Stochastic 3D Models for the Micro-structure of Advanced Functional Materials View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2015

AUTHORS

Volker Schmidt , Gerd Gaiselmann , Ole Stenzel

ABSTRACT

Optimization of functional materials is a challenging task. Thereby, stochastic morphology models can provide helpful methods. Three classes of stochastic models are presented describing different micro-structures of functional materials by means of methods from stochastic geometry, graph theory and time series analysis. The structures of these materials strongly differ from each other, where we consider organic solar cells being an anisotropic composite of two materials, nonwoven gas-diffusion layers in proton exchange membrane fuel cells consisting of a system of curved carbon fibers, and graphite electrodes in Li-ion batteries which are built up by an isotropic two-phase system (i.e., consisting of a pore and a solid phase). The goal is to give an overview how the stochastic modeling of functional materials can be organized and to provide an outlook how these models can be used for material optimization with respect to functionality. More... »

PAGES

95-141

Book

TITLE

Stochastic Geometry, Spatial Statistics and Random Fields

ISBN

978-3-319-10063-0
978-3-319-10064-7

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-319-10064-7_4

DOI

http://dx.doi.org/10.1007/978-3-319-10064-7_4

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1026381159


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0912", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Materials Engineering", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/09", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Engineering", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "University of Ulm", 
          "id": "https://www.grid.ac/institutes/grid.6582.9", 
          "name": [
            "Institute of Stochastics, Ulm University, 89069\u00a0Ulm, Germany"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Schmidt", 
        "givenName": "Volker", 
        "id": "sg:person.01051347101.48", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01051347101.48"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Ulm", 
          "id": "https://www.grid.ac/institutes/grid.6582.9", 
          "name": [
            "Institute of Stochastics, Ulm University, 89069\u00a0Ulm, Germany"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Gaiselmann", 
        "givenName": "Gerd", 
        "id": "sg:person.014360117451.79", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014360117451.79"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Ulm", 
          "id": "https://www.grid.ac/institutes/grid.6582.9", 
          "name": [
            "Institute of Stochastics, Ulm University, 89069\u00a0Ulm, Germany"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Stenzel", 
        "givenName": "Ole", 
        "id": "sg:person.0755640733.86", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0755640733.86"
        ], 
        "type": "Person"
      }
    ], 
    "datePublished": "2015", 
    "datePublishedReg": "2015-01-01", 
    "description": "Optimization of functional materials is a challenging task. Thereby, stochastic morphology models can provide helpful methods. Three classes of stochastic models are presented describing different micro-structures of functional materials by means of methods from stochastic geometry, graph theory and time series analysis. The structures of these materials strongly differ from each other, where we consider organic solar cells being an anisotropic composite of two materials, nonwoven gas-diffusion layers in proton exchange membrane fuel cells consisting of a system of curved carbon fibers, and graphite electrodes in Li-ion batteries which are built up by an isotropic two-phase system (i.e., consisting of a pore and a solid phase). The goal is to give an overview how the stochastic modeling of functional materials can be organized and to provide an outlook how these models can be used for material optimization with respect to functionality.", 
    "editor": [
      {
        "familyName": "Schmidt", 
        "givenName": "Volker", 
        "type": "Person"
      }
    ], 
    "genre": "chapter", 
    "id": "sg:pub.10.1007/978-3-319-10064-7_4", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": {
      "isbn": [
        "978-3-319-10063-0", 
        "978-3-319-10064-7"
      ], 
      "name": "Stochastic Geometry, Spatial Statistics and Random Fields", 
      "type": "Book"
    }, 
    "name": "Stochastic 3D Models for the Micro-structure of Advanced Functional Materials", 
    "pagination": "95-141", 
    "productId": [
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/978-3-319-10064-7_4"
        ]
      }, 
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "7dadd272132b49ed1c101d350ebaedb5d677f7780e373eada33faa5892f4e1fd"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1026381159"
        ]
      }
    ], 
    "publisher": {
      "location": "Cham", 
      "name": "Springer International Publishing", 
      "type": "Organisation"
    }, 
    "sameAs": [
      "https://doi.org/10.1007/978-3-319-10064-7_4", 
      "https://app.dimensions.ai/details/publication/pub.1026381159"
    ], 
    "sdDataset": "chapters", 
    "sdDatePublished": "2019-04-16T00:35", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000001_0000000264/records_8700_00000045.jsonl", 
    "type": "Chapter", 
    "url": "http://link.springer.com/10.1007/978-3-319-10064-7_4"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-10064-7_4'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-10064-7_4'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-10064-7_4'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-10064-7_4'


 

This table displays all metadata directly associated to this object as RDF triples.

