Effect of the carrier gas pressure on the dynamic and separation characteristics of divinylbenzene-based monolithic capillary columns for gas chromatography View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2007-03

AUTHORS

A. V. Kozin, A. A. Korolev, V. E. Shiryaeva, T. P. Popova, A. A. Kurganov

ABSTRACT

The efficiency and dynamic characteristics of divinylbenzene-based monolithic capillary columns for gas chromatography were analyzed using a test mixture composed of five light hydrocarbons. The chromatographic properties of these columns were evaluated within the framework of two varieties of the van Deemter equation, the classical one and that proposed by Giddings (with consideration given to the pressure drop across the column). An analysis of the van Deemter curves demonstrated that the main contribution to peak smearing comes from the diffusion processes in the mobile phase. The contribution from the resistance to mass transfer between the mobile and stationary phases is less important. Negative values obtained for A in the van Deemter equation and for Cs in the Giddings model, parameters that characterize the stationary phase structure and mass transfer kinetics in the stationary phase, have no physical meaning, a result calling for further studies of this type of monolithic capillary columns since the classical theory supposed these parameters to be strictly positive. Under optimal conditions, the HETP of the monolithic columns was found to be 3 to 4 times smaller than that typical of open capillary columns of the same diameter. More... »

PAGES

433-440

References to SciGraph publications

  • 1971-03. Foam filled columns in gas chromatography in CHROMATOGRAPHIA
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1134/s0036024407030259

    DOI

    http://dx.doi.org/10.1134/s0036024407030259

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1014044385


    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/2008/0301", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Analytical Chemistry", 
            "type": "DefinedTerm"
          }, 
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/03", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Chemical Sciences", 
            "type": "DefinedTerm"
          }
        ], 
        "author": [
          {
            "affiliation": {
              "alternateName": "Russian Academy of Sciences", 
              "id": "https://www.grid.ac/institutes/grid.4886.2", 
              "name": [
                "Topchiev Institute of Petrochemical Synthesis, Russian Academy of Sciences, Leninskii pr. 29, 119991, Moscow, Russia"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Kozin", 
            "givenName": "A. V.", 
            "id": "sg:person.014527423015.34", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014527423015.34"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Russian Academy of Sciences", 
              "id": "https://www.grid.ac/institutes/grid.4886.2", 
              "name": [
                "Topchiev Institute of Petrochemical Synthesis, Russian Academy of Sciences, Leninskii pr. 29, 119991, 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": "Russian Academy of Sciences", 
              "id": "https://www.grid.ac/institutes/grid.4886.2", 
              "name": [
                "Topchiev Institute of Petrochemical Synthesis, Russian Academy of Sciences, Leninskii pr. 29, 119991, Moscow, Russia"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Shiryaeva", 
            "givenName": "V. E.", 
            "id": "sg:person.016163553457.07", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016163553457.07"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Russian Academy of Sciences", 
              "id": "https://www.grid.ac/institutes/grid.4886.2", 
              "name": [
                "Topchiev Institute of Petrochemical Synthesis, Russian Academy of Sciences, Leninskii pr. 29, 119991, Moscow, Russia"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Popova", 
            "givenName": "T. P.", 
            "id": "sg:person.01123707162.15", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01123707162.15"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Russian Academy of Sciences", 
              "id": "https://www.grid.ac/institutes/grid.4886.2", 
              "name": [
                "Topchiev Institute of Petrochemical Synthesis, Russian Academy of Sciences, Leninskii pr. 29, 119991, 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/s0021-9673(99)00227-7", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1007717736"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s0021-9673(02)00133-4", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1010655853"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s0021-9673(01)01227-4", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1014794297"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s0021-9673(00)93765-8", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1020359741"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/bf02311199", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1040664144", 
              "https://doi.org/10.1007/bf02311199"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s0021-9673(00)00152-7", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1041695886"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s0021-9673(97)00377-4", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1051537768"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1021/ac60163a043", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1055039375"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/chromsci/8.7.386", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1059466411"
            ], 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2007-03", 
        "datePublishedReg": "2007-03-01", 
        "description": "The efficiency and dynamic characteristics of divinylbenzene-based monolithic capillary columns for gas chromatography were analyzed using a test mixture composed of five light hydrocarbons. The chromatographic properties of these columns were evaluated within the framework of two varieties of the van Deemter equation, the classical one and that proposed by Giddings (with consideration given to the pressure drop across the column). An analysis of the van Deemter curves demonstrated that the main contribution to peak smearing comes from the diffusion processes in the mobile phase. The contribution from the resistance to mass transfer between the mobile and stationary phases is less important. Negative values obtained for A in the van Deemter equation and for Cs in the Giddings model, parameters that characterize the stationary phase structure and mass transfer kinetics in the stationary phase, have no physical meaning, a result calling for further studies of this type of monolithic capillary columns since the classical theory supposed these parameters to be strictly positive. Under optimal conditions, the HETP of the monolithic columns was found to be 3 to 4 times smaller than that typical of open capillary columns of the same diameter.", 
        "genre": "research_article", 
        "id": "sg:pub.10.1134/s0036024407030259", 
        "inLanguage": [
          "en"
        ], 
        "isAccessibleForFree": false, 
        "isPartOf": [
          {
            "id": "sg:journal.1327871", 
            "issn": [
              "0036-0244", 
              "0044-4537"
            ], 
            "name": "Russian Journal of Physical Chemistry A", 
            "type": "Periodical"
          }, 
          {
            "issueNumber": "3", 
            "type": "PublicationIssue"
          }, 
          {
            "type": "PublicationVolume", 
            "volumeNumber": "81"
          }
        ], 
        "name": "Effect of the carrier gas pressure on the dynamic and separation characteristics of divinylbenzene-based monolithic capillary columns for gas chromatography", 
        "pagination": "433-440", 
        "productId": [
          {
            "name": "readcube_id", 
            "type": "PropertyValue", 
            "value": [
              "42e76fde66021c64f5234a148a82c4c17d075dd683b3812501724048c9281816"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1134/s0036024407030259"
            ]
          }, 
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1014044385"
            ]
          }
        ], 
        "sameAs": [
          "https://doi.org/10.1134/s0036024407030259", 
          "https://app.dimensions.ai/details/publication/pub.1014044385"
        ], 
        "sdDataset": "articles", 
        "sdDatePublished": "2019-04-11T01:05", 
        "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_8697_00000504.jsonl", 
        "type": "ScholarlyArticle", 
        "url": "http://link.springer.com/10.1134/S0036024407030259"
      }
    ]
     

