: Surfactant-Mediated Epitaxial Growth of Single-Layer Graphene in an Unconventional Orientation on SiC", https://doi.org/10.26165/JUELICH-DATA/VGEHRD, Jülich DATA, V1

We present here the raw data used to produce the figures in the publication Bocquet et al. Phys. Rev. Lett. 125 106102 (2020). Unless explicitly stated, all metadata necessary to analyze the data is included in the files (or filenames) themselves. The raw data are placed in a sep...

13_SiC_Coffee(GrR0)_165eV_x=23_y=17.5_z=277.5_theta=128_t=7ms_size=170_550points_I=1.05A_Corr_Full_02_Si(111)_Ceasar_165eV_x=21_y=20_z=277.5_theta=128_t=7ms_size=170_550points_I=1.05A_enzeert-2.png

Aug 25, 2020 - Data used in: Surfactant-Mediated Epitaxial Growth of Single-Layer Graphene in an Unconventional Orientation on SiC

PNG Image - 226.9 KB - SHA-256: 9c7d1d3391c3b39c92970e9ca6312a40afe9649cbdf23c61384d3cfcb362d801

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