New method for estimating shift factors in time–temperature superposition models View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2013-08

AUTHORS

Salvador Naya, Antonio Meneses, Javier Tarrío-Saavedra, Ramón Artiaga, Jorge López-Beceiro, Carlos Gracia-Fernández

ABSTRACT

Prediction of polymer properties at short and long observation times is usually performed through time–temperature superposition (TTS) models, which make use of some calculated shift factors. Although TTS principle has been used for many decades, no firm rules have been developed for obtaining the master curves. In the absence of reliable long-term data, it has been a common practice to try to minimize the discrepancy between the individual shifted curves. It was reported that a TTS method is more reliable as that discrepancy is minimized. In this study, a new method for obtaining the shift factors is presented. The optimal shift factors were estimated by minimizing the distance between the single curve derivatives with respect to the derivative of the curve at the reference temperature. That shift factors were tested with some classical models. The data were analyzed by statistical methods, making use of bootstrap resampling and spline estimation. The shift factors obtained from the proposed method allow for obtaining smooth master curves. The accuracy of the estimations was evaluated. More... »

PAGES

453-460

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s10973-013-3193-1

DOI

http://dx.doi.org/10.1007/s10973-013-3193-1

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1009559684


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/2008/0104", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Statistics", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/01", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Mathematical Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "University of A Coru\u00f1a", 
          "id": "https://www.grid.ac/institutes/grid.8073.c", 
          "name": [
            "Departamento de Matem\u00e1ticas, Escuela Polit\u00e9cnica Superior, Universidade da Coru\u00f1a, Ferrol, Spain"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Naya", 
        "givenName": "Salvador", 
        "id": "sg:person.010043463111.42", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010043463111.42"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Universidad Nacional de Chimborazo", 
          "id": "https://www.grid.ac/institutes/grid.442237.4", 
          "name": [
            "Universidad Nacional de Chimborazo, Riobamba, Ecuador"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Meneses", 
        "givenName": "Antonio", 
        "id": "sg:person.013334762273.92", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013334762273.92"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of A Coru\u00f1a", 
          "id": "https://www.grid.ac/institutes/grid.8073.c", 
          "name": [
            "Departamento de Matem\u00e1ticas, Escuela Polit\u00e9cnica Superior, Universidade da Coru\u00f1a, Ferrol, Spain"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Tarr\u00edo-Saavedra", 
        "givenName": "Javier", 
        "id": "sg:person.010527411315.90", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010527411315.90"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of A Coru\u00f1a", 
          "id": "https://www.grid.ac/institutes/grid.8073.c", 
          "name": [
            "Departamento de Ingenier\u00eda Industrial II, Escuela Polit\u00e9cnica Superior, Universidade da Coru\u00f1a, Ferrol, Spain"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Artiaga", 
        "givenName": "Ram\u00f3n", 
        "id": "sg:person.011361512031.23", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011361512031.23"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of A Coru\u00f1a", 
          "id": "https://www.grid.ac/institutes/grid.8073.c", 
          "name": [
            "Departamento de Ingenier\u00eda Industrial II, Escuela Polit\u00e9cnica Superior, Universidade da Coru\u00f1a, Ferrol, Spain"
          ], 
          "type": "Organization"
        }, 
        "familyName": "L\u00f3pez-Beceiro", 
        "givenName": "Jorge", 
        "id": "sg:person.07766551031.96", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07766551031.96"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "name": [
            "TA Instruments, Madrid, Spain"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Gracia-Fern\u00e1ndez", 
        "givenName": "Carlos", 