    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/s0036024407030259'

    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/s0036024407030259'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1134/s0036024407030259'

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

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1134/s0036024407030259'


     

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

    117 TRIPLES      21 PREDICATES      36 URIs      19 LITERALS      7 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1134/s0036024407030259 schema:about anzsrc-for:03
    2 anzsrc-for:0301
    3 schema:author Ncc55a1d470d74d7f808a6b2eef0cde22
    4 schema:citation sg:pub.10.1007/bf02311199
    5 https://doi.org/10.1016/s0021-9673(00)00152-7
    6 https://doi.org/10.1016/s0021-9673(00)93765-8
    7 https://doi.org/10.1016/s0021-9673(01)01227-4
    8 https://doi.org/10.1016/s0021-9673(02)00133-4
    9 https://doi.org/10.1016/s0021-9673(97)00377-4
    10 https://doi.org/10.1016/s0021-9673(99)00227-7
    11 https://doi.org/10.1021/ac60163a043
    12 https://doi.org/10.1093/chromsci/8.7.386
    13 schema:datePublished 2007-03
    14 schema:datePublishedReg 2007-03-01
    15 schema:description The efficiency and dynamic characteristics of divinylbenzene-based monolithic capillary columns for gas chromatography were analyzed using a test mixture composed of five light hydrocarbons. The chromatographic properties of these columns were evaluated within the framework of two varieties of the van Deemter equation, the classical one and that proposed by Giddings (with consideration given to the pressure drop across the column). An analysis of the van Deemter curves demonstrated that the main contribution to peak smearing comes from the diffusion processes in the mobile phase. The contribution from the resistance to mass transfer between the mobile and stationary phases is less important. Negative values obtained for A in the van Deemter equation and for Cs in the Giddings model, parameters that characterize the stationary phase structure and mass transfer kinetics in the stationary phase, have no physical meaning, a result calling for further studies of this type of monolithic capillary columns since the classical theory supposed these parameters to be strictly positive. Under optimal conditions, the HETP of the monolithic columns was found to be 3 to 4 times smaller than that typical of open capillary columns of the same diameter.
    16 schema:genre research_article
    17 schema:inLanguage en
    18 schema:isAccessibleForFree false
    19 schema:isPartOf Na53eb69f3a824e94952de7be2a546a46
    20 Nffb1d4be1d7f47f8ab71bfea3cfecfdd
    21 sg:journal.1327871
    22 schema:name Effect of the carrier gas pressure on the dynamic and separation characteristics of divinylbenzene-based monolithic capillary columns for gas chromatography
    23 schema:pagination 433-440
    24 schema:productId N33e3968a784b41658793eccd373622dd
    25 N5be92821c33d4599aa524239dfd8be88
    26 N905ef08fe3024259b820f3f68b196ee3
    27 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014044385
    28 https://doi.org/10.1134/s0036024407030259
    29 schema:sdDatePublished 2019-04-11T01:05
    30 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    31 schema:sdPublisher Nb5369962e19248fda3e83e74dbc41597
    32 schema:url http://link.springer.com/10.1134/S0036024407030259
    33 sgo:license sg:explorer/license/
    34 sgo:sdDataset articles
    35 rdf:type schema:ScholarlyArticle
    36 N324588b7667c4dacaf9fc29e4c67b84f rdf:first sg:person.01123707162.15
    37 rdf:rest Ne8bdad277825442090b86a25fe99d9b7
    38 N33e3968a784b41658793eccd373622dd schema:name doi
    39 schema:value 10.1134/s0036024407030259
    40 rdf:type schema:PropertyValue
    41 N3799487683db49f2891b2b791d7c681d rdf:first sg:person.0761776377.67
    42 rdf:rest N6c95c79d61a34bbfbfad65293d5f88e6
    43 N5be92821c33d4599aa524239dfd8be88 schema:name dimensions_id
    44 schema:value pub.1014044385
    45 rdf:type schema:PropertyValue
    46 N6c95c79d61a34bbfbfad65293d5f88e6 rdf:first sg:person.016163553457.07
    47 rdf:rest N324588b7667c4dacaf9fc29e4c67b84f
