Adsorption of SO2 molecules on Fe-doped carbon nanotubes: the first principles study View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-02

AUTHORS

Libao An, Xiaotong Jia, Yang Liu

ABSTRACT

In this paper, the first-principles method has been employed to study the adsorption behavior of SO2 molecules on pristine carbon nanotubes (CNTs) and Fe-doped CNTs with or without the existence of vacancy defects. Through the analysis of geometric structure, adsorption energy, charge transfer, and electron density, our calculation illustrates that the adsorption of SO2 molecules is only a weak physical adsorption on both pristine CNTs and vacancy-defected CNTs. After doping with Fe, however, a much stable chemical adsorption is formed between SO2 and CNTs, where the adsorption distance decreases by a maximum of 44.8%, and the adsorption energy and charge transfer increase by a maximum of 1513.3% and 373.9%, respectively. Calculations of front orbit and density of states reveal that Fe-doping narrows the band gap and increases the electrical conductivity of the CNTs. The density of states of Fe-doped CNTs and SO2 molecules are clearly reinforced at the Fermi level, implicating that there is stronger coupling between Fe atoms and SO2 molecules and this enhances the adsorption of SO2 molecules on these CNTs. The study provides useful guidance on how to improve the interactions between air pollutant SO2 molecules and CNTs and illustrates that Fe-doped CNTs could be potentially applied as a next-generation SO2 gas sensor and collector. More... »

