{"data":{"id":"10.6084/m9.figshare.5746740","type":"dois","attributes":{"doi":"10.6084/m9.figshare.5746740","prefix":"10.6084","suffix":"m9.figshare.5746740","identifiers":[],"alternateIdentifiers":[],"creators":[{"name":"Deville, Sylvain","nameType":"Personal","givenName":"Sylvain","familyName":"Deville","affiliation":[],"nameIdentifiers":[{"schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-3363-3184","nameIdentifierScheme":"ORCID"}]}],"titles":[{"title":"Dataset: 5D imaging of freezing emulsions with solute effects"}],"publisher":"figshare","container":{},"publicationYear":2018,"subjects":[{"subject":"30306 Synthesis of Materials","subjectScheme":"FOR"},{"subject":"FOS: Chemical sciences","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"FOS: Chemical sciences","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"90503 Construction Materials","subjectScheme":"FOR"},{"subject":"FOS: Civil engineering","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"FOS: Civil engineering","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"91205 Functional Materials","subjectScheme":"FOR"},{"subject":"FOS: Materials engineering","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"FOS: Materials engineering","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"30304 Physical Chemistry of Materials","subjectScheme":"FOR"},{"subject":"91207 Metals and Alloy Materials","subjectScheme":"FOR"},{"subject":"90802 Food Engineering","subjectScheme":"FOR"},{"subject":"FOS: Other engineering and technologies","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"FOS: Other engineering and technologies","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"Geophysics"},{"subject":"FOS: Earth and related environmental sciences","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"FOS: Earth and related environmental sciences","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"Cell Biology"}],"contributors":[],"dates":[{"date":"2018-01-02","dateType":"Created"},{"date":"2018-04-20","dateType":"Updated"},{"date":"2018","dateType":"Issued"}],"language":null,"types":{"ris":"DATA","bibtex":"misc","citeproc":"dataset","schemaOrg":"Dataset","resourceType":"Dataset","resourceTypeGeneral":"Dataset"},"relatedIdentifiers":[],"relatedItems":[],"sizes":["8739371110 Bytes"],"formats":[],"version":null,"rightsList":[{"rights":"Creative Commons Attribution 4.0 International","rightsUri":"https://creativecommons.org/licenses/by/4.0/legalcode","schemeUri":"https://spdx.org/licenses/","rightsIdentifier":"cc-by-4.0","rightsIdentifierScheme":"SPDX"}],"descriptions":[{"description":"Welcome to this dataset ! \u003cbr\u003e\u003cbr\u003eThis dataset and code were used and developed for the paper \"5D imaging of freezing emulsions with solute effects\", by Dmytro Dedovets, Cécile Monteux, and Sylvain Deville, published in Science, April 20, 2018.\u003cbr\u003e\u003cbr\u003eThe paper is here: http://science.sciencemag.org/content/360/6386/303\u003cbr\u003e\u003cbr\u003eThe Python code has been developed to analyse the confocal images obtained during the freezing of emulsions. \u003cbr\u003e\u003cbr\u003eIf you want to use this code and the data we provided, you should organise your files as follows. Create a main directory with 2 subdirectory:\u003cbr\u003e- \"code\": put the three notebooks here. Create a folder inside called \"functions\". In this functions folder, you need to put the detect peak script which you can find here http://nbviewer.jupyter.org/github/demotu/BMC/blob/master/notebooks/DetectPeaks.ipynb\u003cbr\u003e- \"data\": put the data here\u003cbr\u003e\u003cbr\u003eThe dataset consists in image stacks (8.7Gb total). For each interface velocity, we have two sequences: one with the fluorescent channel of the liquid (filename ends with \"-solute\"), and a second one with the fluorescent channel of the droplet. We analyse both sequences separately in the code.\u003cbr\u003e\u003cbr\u003eWe tested the following interface velocities: 1, 2, 3, 4, 5, 6, 8, and 10 microns/s, for a temperature gradient of 5°C/mm.\u003cbr\u003e\u003cbr\u003eWhen you start the notebook, another directory (\"Results\") will be created, and all the .csv files and figures generated will be saved there.\u003cbr\u003e\u003cbr\u003eWe are not Python experts, but the code runs relatively fast. The whole analysis for one sequence runs in a few minutes on a 2016 MacBook Pro (3,3 GHz Intel Core i7).\u003cbr\u003e\u003cbr\u003eWe still work actively on the code to improve it, so any feedback and suggestions are warmly welcome. Please keep in touch with us if you want to discuss anything.\u003cbr\u003e\u003cbr\u003e-Sylvain Deville\u003cbr\u003eLaboratoire de Synthèse et Fonctionnalisation des Céramiques, Cavaillon, France\u003cbr\u003eEmail: sylvain.deville@saint-gobain.com, also on twitter @DevilleSy\u003cbr\u003e\u003cbr\u003e","descriptionType":"Abstract"}],"geoLocations":[],"fundingReferences":[],"xml":"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