79 TRIPLES      22 PREDICATES      27 URIs      20 LITERALS      8 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/978-3-319-10064-7_4 schema:about anzsrc-for:09
2 anzsrc-for:0912
3 schema:author N6e6fe8d3a9b641a2be967ba61f4bc1cd
4 schema:datePublished 2015
5 schema:datePublishedReg 2015-01-01
6 schema:description Optimization of functional materials is a challenging task. Thereby, stochastic morphology models can provide helpful methods. Three classes of stochastic models are presented describing different micro-structures of functional materials by means of methods from stochastic geometry, graph theory and time series analysis. The structures of these materials strongly differ from each other, where we consider organic solar cells being an anisotropic composite of two materials, nonwoven gas-diffusion layers in proton exchange membrane fuel cells consisting of a system of curved carbon fibers, and graphite electrodes in Li-ion batteries which are built up by an isotropic two-phase system (i.e., consisting of a pore and a solid phase). The goal is to give an overview how the stochastic modeling of functional materials can be organized and to provide an outlook how these models can be used for material optimization with respect to functionality.
7 schema:editor N71d9c6955ce34d84bc64ee2f058d1476
8 schema:genre chapter
9 schema:inLanguage en
10 schema:isAccessibleForFree false
11 schema:isPartOf Nd850b4d58ddf4bc6a46cda1303e59ecb
12 schema:name Stochastic 3D Models for the Micro-structure of Advanced Functional Materials
13 schema:pagination 95-141
14 schema:productId N24d6f69ead2d469ca3d4335fc604318c
15 Nd3afcce7eedd4bcb89a063ed3be079b6
16 Ne806dfa1424647fdbb7b14adeb133261
17 schema:publisher N1b6bb7891b804befa82940315302aebf
18 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026381159
19 https://doi.org/10.1007/978-3-319-10064-7_4
20 schema:sdDatePublished 2019-04-16T00:35
21 schema:sdLicense https://scigraph.springernature.com/explorer/license/
22 schema:sdPublisher Nb3c533c09dab4196af8c38790b7e7faf
23 schema:url http://link.springer.com/10.1007/978-3-319-10064-7_4
24 sgo:license sg:explorer/license/
25 sgo:sdDataset chapters
26 rdf:type schema:Chapter
27 N16e28df8f6324303a1615cda8a3d86c2 rdf:first sg:person.0755640733.86
28 rdf:rest rdf:nil
29 N19ebee20c9be45df982ca5d5e8a6e56d rdf:first sg:person.014360117451.79
30 rdf:rest N16e28df8f6324303a1615cda8a3d86c2
31 N1b6bb7891b804befa82940315302aebf schema:location Cham
32 schema:name Springer International Publishing
33 rdf:type schema:Organisation
34 N24d6f69ead2d469ca3d4335fc604318c schema:name doi
35 schema:value 10.1007/978-3-319-10064-7_4
36 rdf:type schema:PropertyValue
37 N6e6fe8d3a9b641a2be967ba61f4bc1cd rdf:first sg:person.01051347101.48
38 rdf:rest N19ebee20c9be45df982ca5d5e8a6e56d
39 N71d9c6955ce34d84bc64ee2f058d1476 rdf:first Nd11af7b275d346a8804b79efeee2f03d
40 rdf:rest rdf:nil
41 Nb3c533c09dab4196af8c38790b7e7faf schema:name Springer Nature - SN SciGraph project
42 rdf:type schema:Organization
43 Nd11af7b275d346a8804b79efeee2f03d schema:familyName Schmidt
44 schema:givenName Volker
45 rdf:type schema:Person
46 Nd3afcce7eedd4bcb89a063ed3be079b6 schema:name dimensions_id
47 schema:value pub.1026381159
48 rdf:type schema:PropertyValue
49 Nd850b4d58ddf4bc6a46cda1303e59ecb schema:isbn 978-3-319-10063-0
50 978-3-319-10064-7
51 schema:name Stochastic Geometry, Spatial Statistics and Random Fields
52 rdf:type schema:Book
53 Ne806dfa1424647fdbb7b14adeb133261 schema:name readcube_id
54 schema:value 7dadd272132b49ed1c101d350ebaedb5d677f7780e373eada33faa5892f4e1fd
55 rdf:type schema:PropertyValue
56 anzsrc-for:09 schema:inDefinedTermSet anzsrc-for:
57 schema:name Engineering
58 rdf:type schema:DefinedTerm
59 anzsrc-for:0912 schema:inDefinedTermSet anzsrc-for:
60 schema:name Materials Engineering
61 rdf:type schema:DefinedTerm
62 sg:person.01051347101.48 schema:affiliation https://www.grid.ac/institutes/grid.6582.9
63 schema:familyName Schmidt
64 schema:givenName Volker
65 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01051347101.48
66 rdf:type schema:Person
67 sg:person.014360117451.79 schema:affiliation https://www.grid.ac/institutes/grid.6582.9
68 schema:familyName Gaiselmann
69 schema:givenName Gerd
70 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014360117451.79
71 rdf:type schema:Person
72 sg:person.0755640733.86 schema:affiliation https://www.grid.ac/institutes/grid.6582.9
73 schema:familyName Stenzel
74 schema:givenName Ole
75 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0755640733.86
76 rdf:type schema:Person
77 https://www.grid.ac/institutes/grid.6582.9 schema:alternateName University of Ulm
78 schema:name Institute of Stochastics, Ulm University, 89069 Ulm, Germany
79 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...