        "id": "sg:person.016171676123.38", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016171676123.38"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1111/j.1365-2621.2006.01468.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1002082225"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2514/3.2447", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1005055588"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1149/1.2428174", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006060703"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/9780470423837.ch5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006978349"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0008-6215(98)00153-0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012353675"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/app.35113", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1014936110"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1557/jmr.2012.73", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035584249"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/app.21648", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1044033615"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/app.21648", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1044033615"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/ja01164a117", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1055776935"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/ja01619a008", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1055813183"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/ma0712394", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1056193537"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/ma0712394", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1056193537"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1109705929", 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-1-4899-4541-9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1109705929", 
          "https://doi.org/10.1007/978-1-4899-4541-9"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-1-4899-4541-9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1109705929", 
          "https://doi.org/10.1007/978-1-4899-4541-9"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2013-08", 
    "datePublishedReg": "2013-08-01", 
    "description": "Prediction of polymer properties at short and long observation times is usually performed through time\u2013temperature superposition (TTS) models, which make use of some calculated shift factors. Although TTS principle has been used for many decades, no firm rules have been developed for obtaining the master curves. In the absence of reliable long-term data, it has been a common practice to try to minimize the discrepancy between the individual shifted curves. It was reported that a TTS method is more reliable as that discrepancy is minimized. In this study, a new method for obtaining the shift factors is presented. The optimal shift factors were estimated by minimizing the distance between the single curve derivatives with respect to the derivative of the curve at the reference temperature. That shift factors were tested with some classical models. The data were analyzed by statistical methods, making use of bootstrap resampling and spline estimation. The shift factors obtained from the proposed method allow for obtaining smooth master curves. The accuracy of the estimations was evaluated.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/s10973-013-3193-1", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1294862", 
        "issn": [
          "1388-6150", 
          "1572-8943"
        ], 
        "name": "Journal of Thermal Analysis and Calorimetry", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "2", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "113"
      }
    ], 
    "name": "New method for estimating shift factors in time\u2013temperature superposition models", 
    "pagination": "453-460", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "2d89e9191acfc1b2a620ba9268bf208d0e1af630aec5793b3b9a12a1fcc501c2"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s10973-013-3193-1"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1009559684"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s10973-013-3193-1", 
      "https://app.dimensions.ai/details/publication/pub.1009559684"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-10T19:18", 
    "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_8678_00000582.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "http://link.springer.com/10.1007%2Fs10973-013-3193-1"
  }
]
 

