Chromatographic determination of the diffusion coefficients of light hydrocarbons in polymers View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2017-01

AUTHORS

E. E. Yakubenko, A. A. Korolev, P. P. Chapala, M. V. Bermeshev, A. Yu. Kanat’eva, A. A. Kurganov

ABSTRACT

Gas-chromatographic determination of the diffusion coefficients that allows for the compressibility of the mobile phase has been suggested. The diffusion coefficients were determined for light hydrocarbons С1–С4 in four polymers with a high free volume, which are candidates for use as gas-separating membranes. The diffusion coefficients calculated from chromatographic data were shown to be one or two orders of magnitude smaller than the values obtained by the membrane method. This may be due to the presence of an additional flow through the membrane caused by the pressure gradient across the membrane in membrane methods. More... »

PAGES

175-181

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1134/s0036024417010319

DOI

http://dx.doi.org/10.1134/s0036024417010319

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1083759026


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/2008/0904", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Chemical 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": "A.V.Topchiev Institute of Petrochemical Synthesis", 
          "id": "https://www.grid.ac/institutes/grid.423490.8", 
          "name": [
            "Topchiev Institute of Petrochemical Synthesis, Russian Academy of Sciences, Moscow, Russia"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Yakubenko", 
        "givenName": "E. E.", 
        "id": "sg:person.01277702211.03", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01277702211.03"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "A.V.Topchiev Institute of Petrochemical Synthesis", 
          "id": "https://www.grid.ac/institutes/grid.423490.8", 
          "name": [
            "Topchiev Institute of Petrochemical Synthesis, Russian Academy of Sciences, Moscow, Russia"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Korolev", 
        "givenName": "A. A.", 
        "id": "sg:person.0761776377.67", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0761776377.67"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "A.V.Topchiev Institute of Petrochemical Synthesis", 
          "id": "https://www.grid.ac/institutes/grid.423490.8", 
          "name": [
            "Topchiev Institute of Petrochemical Synthesis, Russian Academy of Sciences, Moscow, Russia"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Chapala", 
        "givenName": "P. P.", 
        "id": "sg:person.012346031703.46", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012346031703.46"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "A.V.Topchiev Institute of Petrochemical Synthesis", 
          "id": "https://www.grid.ac/institutes/grid.423490.8", 
          "name": [
            "Topchiev Institute of Petrochemical Synthesis, Russian Academy of Sciences, Moscow, Russia"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Bermeshev", 
        "givenName": "M. V.", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "A.V.Topchiev Institute of Petrochemical Synthesis", 
          "id": "https://www.grid.ac/institutes/grid.423490.8", 
          "name": [
            "Topchiev Institute of Petrochemical Synthesis, Russian Academy of Sciences, Moscow, Russia"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kanat\u2019eva", 
        "givenName": "A. Yu.", 
        "id": "sg:person.010657112101.27", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010657112101.27"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "A.V.Topchiev Institute of Petrochemical Synthesis", 
          "id": "https://www.grid.ac/institutes/grid.423490.8", 
          "name": [
            "Topchiev Institute of Petrochemical Synthesis, Russian Academy of Sciences, Moscow, Russia"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kurganov", 
        "givenName": "A. A.", 
        "id": "sg:person.01240135562.44", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01240135562.44"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1016/j.memsci.2006.05.030", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003042793"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1134/s0036024409040268", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015637620", 
          "https://doi.org/10.1134/s0036024409040268"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.chroma.2015.01.053", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020540712"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/pc.23432", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036467039"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.memsci.2014.09.043", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1038392058"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.memsci.2013.11.002", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1042493151"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1039/tf9656101637", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1049025453"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1039/tf9666202341", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050735805"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1042/bj0500679", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051155949"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1042/bj0500679", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051155949"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/ac60075a013", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1055026868"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/acs.macromol.5b02087", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1055118928"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/ma100656e", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1056194085"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/ma100656e", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1056194085"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2017-01", 
    "datePublishedReg": "2017-01-01", 
    "description": "Gas-chromatographic determination of the diffusion coefficients that allows for the compressibility of the mobile phase has been suggested. The diffusion coefficients were determined for light hydrocarbons \u04211\u2013\u04214 in four polymers with a high free volume, which are candidates for use as gas-separating membranes. The diffusion coefficients calculated from chromatographic data were shown to be one or two orders of magnitude smaller than the values obtained by the membrane method. This may be due to the presence of an additional flow through the membrane caused by the pressure gradient across the membrane in membrane methods.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1134/s0036024417010319", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1327871", 
        "issn": [
          "0036-0244", 
          "0044-4537"
        ], 
        "name": "Russian Journal of Physical Chemistry A", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "91"
      }
    ], 
    "name": "Chromatographic determination of the diffusion coefficients of light hydrocarbons in polymers", 
    "pagination": "175-181", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "c0b70f6a50ee79ff4a15c1946879b3049719f72a59e0fc3f9c7c30d9b256772d"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1134/s0036024417010319"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1083759026"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1134/s0036024417010319", 
      "https://app.dimensions.ai/details/publication/pub.1083759026"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T13:06", 
    "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/v90/0000000367_0000000367/records_88217_00000001.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://link.springer.com/10.1134%2FS0036024417010319"
  }
]
 