PAGES

217-224

Journal

TITLE

Adsorption

ISSUE

2

VOLUME

25

Author Affiliations

From Grant

  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s10450-019-00026-4

    DOI

    http://dx.doi.org/10.1007/s10450-019-00026-4

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1111911916


    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/2008/0306", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Physical Chemistry (incl. Structural)", 
            "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": "Hebei United University", 
              "id": "https://www.grid.ac/institutes/grid.440734.0", 
              "name": [
                "College of Mechanical Engineering, North China University of Science and Technology, 21 Bohai Road, Caofeidian District, 063210, Tangshan, Hebei, China"
              ], 
              "type": "Organization"
            }, 
            "familyName": "An", 
            "givenName": "Libao", 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Hebei United University", 
              "id": "https://www.grid.ac/institutes/grid.440734.0", 
              "name": [
                "College of Mechanical Engineering, North China University of Science and Technology, 21 Bohai Road, Caofeidian District, 063210, Tangshan, Hebei, China"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Jia", 
            "givenName": "Xiaotong", 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Hebei United University", 
              "id": "https://www.grid.ac/institutes/grid.440734.0", 
              "name": [
                "College of Mechanical Engineering, North China University of Science and Technology, 21 Bohai Road, Caofeidian District, 063210, Tangshan, Hebei, China"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Liu", 
            "givenName": "Yang", 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "https://doi.org/10.1016/j.theochem.2006.11.012", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1001712065"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.molliq.2015.06.029", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1003805414"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1126/science.287.5453.622", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1006186722"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.jallcom.2015.06.130", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1008532782"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.snb.2016.07.039", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1010293993"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.apcatb.2013.09.016", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1010551928"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.jcp.2013.04.020", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1011175101"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.apsusc.2013.11.003", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1011484648"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.5194/acp-16-1479-2016", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1012071934"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.apsusc.2015.12.177", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1012515805"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.synthmet.2016.09.017", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1014593669"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.cplett.2008.02.027", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1018634956"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.apsusc.2015.05.088", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1023614772"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.matchemphys.2016.11.006", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1031259845"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s10853-015-9007-z", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1040510762", 
              "https://doi.org/10.1007/s10853-015-9007-z"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1103/physrevb.85.045433", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1047691741"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1103/physrevb.85.045433", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1047691741"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.spmi.2016.08.049", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1047998960"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.commatsci.2013.09.046", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1048072096"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s10450-007-9002-z", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1048482520", 
              "https://doi.org/10.1007/s10450-007-9002-z"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s10450-007-9002-z", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1048482520", 
              "https://doi.org/10.1007/s10450-007-9002-z"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1039/c5ra00834d", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1049927440"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1021/acs.jctc.5b00535", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1055098664"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1021/ie000976k", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1055594780"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1021/ie000976k", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1055594780"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1021/ja0447053", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1055836334"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1021/ja0447053", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1055836334"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1021/jp076965n", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1056074591"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1021/jp076965n", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1056074591"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1021/jp111389v", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1056080923"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1021/jp111389v", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1056080923"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1021/jp808264d", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1056111203"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1021/jp808264d", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1056111203"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1063/1.3255016", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1057925590"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1103/physrevb.46.6671", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1060564150"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1103/physrevb.46.6671", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1060564150"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1103/physrevb.73.205104", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1060617606"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1103/physrevb.73.205104", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1060617606"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1103/physrevb.81.165406", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1060632440"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1103/physrevb.81.165406", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1060632440"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.apcatb.2017.02.020", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1083695455"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s10450-017-9901-6", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1091081803", 
              "https://doi.org/10.1007/s10450-017-9901-6"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s10450-017-9901-6", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1091081803", 
              "https://doi.org/10.1007/s10450-017-9901-6"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.apsusc.2017.10.166", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1092597048"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.cplett.2017.11.017", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1092667396"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1080/00150193.2017.1388763", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1099645528"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.apsusc.2018.03.108", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1101523475"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.commatsci.2018.03.067", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1101848001"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.commatsci.2018.03.067", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1101848001"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s10450-018-9964-z", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1106020422", 
              "https://doi.org/10.1007/s10450-018-9964-z"
            ], 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2019-02", 
        "datePublishedReg": "2019-02-01", 
        "description": "In this paper, the first-principles method has been employed to study the adsorption behavior of SO2 molecules on pristine carbon nanotubes (CNTs) and Fe-doped CNTs with or without the existence of vacancy defects. Through the analysis of geometric structure, adsorption energy, charge transfer, and electron density, our calculation illustrates that the adsorption of SO2 molecules is only a weak physical adsorption on both pristine CNTs and vacancy-defected CNTs. After doping with Fe, however, a much stable chemical adsorption is formed between SO2 and CNTs, where the adsorption distance decreases by a maximum of 44.8%, and the adsorption energy and charge transfer increase by a maximum of 1513.3% and 373.9%, respectively. Calculations of front orbit and density of states reveal that Fe-doping narrows the band gap and increases the electrical conductivity of the CNTs. The density of states of Fe-doped CNTs and SO2 molecules are clearly reinforced at the Fermi level, implicating that there is stronger coupling between Fe atoms and SO2 molecules and this enhances the adsorption of SO2 molecules on these CNTs. The study provides useful guidance on how to improve the interactions between air pollutant SO2 molecules and CNTs and illustrates that Fe-doped CNTs could be potentially applied as a next-generation SO2 gas sensor and collector.", 
        "genre": "research_article", 
        "id": "sg:pub.10.1007/s10450-019-00026-4", 
        "inLanguage": [
          "en"
        ], 
        "isAccessibleForFree": false, 
        "isFundedItemOf": [
          {
            "id": "sg:grant.6984049", 
            "type": "MonetaryGrant"
          }
        ], 
        "isPartOf": [
          {
            "id": "sg:journal.1134428", 
            "issn": [
              "0929-5607", 
              "1572-8757"
            ], 
            "name": "Adsorption", 
            "type": "Periodical"
          }, 
          {
            "issueNumber": "2", 
            "type": "PublicationIssue"
          }, 
          {
            "type": "PublicationVolume", 
            "volumeNumber": "25"
          }
        ], 
        "name": "Adsorption of SO2 molecules on Fe-doped carbon nanotubes: the first principles study", 
        "pagination": "217-224", 
        "productId": [
          {
            "name": "readcube_id", 
            "type": "PropertyValue", 
            "value": [
              "6c93f99826ea50efcf8d78e8d46fa719edb3469019aa57e17bdafffa80415bf9"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1007/s10450-019-00026-4"
            ]
          }, 
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1111911916"
            ]
          }
        ], 
        "sameAs": [
          "https://doi.org/10.1007/s10450-019-00026-4", 
          "https://app.dimensions.ai/details/publication/pub.1111911916"
        ], 
        "sdDataset": "articles", 
        "sdDatePublished": "2019-04-11T10:37", 
        "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/v90/0000000349_0000000349/records_113673_00000005.jsonl", 
        "type": "ScholarlyArticle", 
        "url": "https://link.springer.com/10.1007%2Fs10450-019-00026-4"
      }
    ]
     

