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Interactive results viewer: Computing single-particle flotation kinetics using automated mineralogy data and machine learning

Pereira, Lucas; Frenzel, Max; Hoang, Duong Huu; Tolosana-Delgado, Raimon; Rudolph, Martin; Gutzmer, Jens


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{
  "@context": "https://schema.org/", 
  "name": "Interactive results viewer: Computing single-particle flotation kinetics using automated mineralogy data and machine learning", 
  "version": "1", 
  "identifier": "https://doi.org/10.14278/rodare.920", 
  "license": "https://creativecommons.org/licenses/by/4.0/legalcode", 
  "@id": "https://doi.org/10.14278/rodare.920", 
  "creator": [
    {
      "@id": "https://orcid.org/0000-0001-8041-5406", 
      "name": "Pereira, Lucas", 
      "affiliation": "FWGA", 
      "@type": "Person"
    }, 
    {
      "@id": "https://orcid.org/0000-0001-6625-559X", 
      "name": "Frenzel, Max", 
      "affiliation": "FWGA", 
      "@type": "Person"
    }, 
    {
      "@id": "https://orcid.org/0000-0002-2320-7210", 
      "name": "Hoang, Duong Huu", 
      "affiliation": "FWGP", 
      "@type": "Person"
    }, 
    {
      "@id": "https://orcid.org/0000-0001-9847-0462", 
      "name": "Tolosana-Delgado, Raimon", 
      "affiliation": "FWGB", 
      "@type": "Person"
    }, 
    {
      "@id": "https://orcid.org/0000-0002-5374-6135", 
      "name": "Rudolph, Martin", 
      "affiliation": "FWGP", 
      "@type": "Person"
    }, 
    {
      "@id": "https://orcid.org/0000-0002-1034-6545", 
      "name": "Gutzmer, Jens", 
      "affiliation": "FWGA", 
      "@type": "Person"
    }
  ], 
  "keywords": [
    "Geometallurgy", 
    "Particle-tracking", 
    "Froth flotation", 
    "Automated mineralogy"
  ], 
  "sameAs": [
    "https://www.hzdr.de/publications/Publ-31588"
  ], 
  "datePublished": "2020-10-06", 
  "@type": "CreativeWork", 
  "url": "https://rodare.hzdr.de/record/920", 
  "inLanguage": {
    "name": "English", 
    "alternateName": "eng", 
    "@type": "Language"
  }, 
  "description": "<p>This plotting application allows the reader to interact with all results obtained in the case study presented in the publication</p>\n\n<p>&quot;Computing single-particle flotation kinetics using automated mineralogy data and machine learning&quot;, submitted on 07/10/2020 to Minerals Engineering and currently under review.</p>\n\n<p>The interactive plot displays the flotation kinetics modelling outcome (<em>k, R<sub>max</sub>, k<sub>m</sub></em>) for single-particles. The user is able to filter particles according to their intrinsic properties (modal composition, surface composition, size, and shape), thus allowing the user to understand the influence of every particle property in their process (i.e. flotation) behavior.</p>\n\n<p>The platform contains a help function to guide the user.</p>\n\n<p>It can be accessed here: <a href=\"https://pereira.shinyapps.io/flotationkinetics/\">Pereira et al. 2021 Flotation kinetics platform.</a></p>"
}
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