Jülich DATA

Publication Year: 2024

41 to 50 of 3,515 Results

15.tif Jan 31, 2025 - Dataset for: Investigating the metastability of amorphous calcium carbonate by droplet microfluidics experiments using machine learning TIFF Image - 373.8 MB - SHA-256: cc280be6b01582f9048ca712123381ae7df1a844a471de8485ae1094fd9219f4
16.tif Jan 31, 2025 - Dataset for: Investigating the metastability of amorphous calcium carbonate by droplet microfluidics experiments using machine learning TIFF Image - 373.8 MB - SHA-256: 90fd6f75acf48ce8023868945b2648018b5f67e45d5167876fed0f9c761b0a18
4.tif Jan 31, 2025 - Dataset for: Investigating the metastability of amorphous calcium carbonate by droplet microfluidics experiments using machine learning TIFF Image - 373.8 MB - SHA-256: 7fecb26e06f838872bccde469459f4cd2c87a000515756af2e00c984da07825c
6.tif Jan 31, 2025 - Dataset for: Investigating the metastability of amorphous calcium carbonate by droplet microfluidics experiments using machine learning TIFF Image - 373.8 MB - SHA-256: aee1aa739563679adce36331b1d174000be9428a0e41e5e26374a48213066d35
7.tif Jan 31, 2025 - Dataset for: Investigating the metastability of amorphous calcium carbonate by droplet microfluidics experiments using machine learning TIFF Image - 373.8 MB - SHA-256: 1e92100061cf67da8cde8bc95ccac15ed92bd9affcbd2333e3ebea4d1ccaa135
8.tif Jan 31, 2025 - Dataset for: Investigating the metastability of amorphous calcium carbonate by droplet microfluidics experiments using machine learning TIFF Image - 373.8 MB - SHA-256: faec5016bddb5359c0fbb1f54154f437d6809c255cfd10019153d07fb46044cf
9.tif Jan 31, 2025 - Dataset for: Investigating the metastability of amorphous calcium carbonate by droplet microfluidics experiments using machine learning TIFF Image - 373.8 MB - SHA-256: 0cffd82f2ca4a0bb333e4ed11760b1d9fcf97a51fb92ed5dd304fabf842ce183
README.txt Jan 31, 2025 - Dataset for: Investigating the metastability of amorphous calcium carbonate by droplet microfluidics experiments using machine learning Plain Text - 764 B - SHA-256: f73eec798734588aeaa8fc31ef835aa77edf586ddf8cac77888d27a3f57e6a92
t0_snapshots.pptx Jan 31, 2025 - Dataset for: Investigating the metastability of amorphous calcium carbonate by droplet microfluidics experiments using machine learning MS Powerpoint - 58.4 MB - SHA-256: b4abef9f781b125406ee5960926d125c8229135385f6332d70951f338104fccb
HyData: HyPlant FLUO at-sensor radiance data packages and FLOX measurements for SIF retrieval method development from selected campaigns of the years 2018 - 2023 Jan 8, 2025 - HyPlant Buffat, Jim; Rascher, Uwe; Rademske, Patrick; Siegmann, Bastian; Junker-Frohn, Laura Verena; Emin, Dzhaner; Grygosch, Lars, 2024, "HyData: HyPlant FLUO at-sensor radiance data packages and FLOX measurements for SIF retrieval method development from selected campaigns of the years 2018 - 2023", https://doi.org/10.26165/JUELICH-DATA/QKJKPW, Jülich DATA, V3 This dataset consists of HyPlant FLUO at-sensor radiance measurements from different campaigns in the years 2018 - 2023, FLOX measurements corresponding to several campaigns and matching SFMNN and SFM SIF products.

15.tif

Jan 31, 2025 - Dataset for: Investigating the metastability of amorphous calcium carbonate by droplet microfluidics experiments using machine learning

TIFF Image - 373.8 MB - SHA-256: cc280be6b01582f9048ca712123381ae7df1a844a471de8485ae1094fd9219f4

16.tif

Jan 31, 2025 - Dataset for: Investigating the metastability of amorphous calcium carbonate by droplet microfluidics experiments using machine learning

TIFF Image - 373.8 MB - SHA-256: 90fd6f75acf48ce8023868945b2648018b5f67e45d5167876fed0f9c761b0a18

4.tif

Jan 31, 2025 - Dataset for: Investigating the metastability of amorphous calcium carbonate by droplet microfluidics experiments using machine learning

TIFF Image - 373.8 MB - SHA-256: 7fecb26e06f838872bccde469459f4cd2c87a000515756af2e00c984da07825c

6.tif

Jan 31, 2025 - Dataset for: Investigating the metastability of amorphous calcium carbonate by droplet microfluidics experiments using machine learning

TIFF Image - 373.8 MB - SHA-256: aee1aa739563679adce36331b1d174000be9428a0e41e5e26374a48213066d35

7.tif

Jan 31, 2025 - Dataset for: Investigating the metastability of amorphous calcium carbonate by droplet microfluidics experiments using machine learning

TIFF Image - 373.8 MB - SHA-256: 1e92100061cf67da8cde8bc95ccac15ed92bd9affcbd2333e3ebea4d1ccaa135

8.tif

Jan 31, 2025 - Dataset for: Investigating the metastability of amorphous calcium carbonate by droplet microfluidics experiments using machine learning

TIFF Image - 373.8 MB - SHA-256: faec5016bddb5359c0fbb1f54154f437d6809c255cfd10019153d07fb46044cf

9.tif

Jan 31, 2025 - Dataset for: Investigating the metastability of amorphous calcium carbonate by droplet microfluidics experiments using machine learning

TIFF Image - 373.8 MB - SHA-256: 0cffd82f2ca4a0bb333e4ed11760b1d9fcf97a51fb92ed5dd304fabf842ce183

README.txt

Jan 31, 2025 - Dataset for: Investigating the metastability of amorphous calcium carbonate by droplet microfluidics experiments using machine learning

Plain Text - 764 B - SHA-256: f73eec798734588aeaa8fc31ef835aa77edf586ddf8cac77888d27a3f57e6a92

t0_snapshots.pptx

Jan 31, 2025 - Dataset for: Investigating the metastability of amorphous calcium carbonate by droplet microfluidics experiments using machine learning

MS Powerpoint - 58.4 MB - SHA-256: b4abef9f781b125406ee5960926d125c8229135385f6332d70951f338104fccb

HyData: HyPlant FLUO at-sensor radiance data packages and FLOX measurements for SIF retrieval method development from selected campaigns of the years 2018 - 2023

Jan 8, 2025 - HyPlant

Buffat, Jim; Rascher, Uwe; Rademske, Patrick; Siegmann, Bastian; Junker-Frohn, Laura Verena; Emin, Dzhaner; Grygosch, Lars, 2024, "HyData: HyPlant FLUO at-sensor radiance data packages and FLOX measurements for SIF retrieval method development from selected campaigns of the years 2018 - 2023", https://doi.org/10.26165/JUELICH-DATA/QKJKPW, Jülich DATA, V3

This dataset consists of HyPlant FLUO at-sensor radiance measurements from different campaigns in the years 2018 - 2023, FLOX measurements corresponding to several campaigns and matching SFMNN and SFM SIF products.