    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/s10450-019-00026-4'

    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/s10450-019-00026-4'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s10450-019-00026-4'

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

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s10450-019-00026-4'


     

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

    192 TRIPLES      21 PREDICATES      65 URIs      19 LITERALS      7 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1007/s10450-019-00026-4 schema:about anzsrc-for:03
    2 anzsrc-for:0306
    3 schema:author Ndaa1cf6e8570424481f03974294c091d
    4 schema:citation sg:pub.10.1007/s10450-007-9002-z
    5 sg:pub.10.1007/s10450-017-9901-6
    6 sg:pub.10.1007/s10450-018-9964-z
    7 sg:pub.10.1007/s10853-015-9007-z
    8 https://doi.org/10.1016/j.apcatb.2013.09.016
    9 https://doi.org/10.1016/j.apcatb.2017.02.020
    10 https://doi.org/10.1016/j.apsusc.2013.11.003
    11 https://doi.org/10.1016/j.apsusc.2015.05.088
    12 https://doi.org/10.1016/j.apsusc.2015.12.177
    13 https://doi.org/10.1016/j.apsusc.2017.10.166
    14 https://doi.org/10.1016/j.apsusc.2018.03.108
    15 https://doi.org/10.1016/j.commatsci.2013.09.046
    16 https://doi.org/10.1016/j.commatsci.2018.03.067
    17 https://doi.org/10.1016/j.cplett.2008.02.027
    18 https://doi.org/10.1016/j.cplett.2017.11.017
    19 https://doi.org/10.1016/j.jallcom.2015.06.130
    20 https://doi.org/10.1016/j.jcp.2013.04.020
    21 https://doi.org/10.1016/j.matchemphys.2016.11.006
    22 https://doi.org/10.1016/j.molliq.2015.06.029
    23 https://doi.org/10.1016/j.snb.2016.07.039
    24 https://doi.org/10.1016/j.spmi.2016.08.049
    25 https://doi.org/10.1016/j.synthmet.2016.09.017
    26 https://doi.org/10.1016/j.theochem.2006.11.012
    27 https://doi.org/10.1021/acs.jctc.5b00535
    28 https://doi.org/10.1021/ie000976k
    29 https://doi.org/10.1021/ja0447053
    30 https://doi.org/10.1021/jp076965n
    31 https://doi.org/10.1021/jp111389v
    32 https://doi.org/10.1021/jp808264d
    33 https://doi.org/10.1039/c5ra00834d
    34 https://doi.org/10.1063/1.3255016
    35 https://doi.org/10.1080/00150193.2017.1388763
    36 https://doi.org/10.1103/physrevb.46.6671
    37 https://doi.org/10.1103/physrevb.73.205104
    38 https://doi.org/10.1103/physrevb.81.165406
    39 https://doi.org/10.1103/physrevb.85.045433
    40 https://doi.org/10.1126/science.287.5453.622
    41 https://doi.org/10.5194/acp-16-1479-2016
    42 schema:datePublished 2019-02
    43 schema:datePublishedReg 2019-02-01
    44 schema:description In this paper, the first-principles method has been employed to study the adsorption behavior of SO2 molecules on pristine carbon nanotubes (CNTs) and Fe-doped CNTs with or without the existence of vacancy defects. Through the analysis of geometric structure, adsorption energy, charge transfer, and electron density, our calculation illustrates that the adsorption of SO2 molecules is only a weak physical adsorption on both pristine CNTs and vacancy-defected CNTs. After doping with Fe, however, a much stable chemical adsorption is formed between SO2 and CNTs, where the adsorption distance decreases by a maximum of 44.8%, and the adsorption energy and charge transfer increase by a maximum of 1513.3% and 373.9%, respectively. Calculations of front orbit and density of states reveal that Fe-doping narrows the