Controlling gas permeability of a graft copolymer membrane using solvent vapor treatment View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2014-02

AUTHORS

Sung Hoon Ahn, Sang Jin Kim, Dong Kyu Roh, Hyung-Keun Lee, Bumsuk Jung, Jong Hak Kim

ABSTRACT

A strategy is reported that combines assembled nanostructures and solvent vapor treatment to manipulate the gas permeability of graft copolymer membranes. The VC-g-POEM graft copolymer consists of poly(vinyl chloride) (PVC) main chains and poly(oxyethylene methacrylate) (POEM) side chains, and was synthesized via atom transfer radical polymerization (ATRP). When the PVC-g-POEM membrane was treated with a good solvent vapor such as acetone, the CO2 permeability increased from 107 to 145 Barrer (1 Barrer=10−10 cm3(STP)·cm·cm−2·s−1·cmHg−1), which is approximately a 36% improvement compared to an untreated sample. However, the permeability was significantly reduced from 107 to 45 and 38 Barrer upon being treated with a selective (methanol) or poor solvent (hexane). The structure-property relation of the solvent-vapor-treated membranes was investigated using transmission electron microscopy (TEM) and small-angle X-ray scattering (SAXS) analysis. More... »

PAGES

160-164

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s13233-014-2014-0

DOI

http://dx.doi.org/10.1007/s13233-014-2014-0

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1039396795


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/2008/0303", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Macromolecular and Materials 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": "Yonsei University", 
          "id": "https://www.grid.ac/institutes/grid.15444.30", 
          "name": [
            "Department of Chemical and Biomolecular Engineering, Yonsei University, 120-749, Seoul, Korea"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Ahn", 
        "givenName": "Sung Hoon", 
        "id": "sg:person.01004521447.50", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01004521447.50"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Yonsei University", 
          "id": "https://www.grid.ac/institutes/grid.15444.30", 
          "name": [
            "Department of Chemical and Biomolecular Engineering, Yonsei University, 120-749, Seoul, Korea"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kim", 
        "givenName": "Sang Jin", 
        "id": "sg:person.01341252607.80", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01341252607.80"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Yonsei University", 
          "id": "https://www.grid.ac/institutes/grid.15444.30", 
          "name": [
            "Department of Chemical and Biomolecular Engineering, Yonsei University, 120-749, Seoul, Korea"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Roh", 
        "givenName": "Dong Kyu", 
        "id": "sg:person.01303350323.14", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01303350323.14"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Korea Institute of Energy Research", 
          "id": "https://www.grid.ac/institutes/grid.418979.a", 
          "name": [
            "Korea Institute of Energy Research, 305-343, Daejeon, Korea"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Lee", 
        "givenName": "Hyung-Keun", 
        "id": "sg:person.010427104517.13", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010427104517.13"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Myongji University", 
          "id": "https://www.grid.ac/institutes/grid.410898.c", 
          "name": [
            "Department of Environmental Engineering and Energy, Myongji University, 499-728, Gyeonggi, Korea"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Jung", 
        "givenName": "Bumsuk", 
        "id": "sg:person.07536040525.33", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07536040525.33"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Yonsei University", 
          "id": "https://www.grid.ac/institutes/grid.15444.30", 
          "name": [
            "Department of Chemical and Biomolecular Engineering, Yonsei University, 120-749, Seoul, Korea"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kim", 
        "givenName": "Jong Hak", 
        "id": "sg:person.012444663541.35", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012444663541.35"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1016/j.memsci.2008.01.015", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000030801"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/adfm.200800436", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000282250"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1039/c2ra20748f", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1002129160"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1149/1.1824032", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003166169"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s13233-012-0159-2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003887732", 