    48 N905ef08fe3024259b820f3f68b196ee3 schema:name readcube_id
    49 schema:value 42e76fde66021c64f5234a148a82c4c17d075dd683b3812501724048c9281816
    50 rdf:type schema:PropertyValue
    51 Na53eb69f3a824e94952de7be2a546a46 schema:volumeNumber 81
    52 rdf:type schema:PublicationVolume
    53 Nb5369962e19248fda3e83e74dbc41597 schema:name Springer Nature - SN SciGraph project
    54 rdf:type schema:Organization
    55 Ncc55a1d470d74d7f808a6b2eef0cde22 rdf:first sg:person.014527423015.34
    56 rdf:rest N3799487683db49f2891b2b791d7c681d
    57 Ne8bdad277825442090b86a25fe99d9b7 rdf:first sg:person.01240135562.44
    58 rdf:rest rdf:nil
    59 Nffb1d4be1d7f47f8ab71bfea3cfecfdd schema:issueNumber 3
    60 rdf:type schema:PublicationIssue
    61 anzsrc-for:03 schema:inDefinedTermSet anzsrc-for:
    62 schema:name Chemical Sciences
    63 rdf:type schema:DefinedTerm
    64 anzsrc-for:0301 schema:inDefinedTermSet anzsrc-for:
    65 schema:name Analytical Chemistry
    66 rdf:type schema:DefinedTerm
    67 sg:journal.1327871 schema:issn 0036-0244
    68 0044-4537
    69 schema:name Russian Journal of Physical Chemistry A
    70 rdf:type schema:Periodical
    71 sg:person.01123707162.15 schema:affiliation https://www.grid.ac/institutes/grid.4886.2
    72 schema:familyName Popova
    73 schema:givenName T. P.
    74 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01123707162.15
    75 rdf:type schema:Person
    76 sg:person.01240135562.44 schema:affiliation https://www.grid.ac/institutes/grid.4886.2
    77 schema:familyName Kurganov
    78 schema:givenName A. A.
    79 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01240135562.44
    80 rdf:type schema:Person
    81 sg:person.014527423015.34 schema:affiliation https://www.grid.ac/institutes/grid.4886.2
    82 schema:familyName Kozin
    83 schema:givenName A. V.
    84 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014527423015.34
    85 rdf:type schema:Person
    86 sg:person.016163553457.07 schema:affiliation https://www.grid.ac/institutes/grid.4886.2
    87 schema:familyName Shiryaeva
    88 schema:givenName V. E.
    89 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016163553457.07
    90 rdf:type schema:Person
    91 sg:person.0761776377.67 schema:affiliation https://www.grid.ac/institutes/grid.4886.2
    92 schema:familyName Korolev
    93 schema:givenName A. A.
    94 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0761776377.67
    95 rdf:type schema:Person
    96 sg:pub.10.1007/bf02311199 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040664144
    97 https://doi.org/10.1007/bf02311199
    98 rdf:type schema:CreativeWork
    99 https://doi.org/10.1016/s0021-9673(00)00152-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041695886
    100 rdf:type schema:CreativeWork
    101 https://doi.org/10.1016/s0021-9673(00)93765-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020359741
    102 rdf:type schema:CreativeWork
    103 https://doi.org/10.1016/s0021-9673(01)01227-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014794297
    104 rdf:type schema:CreativeWork
    105 https://doi.org/10.1016/s0021-9673(02)00133-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010655853
    106 rdf:type schema:CreativeWork
    107 https://doi.org/10.1016/s0021-9673(97)00377-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051537768
    108 rdf:type schema:CreativeWork
    109 https://doi.org/10.1016/s0021-9673(99)00227-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007717736
    110 rdf:type schema:CreativeWork
    111 https://doi.org/10.1021/ac60163a043 schema:sameAs https://app.dimensions.ai/details/publication/pub.1055039375
    112 rdf:type schema:CreativeWork
    113 https://doi.org/10.1093/chromsci/8.7.386 schema:sameAs https://app.dimensions.ai/details/publication/pub.1059466411
    114 rdf:type schema:CreativeWork
    115 https://www.grid.ac/institutes/grid.4886.2 schema:alternateName Russian Academy of Sciences
    116 schema:name Topchiev Institute of Petrochemical Synthesis, Russian Academy of Sciences, Leninskii pr. 29, 119991, Moscow, Russia
    117 rdf:type schema:Organization
     




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


    ...