band gap and increases the electrical conductivity of the CNTs. The density of states of Fe-doped CNTs and SO2 molecules are clearly reinforced at the Fermi level, implicating that there is stronger coupling between Fe atoms and SO2 molecules and this enhances the adsorption of SO2 molecules on these CNTs. The study provides useful guidance on how to improve the interactions between air pollutant SO2 molecules and CNTs and illustrates that Fe-doped CNTs could be potentially applied as a next-generation SO2 gas sensor and collector.
    45 schema:genre research_article
    46 schema:inLanguage en
    47 schema:isAccessibleForFree false
    48 schema:isPartOf N4e1cdcfb9c04466b9b5a82c4ad003901
    49 Nddeacb52d4af4afeba6c3796826b23b8
    50 sg:journal.1134428
    51 schema:name Adsorption of SO2 molecules on Fe-doped carbon nanotubes: the first principles study
    52 schema:pagination 217-224
    53 schema:productId N8256347f4f6f4e5e9f7f929d8c25b8a7
    54 N9fb6c9bb72de49ceb797790d74e9ded6
    55 Nb0b818ecdc1d4984a249289cedebcec3
    56 schema:sameAs https://app.dimensions.ai/details/publication/pub.1111911916
    57 https://doi.org/10.1007/s10450-019-00026-4
    58 schema:sdDatePublished 2019-04-11T10:37
    59 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    60 schema:sdPublisher Nf9119187cbcf41aeabeef3b8c6753753
    61 schema:url https://link.springer.com/10.1007%2Fs10450-019-00026-4
    62 sgo:license sg:explorer/license/
    63 sgo:sdDataset articles
    64 rdf:type schema:ScholarlyArticle
    65 N0a1cc7dbdcc84bac8a20eea120b52fec schema:affiliation https://www.grid.ac/institutes/grid.440734.0
    66 schema:familyName An
    67 schema:givenName Libao
    68 rdf:type schema:Person
    69 N1226ac8a16be4f8e80d5070dd45dd9cc rdf:first N606b9a5bf56c468db337894cad5e4d42
    70 rdf:rest Nc71a7ecfc3664cdebf40307cc0f6d235
    71 N4e1cdcfb9c04466b9b5a82c4ad003901 schema:issueNumber 2
    72 rdf:type schema:PublicationIssue
    73 N606b9a5bf56c468db337894cad5e4d42 schema:affiliation https://www.grid.ac/institutes/grid.440734.0
    74 schema:familyName Jia
    75 schema:givenName Xiaotong
    76 rdf:type schema:Person
    77 N79861e4c40434d6b9891cfaab95b335a schema:affiliation https://www.grid.ac/institutes/grid.440734.0
    78 schema:familyName Liu
    79 schema:givenName Yang
    80 rdf:type schema:Person
    81 N8256347f4f6f4e5e9f7f929d8c25b8a7 schema:name doi
    82 schema:value 10.1007/s10450-019-00026-4
    83 rdf:type schema:PropertyValue
    84 N9fb6c9bb72de49ceb797790d74e9ded6 schema:name dimensions_id
    85 schema:value pub.1111911916
    86 rdf:type schema:PropertyValue
    87 Nb0b818ecdc1d4984a249289cedebcec3 schema:name readcube_id
    88 schema:value 6c93f99826ea50efcf8d78e8d46fa719edb3469019aa57e17bdafffa80415bf9
    89 rdf:type schema:PropertyValue
    90 Nc71a7ecfc3664cdebf40307cc0f6d235 rdf:first N79861e4c40434d6b9891cfaab95b335a
    91 rdf:rest rdf:nil
    92 Ndaa1cf6e8570424481f03974294c091d rdf:first N0a1cc7dbdcc84bac8a20eea120b52fec
    93 rdf:rest N1226ac8a16be4f8e80d5070dd45dd9cc
    94 Nddeacb52d4af4afeba6c3796826b23b8 schema:volumeNumber 25
    95 rdf:type schema:PublicationVolume
    96 Nf9119187cbcf41aeabeef3b8c6753753 schema:name Springer Nature - SN SciGraph project
    97 rdf:type schema:Organization
    98 anzsrc-for:03 schema:inDefinedTermSet anzsrc-for:
    99 schema:name Chemical Sciences
    100 rdf:type schema:DefinedTerm