          "https://doi.org/10.1007/s13233-012-0159-2"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.memsci.2004.07.005", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1005707585"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.seppur.2013.03.052", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1009422454"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nmat2989", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1013047794", 
          "https://doi.org/10.1038/nmat2989"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1088/0957-4484/23/11/115604", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016303684"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.memsci.2009.08.037", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017049789"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1039/c2cc17535e", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023025871"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1039/c1cc10540j", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1028624471"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1039/c2jm31037f", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1028638454"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/ie8019032", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1031679582"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/ie8019032", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1031679582"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.memsci.2008.04.030", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1033561600"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.memsci.2007.01.022", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034976835"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s13233-011-1116-1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039868377", 
          "https://doi.org/10.1007/s13233-011-1116-1"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.memsci.2009.02.016", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039988193"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1039/c2ee23080a", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1041422966"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/adma.201103799", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048100941"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1126/science.1146744", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048738723"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/adfm.201101520", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051792084"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/ma060128m", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1056191761"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/ma060128m", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1056191761"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/ma2001838", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1056195102"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/ma2001838", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1056195102"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/ma202415t", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1056195959"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2014-02", 
    "datePublishedReg": "2014-02-01", 
    "description": "A strategy is reported that combines assembled nanostructures and solvent vapor treatment to manipulate the gas permeability of graft copolymer membranes. The VC-g-POEM graft copolymer consists of poly(vinyl chloride) (PVC) main chains and poly(oxyethylene methacrylate) (POEM) side chains, and was synthesized via atom transfer radical polymerization (ATRP). When the PVC-g-POEM membrane was treated with a good solvent vapor such as acetone, the CO2 permeability increased from 107 to 145 Barrer (1 Barrer=10\u221210 cm3(STP)\u00b7cm\u00b7cm\u22122\u00b7s\u22121\u00b7cmHg\u22121), which is approximately a 36% improvement compared to an untreated sample. However, the permeability was significantly reduced from 107 to 45 and 38 Barrer upon being treated with a selective (methanol) or poor solvent (hexane). The structure-property relation of the solvent-vapor-treated membranes was investigated using transmission electron microscopy (TEM) and small-angle X-ray scattering (SAXS) analysis.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/s13233-014-2014-0", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1294783", 
        "issn": [
          "1598-5032", 
          "2092-7673"
        ], 
        "name": "Macromolecular Research", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "2", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "22"
      }
    ], 
    "name": "Controlling gas permeability of a graft copolymer membrane using solvent vapor treatment", 
    "pagination": "160-164", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "bbab0de792f6cd25fb2a7df1fdaf1dcb8a19e9bcd93e0f47e164b736546888d0"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s13233-014-2014-0"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1039396795"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s13233-014-2014-0", 
      "https://app.dimensions.ai/details/publication/pub.1039396795"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-10T19:11", 
    "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_00000523.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "http://link.springer.com/10.1007%2Fs13233-014-2014-0"
  }
]
 