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/s10973-013-3193-1'

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/s10973-013-3193-1'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s10973-013-3193-1'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s10973-013-3193-1'


 

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

141 TRIPLES      21 PREDICATES      40 URIs      19 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s10973-013-3193-1 schema:about anzsrc-for:01
2 anzsrc-for:0104
3 schema:author Na35b83bbf93d401c9c85935a28dce708
4 schema:citation sg:pub.10.1007/978-1-4899-4541-9
5 https://app.dimensions.ai/details/publication/pub.1109705929
6 https://doi.org/10.1002/9780470423837.ch5
7 https://doi.org/10.1002/app.21648
8 https://doi.org/10.1002/app.35113
9 https://doi.org/10.1016/s0008-6215(98)00153-0
10 https://doi.org/10.1021/ja01164a117
11 https://doi.org/10.1021/ja01619a008
12 https://doi.org/10.1021/ma0712394
13 https://doi.org/10.1111/j.1365-2621.2006.01468.x
14 https://doi.org/10.1149/1.2428174
15 https://doi.org/10.1557/jmr.2012.73
16 https://doi.org/10.2514/3.2447
17 schema:datePublished 2013-08
18 schema:datePublishedReg 2013-08-01
19 schema:description Prediction of polymer properties at short and long observation times is usually performed through time–temperature superposition (TTS) models, which make use of some calculated shift factors. Although TTS principle has been used for many decades, no firm rules have been developed for obtaining the master curves. In the absence of reliable long-term data, it has been a common practice to try to minimize the discrepancy between the individual shifted curves. It was reported that a TTS method is more reliable as that discrepancy is minimized. In this study, a new method for obtaining the shift factors is presented. The optimal shift factors were estimated by minimizing the distance between the single curve derivatives with respect to the derivative of the curve at the reference temperature. That shift factors were tested with some classical models. The data were analyzed by statistical methods, making use of bootstrap resampling and spline estimation. The shift factors obtained from the proposed method allow for obtaining smooth master curves. The accuracy of the estimations was evaluated.
20 schema:genre research_article
21 schema:inLanguage en
22 schema:isAccessibleForFree false
23 schema:isPartOf N5ee29c1fc71c4c899166902901097f9a
24 Ndccf59bdb43148a29d815195618bd30e
25 sg:journal.1294862
26 schema:name New method for estimating shift factors in time–temperature superposition models
27 schema:pagination 453-460
28 schema:productId N3a9a013c787c4e6a965df3327e30dba2
29 N7c4ccb2acdc141f9937ff846178e8bf2
30 Nd1a1c59fe2fb4692bbc277ef0450b0ba
31 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009559684
32 https://doi.org/10.1007/s10973-013-3193-1
33 schema:sdDatePublished 2019-04-10T19:18
34 schema:sdLicense https://scigraph.springernature.com/explorer/license/
35 schema:sdPublisher N780eeced3d6749659d086b284680e2ee
36 schema:url http://link.springer.com/10.1007%2Fs10973-013-3193-1
37 sgo:license sg:explorer/license/
38 sgo:sdDataset articles
39 rdf:type schema:ScholarlyArticle
40 N34ac3ccea19249fdba2a2f63733f6dec schema:name TA Instruments, Madrid, Spain
41 rdf:type schema:Organization
42 N3a9a013c787c4e6a965df3327e30dba2 schema:name doi
43 schema:value 10.1007/s10973-013-3193-1
44 rdf:type schema:PropertyValue
45 N5ee29c1fc71c4c899166902901097f9a schema:issueNumber 2
46 rdf:type schema:PublicationIssue
47 N780eeced3d6749659d086b284680e2ee schema:name Springer Nature - SN SciGraph project
48 rdf:type schema:Organization
49 N7c4ccb2acdc141f9937ff846178e8bf2 schema:name readcube_id
50 schema:value 2d89e9191acfc1b2a620ba9268bf208d0e1af630aec5793b3b9a12a1fcc501c2
51 rdf:type schema:PropertyValue
52 N8b5f00281bbf434bbf5ea1fd2a01942c rdf:first sg:person.010527411315.90
53 rdf:rest Nd355afbef1c8413982b0d87fde0ba8f5
54 N8b8b4f73dd514bcca72fc956cd80f1a1 rdf:first sg:person.07766551031.96
55 rdf:rest Nd993f7b0a854490f8c99dfe25fdfb488
56 Na35b83bbf93d401c9c85935a28dce708 rdf:first sg:person.010043463111.42
57 rdf:rest Ne2c1b1c41be248afbd5c5b927a9830e3
58 Nd1a1c59fe2fb4692bbc277ef0450b0ba schema:name dimensions_id
59 schema:value pub.1009559684
60 rdf:type schema:PropertyValue
61 Nd355afbef1c8413982b0d87fde0ba8f5 rdf:first sg:person.011361512031.23
62 rdf:rest N8b8b4f73dd514bcca72fc956cd80f1a1
63 Nd993f7b0a854490f8c99dfe25fdfb488 rdf:first sg:person.016171676123.38