    101 anzsrc-for:0306 schema:inDefinedTermSet anzsrc-for:
    102 schema:name Physical Chemistry (incl. Structural)
    103 rdf:type schema:DefinedTerm
    104 sg:grant.6984049 http://pending.schema.org/fundedItem sg:pub.10.1007/s10450-019-00026-4
    105 rdf:type schema:MonetaryGrant
    106 sg:journal.1134428 schema:issn 0929-5607
    107 1572-8757
    108 schema:name Adsorption
    109 rdf:type schema:Periodical
    110 sg:pub.10.1007/s10450-007-9002-z schema:sameAs https://app.dimensions.ai/details/publication/pub.1048482520
    111 https://doi.org/10.1007/s10450-007-9002-z
    112 rdf:type schema:CreativeWork
    113 sg:pub.10.1007/s10450-017-9901-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1091081803
    114 https://doi.org/10.1007/s10450-017-9901-6
    115 rdf:type schema:CreativeWork
    116 sg:pub.10.1007/s10450-018-9964-z schema:sameAs https://app.dimensions.ai/details/publication/pub.1106020422
    117 https://doi.org/10.1007/s10450-018-9964-z
    118 rdf:type schema:CreativeWork
    119 sg:pub.10.1007/s10853-015-9007-z schema:sameAs https://app.dimensions.ai/details/publication/pub.1040510762
    120 https://doi.org/10.1007/s10853-015-9007-z
    121 rdf:type schema:CreativeWork
    122 https://doi.org/10.1016/j.apcatb.2013.09.016 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010551928
    123 rdf:type schema:CreativeWork
    124 https://doi.org/10.1016/j.apcatb.2017.02.020 schema:sameAs https://app.dimensions.ai/details/publication/pub.1083695455
    125 rdf:type schema:CreativeWork
    126 https://doi.org/10.1016/j.apsusc.2013.11.003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011484648
    127 rdf:type schema:CreativeWork
    128 https://doi.org/10.1016/j.apsusc.2015.05.088 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023614772
    129 rdf:type schema:CreativeWork
    130 https://doi.org/10.1016/j.apsusc.2015.12.177 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012515805
    131 rdf:type schema:CreativeWork
    132 https://doi.org/10.1016/j.apsusc.2017.10.166 schema:sameAs https://app.dimensions.ai/details/publication/pub.1092597048
    133 rdf:type schema:CreativeWork
    134 https://doi.org/10.1016/j.apsusc.2018.03.108 schema:sameAs https://app.dimensions.ai/details/publication/pub.1101523475
    135 rdf:type schema:CreativeWork
    136 https://doi.org/10.1016/j.commatsci.2013.09.046 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048072096
    137 rdf:type schema:CreativeWork
    138 https://doi.org/10.1016/j.commatsci.2018.03.067 schema:sameAs https://app.dimensions.ai/details/publication/pub.1101848001
    139 rdf:type schema:CreativeWork
    140 https://doi.org/10.1016/j.cplett.2008.02.027 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018634956
    141 rdf:type schema:CreativeWork
    142 https://doi.org/10.1016/j.cplett.2017.11.017 schema:sameAs https://app.dimensions.ai/details/publication/pub.1092667396
    143 rdf:type schema:CreativeWork
    144 https://doi.org/10.1016/j.jallcom.2015.06.130 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008532782
    145 rdf:type schema:CreativeWork
    146 https://doi.org/10.1016/j.jcp.2013.04.020 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011175101
    147 rdf:type schema:CreativeWork
    148 https://doi.org/10.1016/j.matchemphys.2016.11.006 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031259845
    149 rdf:type schema:CreativeWork
