Experimental Data for: Machine learning enabled image analysis of time-temperature sensing colloidal arrays
Authors/Creators
- 1. Department of Chemistry, University of Bayreuth, Universitätsstr. 30, 95447 Bayreuth, Germany
- 2. Theoretical Physics VII and Bavarian Center for Battery Technologies, University of Bayreuth, Universitätsstr. 30, 95447 Bayreuth, Germany
- 3. Department of Chemistry and Bavarian Center for Battery Technologies, University of Bayreuth, Universitätsstr. 30, 95447 Bayreuth, Germany
Description
This dataset contains images of colloidal arrays functioning as time-temperature integrating, autonomous sensors. Each image shows a sensor consisting of multiple colloidal crystals with varying compositions of particles with different glass transition temperatures. Details on the composition and manufacturing procedures are explained in the corresponding publication. The data is organized into folders with different temperature setpoints. For each temperature, we investigated 10 samples. The name of the samples corresponds to their creation date. The name of the image files corresponds to their acquisition time. The first image in each sample folder was taken at the very start of the heating period. Hence, the heating time can be calculated by subtracting the start time from the acquisition time.
Files
CroppedImages.zip
Files
(2.8 GB)
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