64 rdf:rest rdf:nil
65 Ndccf59bdb43148a29d815195618bd30e schema:volumeNumber 113
66 rdf:type schema:PublicationVolume
67 Ne2c1b1c41be248afbd5c5b927a9830e3 rdf:first sg:person.013334762273.92
68 rdf:rest N8b5f00281bbf434bbf5ea1fd2a01942c
69 anzsrc-for:01 schema:inDefinedTermSet anzsrc-for:
70 schema:name Mathematical Sciences
71 rdf:type schema:DefinedTerm
72 anzsrc-for:0104 schema:inDefinedTermSet anzsrc-for:
73 schema:name Statistics
74 rdf:type schema:DefinedTerm
75 sg:journal.1294862 schema:issn 1388-6150
76 1572-8943
77 schema:name Journal of Thermal Analysis and Calorimetry
78 rdf:type schema:Periodical
79 sg:person.010043463111.42 schema:affiliation https://www.grid.ac/institutes/grid.8073.c
80 schema:familyName Naya
81 schema:givenName Salvador
82 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010043463111.42
83 rdf:type schema:Person
84 sg:person.010527411315.90 schema:affiliation https://www.grid.ac/institutes/grid.8073.c
85 schema:familyName Tarrío-Saavedra
86 schema:givenName Javier
87 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010527411315.90
88 rdf:type schema:Person
89 sg:person.011361512031.23 schema:affiliation https://www.grid.ac/institutes/grid.8073.c
90 schema:familyName Artiaga
91 schema:givenName Ramón
92 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011361512031.23
93 rdf:type schema:Person
94 sg:person.013334762273.92 schema:affiliation https://www.grid.ac/institutes/grid.442237.4
95 schema:familyName Meneses
96 schema:givenName Antonio
97 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013334762273.92
98 rdf:type schema:Person
99 sg:person.016171676123.38 schema:affiliation N34ac3ccea19249fdba2a2f63733f6dec
100 schema:familyName Gracia-Fernández
101 schema:givenName Carlos
102 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016171676123.38
103 rdf:type schema:Person
104 sg:person.07766551031.96 schema:affiliation https://www.grid.ac/institutes/grid.8073.c
105 schema:familyName López-Beceiro
106 schema:givenName Jorge
107 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07766551031.96
108 rdf:type schema:Person
109 sg:pub.10.1007/978-1-4899-4541-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1109705929
110 https://doi.org/10.1007/978-1-4899-4541-9
111 rdf:type schema:CreativeWork
112 https://app.dimensions.ai/details/publication/pub.1109705929 schema:CreativeWork
113 https://doi.org/10.1002/9780470423837.ch5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006978349
114 rdf:type schema:CreativeWork
115 https://doi.org/10.1002/app.21648 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044033615
116 rdf:type schema:CreativeWork
117 https://doi.org/10.1002/app.35113 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014936110
118 rdf:type schema:CreativeWork
119 https://doi.org/10.1016/s0008-6215(98)00153-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012353675
120 rdf:type schema:CreativeWork
121 https://doi.org/10.1021/ja01164a117 schema:sameAs https://app.dimensions.ai/details/publication/pub.1055776935
122 rdf:type schema:CreativeWork
123 https://doi.org/10.1021/ja01619a008 schema:sameAs https://app.dimensions.ai/details/publication/pub.1055813183
124 rdf:type schema:CreativeWork
125 https://doi.org/10.1021/ma0712394 schema:sameAs https://app.dimensions.ai/details/publication/pub.1056193537
126 rdf:type schema:CreativeWork
127 https://doi.org/10.1111/j.1365-2621.2006.01468.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1002082225
128 rdf:type schema:CreativeWork
129 https://doi.org/10.1149/1.2428174 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006060703
130 rdf:type schema:CreativeWork
131 https://doi.org/10.1557/jmr.2012.73 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035584249
132 rdf:type schema:CreativeWork
133 https://doi.org/10.2514/3.2447 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005055588
134 rdf:type schema:CreativeWork
135 https://www.grid.ac/institutes/grid.442237.4 schema:alternateName Universidad Nacional de Chimborazo
136 schema:name Universidad Nacional de Chimborazo, Riobamba, Ecuador
137 rdf:type schema:Organization
138 https://www.grid.ac/institutes/grid.8073.c schema:alternateName University of A Coruña
139 schema:name Departamento de Ingeniería Industrial II, Escuela Politécnica Superior, Universidade da Coruña, Ferrol, Spain
140 Departamento de Matemáticas, Escuela Politécnica Superior, Universidade da Coruña, Ferrol, Spain
141 rdf:type schema:Organization
 




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


...