    150 https://doi.org/10.1016/j.molliq.2015.06.029 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003805414
    151 rdf:type schema:CreativeWork
    152 https://doi.org/10.1016/j.snb.2016.07.039 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010293993
    153 rdf:type schema:CreativeWork
    154 https://doi.org/10.1016/j.spmi.2016.08.049 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047998960
    155 rdf:type schema:CreativeWork
    156 https://doi.org/10.1016/j.synthmet.2016.09.017 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014593669
    157 rdf:type schema:CreativeWork
    158 https://doi.org/10.1016/j.theochem.2006.11.012 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001712065
    159 rdf:type schema:CreativeWork
    160 https://doi.org/10.1021/acs.jctc.5b00535 schema:sameAs https://app.dimensions.ai/details/publication/pub.1055098664
    161 rdf:type schema:CreativeWork
    162 https://doi.org/10.1021/ie000976k schema:sameAs https://app.dimensions.ai/details/publication/pub.1055594780
    163 rdf:type schema:CreativeWork
    164 https://doi.org/10.1021/ja0447053 schema:sameAs https://app.dimensions.ai/details/publication/pub.1055836334
    165 rdf:type schema:CreativeWork
    166 https://doi.org/10.1021/jp076965n schema:sameAs https://app.dimensions.ai/details/publication/pub.1056074591
    167 rdf:type schema:CreativeWork
    168 https://doi.org/10.1021/jp111389v schema:sameAs https://app.dimensions.ai/details/publication/pub.1056080923
    169 rdf:type schema:CreativeWork
    170 https://doi.org/10.1021/jp808264d schema:sameAs https://app.dimensions.ai/details/publication/pub.1056111203
    171 rdf:type schema:CreativeWork
    172 https://doi.org/10.1039/c5ra00834d schema:sameAs https://app.dimensions.ai/details/publication/pub.1049927440
    173 rdf:type schema:CreativeWork
    174 https://doi.org/10.1063/1.3255016 schema:sameAs https://app.dimensions.ai/details/publication/pub.1057925590
    175 rdf:type schema:CreativeWork
    176 https://doi.org/10.1080/00150193.2017.1388763 schema:sameAs https://app.dimensions.ai/details/publication/pub.1099645528
    177 rdf:type schema:CreativeWork
    178 https://doi.org/10.1103/physrevb.46.6671 schema:sameAs https://app.dimensions.ai/details/publication/pub.1060564150
    179 rdf:type schema:CreativeWork
    180 https://doi.org/10.1103/physrevb.73.205104 schema:sameAs https://app.dimensions.ai/details/publication/pub.1060617606
    181 rdf:type schema:CreativeWork
    182 https://doi.org/10.1103/physrevb.81.165406 schema:sameAs https://app.dimensions.ai/details/publication/pub.1060632440
    183 rdf:type schema:CreativeWork
    184 https://doi.org/10.1103/physrevb.85.045433 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047691741
    185 rdf:type schema:CreativeWork
    186 https://doi.org/10.1126/science.287.5453.622 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006186722
    187 rdf:type schema:CreativeWork
    188 https://doi.org/10.5194/acp-16-1479-2016 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012071934
    189 rdf:type schema:CreativeWork
    190 https://www.grid.ac/institutes/grid.440734.0 schema:alternateName Hebei United University
    191 schema:name College of Mechanical Engineering, North China University of Science and Technology, 21 Bohai Road, Caofeidian District, 063210, Tangshan, Hebei, China
    192 rdf:type schema:Organization
     




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


    ...