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.10.1134/s0036024417010319'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1134/s0036024417010319'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1134/s0036024417010319'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1134/s0036024417010319'


 

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

132 TRIPLES      21 PREDICATES      39 URIs      19 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1134/s0036024417010319 schema:about anzsrc-for:09
2 anzsrc-for:0904
3 schema:author N8881ff74f7444d03a65fffcf694774c7
4 schema:citation sg:pub.10.1134/s0036024409040268
5 https://doi.org/10.1002/pc.23432
6 https://doi.org/10.1016/j.chroma.2015.01.053
7 https://doi.org/10.1016/j.memsci.2006.05.030
8 https://doi.org/10.1016/j.memsci.2013.11.002
9 https://doi.org/10.1016/j.memsci.2014.09.043
10 https://doi.org/10.1021/ac60075a013
11 https://doi.org/10.1021/acs.macromol.5b02087
12 https://doi.org/10.1021/ma100656e
13 https://doi.org/10.1039/tf9656101637
14 https://doi.org/10.1039/tf9666202341
15 https://doi.org/10.1042/bj0500679
16 schema:datePublished 2017-01
17 schema:datePublishedReg 2017-01-01
18 schema:description Gas-chromatographic determination of the diffusion coefficients that allows for the compressibility of the mobile phase has been suggested. The diffusion coefficients were determined for light hydrocarbons С1–С4 in four polymers with a high free volume, which are candidates for use as gas-separating membranes. The diffusion coefficients calculated from chromatographic data were shown to be one or two orders of magnitude smaller than the values obtained by the membrane method. This may be due to the presence of an additional flow through the membrane caused by the pressure gradient across the membrane in membrane methods.
19 schema:genre research_article
20 schema:inLanguage en
21 schema:isAccessibleForFree false
22 schema:isPartOf N5908393ac22f4866bcee4ed264f4b64e
23 N808705f4f586442c8837d36ea746258c
24 sg:journal.1327871
25 schema:name Chromatographic determination of the diffusion coefficients of light hydrocarbons in polymers
26 schema:pagination 175-181
27 schema:productId N322242f7ce64424dab27dc6dc2cd7849
28 N57ed23efeb87435b95f21de7839ea7b8
29 Nec40a0a036eb4ec1ac5c956db7bd705b
30 schema:sameAs https://app.dimensions.ai/details/publication/pub.1083759026
31 https://doi.org/10.1134/s0036024417010319
32 schema:sdDatePublished 2019-04-11T13:06
33 schema:sdLicense https://scigraph.springernature.com/explorer/license/
34 schema:sdPublisher N22c6ce2939d1485792011284202f2395
35 schema:url https://link.springer.com/10.1134%2FS0036024417010319
36 sgo:license sg:explorer/license/
37 sgo:sdDataset articles
38 rdf:type schema:ScholarlyArticle
39 N22c6ce2939d1485792011284202f2395 schema:name Springer Nature - SN SciGraph project
40 rdf:type schema:Organization
41 N322242f7ce64424dab27dc6dc2cd7849 schema:name readcube_id
42 schema:value c0b70f6a50ee79ff4a15c1946879b3049719f72a59e0fc3f9c7c30d9b256772d
43 rdf:type schema:PropertyValue
44 N413f635038d54523943d6ee3f4dd9982 rdf:first sg:person.0761776377.67
45 rdf:rest Nc0a150cfded54b1a98a52bc3b0ff1ab3
46 N57ed23efeb87435b95f21de7839ea7b8 schema:name doi
47 schema:value 10.1134/s0036024417010319
48 rdf:type schema:PropertyValue
49 N5908393ac22f4866bcee4ed264f4b64e schema:issueNumber 1
50 rdf:type schema:PublicationIssue
51 N808705f4f586442c8837d36ea746258c schema:volumeNumber 91
52 rdf:type schema:PublicationVolume
53 N8881ff74f7444d03a65fffcf694774c7 rdf:first sg:person.01277702211.03
54 rdf:rest N413f635038d54523943d6ee3f4dd9982
55 N97b1cc3b92d1401bbee1fd370e5ff6fc schema:affiliation https://www.grid.ac/institutes/grid.423490.8
56 schema:familyName Bermeshev
57 schema:givenName M. V.
58 rdf:type schema:Person
59 Na934c90528a64e0e811344d9810f58e1 rdf:first sg:person.010657112101.27
60 rdf:rest Nf82f96fb88554c92922550d9ae30819f
61 Nc0a150cfded54b1a98a52bc3b0ff1ab3 rdf:first sg:person.012346031703.46
62 rdf:rest Nd31bec6a42c84fde9fc15e9eaafb836d
63 Nd31bec6a42c84fde9fc15e9eaafb836d rdf:first N97b1cc3b92d1401bbee1fd370e5ff6fc
64 rdf:rest Na934c90528a64e0e811344d9810f58e1
65 Nec40a0a036eb4ec1ac5c956db7bd705b schema:name dimensions_id
66 schema:value pub.1083759026
67 rdf:type schema:PropertyValue
68 Nf82f96fb88554c92922550d9ae30819f rdf:first sg:person.01240135562.44
69 rdf:rest rdf:nil
70 anzsrc-for:09 schema:inDefinedTermSet anzsrc-for:
71 schema:name Engineering
72 rdf:type schema:DefinedTerm
73 anzsrc-for:0904 schema:inDefinedTermSet anzsrc-for:
74 schema:name Chemical Engineering
75 rdf:type schema:DefinedTerm
76 sg:journal.1327871 schema:issn 0036-0244
77 0044-4537
78 schema:name Russian Journal of Physical Chemistry A
79 rdf:type schema:Periodical
80 sg:person.010657112101.27 schema:affiliation https://www.grid.ac/institutes/grid.423490.8
81 schema:familyName Kanat’eva
82 schema:givenName A. Yu.
83 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010657112101.27
84 rdf:type schema:Person
85 sg:person.012346031703.46 schema:affiliation https://www.grid.ac/institutes/grid.423490.8
86 schema:familyName Chapala
87 schema:givenName P. P.
88 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012346031703.46
89 rdf:type schema:Person
90 sg:person.01240135562.44 schema:affiliation https://www.grid.ac/institutes/grid.423490.8
91 schema:familyName Kurganov
92 schema:givenName A. A.
93 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01240135562.44
94 rdf:type schema:Person
95 sg:person.01277702211.03 schema:affiliation https://www.grid.ac/institutes/grid.423490.8
96 schema:familyName Yakubenko
97 schema:givenName E. E.
98 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01277702211.03
99 rdf:type schema:Person
100 sg:person.0761776377.67 schema:affiliation https://www.grid.ac/institutes/grid.423490.8
101 schema:familyName Korolev
102 schema:givenName A. A.
103 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0761776377.67
104 rdf:type schema:Person
105 sg:pub.10.1134/s0036024409040268 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015637620
106 https://doi.org/10.1134/s0036024409040268
107 rdf:type schema:CreativeWork
108 https://doi.org/10.1002/pc.23432 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036467039
109 rdf:type schema:CreativeWork
110 https://doi.org/10.1016/j.chroma.2015.01.053 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020540712
111 rdf:type schema:CreativeWork
112 https://doi.org/10.1016/j.memsci.2006.05.030 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003042793
113 rdf:type schema:CreativeWork
114 https://doi.org/10.1016/j.memsci.2013.11.002 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042493151
115 rdf:type schema:CreativeWork
116 https://doi.org/10.1016/j.memsci.2014.09.043 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038392058
117 rdf:type schema:CreativeWork
118 https://doi.org/10.1021/ac60075a013 schema:sameAs https://app.dimensions.ai/details/publication/pub.1055026868
119 rdf:type schema:CreativeWork
120 https://doi.org/10.1021/acs.macromol.5b02087 schema:sameAs https://app.dimensions.ai/details/publication/pub.1055118928
121 rdf:type schema:CreativeWork
122 https://doi.org/10.1021/ma100656e schema:sameAs https://app.dimensions.ai/details/publication/pub.1056194085
123 rdf:type schema:CreativeWork
124 https://doi.org/10.1039/tf9656101637 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049025453
125 rdf:type schema:CreativeWork
126 https://doi.org/10.1039/tf9666202341 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050735805
127 rdf:type schema:CreativeWork
128 https://doi.org/10.1042/bj0500679 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051155949
129 rdf:type schema:CreativeWork
130 https://www.grid.ac/institutes/grid.423490.8 schema:alternateName A.V.Topchiev Institute of Petrochemical Synthesis
131 schema:name Topchiev Institute of Petrochemical Synthesis, Russian Academy of Sciences, Moscow, Russia
132 rdf:type schema:Organization
 




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


...