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/s13233-014-2014-0'

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/s13233-014-2014-0'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s13233-014-2014-0'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s13233-014-2014-0'


 

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

180 TRIPLES      21 PREDICATES      52 URIs      19 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s13233-014-2014-0 schema:about anzsrc-for:03
2 anzsrc-for:0303
3 schema:author N42ff4d3d881e48dc8f7232a61ce11501
4 schema:citation sg:pub.10.1007/s13233-011-1116-1
5 sg:pub.10.1007/s13233-012-0159-2
6 sg:pub.10.1038/nmat2989
7 https://doi.org/10.1002/adfm.200800436
8 https://doi.org/10.1002/adfm.201101520
9 https://doi.org/10.1002/adma.201103799
10 https://doi.org/10.1016/j.memsci.2004.07.005
11 https://doi.org/10.1016/j.memsci.2007.01.022
12 https://doi.org/10.1016/j.memsci.2008.01.015
13 https://doi.org/10.1016/j.memsci.2008.04.030
14 https://doi.org/10.1016/j.memsci.2009.02.016
15 https://doi.org/10.1016/j.memsci.2009.08.037
16 https://doi.org/10.1016/j.seppur.2013.03.052
17 https://doi.org/10.1021/ie8019032
18 https://doi.org/10.1021/ma060128m
19 https://doi.org/10.1021/ma2001838
20 https://doi.org/10.1021/ma202415t
21 https://doi.org/10.1039/c1cc10540j
22 https://doi.org/10.1039/c2cc17535e
23 https://doi.org/10.1039/c2ee23080a
24 https://doi.org/10.1039/c2jm31037f
25 https://doi.org/10.1039/c2ra20748f
26 https://doi.org/10.1088/0957-4484/23/11/115604
27 https://doi.org/10.1126/science.1146744
28 https://doi.org/10.1149/1.1824032
29 schema:datePublished 2014-02
30 schema:datePublishedReg 2014-02-01
31 schema:description A strategy is reported that combines assembled nanostructures and solvent vapor treatment to manipulate the gas permeability of graft copolymer membranes. The VC-g-POEM graft copolymer consists of poly(vinyl chloride) (PVC) main chains and poly(oxyethylene methacrylate) (POEM) side chains, and was synthesized via atom transfer radical polymerization (ATRP). When the PVC-g-POEM membrane was treated with a good solvent vapor such as acetone, the CO2 permeability increased from 107 to 145 Barrer (1 Barrer=10−10 cm3(STP)·cm·cm−2·s−1·cmHg−1), which is approximately a 36% improvement compared to an untreated sample. However, the permeability was significantly reduced from 107 to 45 and 38 Barrer upon being treated with a selective (methanol) or poor solvent (hexane). The structure-property relation of the solvent-vapor-treated membranes was investigated using transmission electron microscopy (TEM) and small-angle X-ray scattering (SAXS) analysis.
32 schema:genre research_article
33 schema:inLanguage en
34 schema:isAccessibleForFree false
35 schema:isPartOf Nb0010a3033a9455cb3c84c74306b6e9b
36 Nd9c482b11ed346db9400f0fccd77c10f
37 sg:journal.1294783
38 schema:name Controlling gas permeability of a graft copolymer membrane using solvent vapor treatment
39 schema:pagination 160-164
40 schema:productId N12bd1142f15e4379bb3e5d30bf26fbc8
41 N49613eafc7b7414d95ee5b5b028ed410
42 Neac9e008556240e6a1b1ea04f4347da2
43 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039396795
44 https://doi.org/10.1007/s13233-014-2014-0
45 schema:sdDatePublished 2019-04-10T19:11
46 schema:sdLicense https://scigraph.springernature.com/explorer/license/
47 schema:sdPublisher Na3b6a9b40090414f8144267445777410
48 schema:url http://link.springer.com/10.1007%2Fs13233-014-2014-0
49 sgo:license sg:explorer/license/
50 sgo:sdDataset articles
51 rdf:type schema:ScholarlyArticle
52 N12bd1142f15e4379bb3e5d30bf26fbc8 schema:name doi
53 schema:value 10.1007/s13233-014-2014-0
54 rdf:type schema:PropertyValue
55 N20b7fceafea944f4ab670277aa76298f rdf:first sg:person.01303350323.14
56 rdf:rest Na3ec8e87d7e042c49e22cf4600af7925
57 N42ff4d3d881e48dc8f7232a61ce11501 rdf:first sg:person.01004521447.50
58 rdf:rest Ne4ed562cd5444938816353df017b9ec2
59 N49613eafc7b7414d95ee5b5b028ed410 schema:name readcube_id
60 schema:value bbab0de792f6cd25fb2a7df1fdaf1dcb8a19e9bcd93e0f47e164b736546888d0
61 rdf:type schema:PropertyValue
62 Na3b6a9b40090414f8144267445777410 schema:name Springer Nature - SN SciGraph project
63 rdf:type schema:Organization
64 Na3ec8e87d7e042c49e22cf4600af7925 rdf:first sg:person.010427104517.13
65 rdf:rest Nf302102a2b0540ffb137d5f8ce4a5409
66 Nae8696a771264cbab9d5daca01e6a22f rdf:first sg:person.012444663541.35
67 rdf:rest rdf:nil
68 Nb0010a3033a9455cb3c84c74306b6e9b schema:volumeNumber 22
69 rdf:type schema:PublicationVolume
70 Nd9c482b11ed346db9400f0fccd77c10f schema:issueNumber 2
71 rdf:type schema:PublicationIssue
72 Ne4ed562cd5444938816353df017b9ec2 rdf:first sg:person.01341252607.80
73 rdf:rest N20b7fceafea944f4ab670277aa76298f
74 Neac9e008556240e6a1b1ea04f4347da2 schema:name dimensions_id
75 schema:value pub.1039396795
76 rdf:type schema:PropertyValue
77 Nf302102a2b0540ffb137d5f8ce4a5409 rdf:first sg:person.07536040525.33
78 rdf:rest Nae8696a771264cbab9d5daca01e6a22f
79 anzsrc-for:03 schema:inDefinedTermSet anzsrc-for:
80 schema:name Chemical Sciences
81 rdf:type schema:DefinedTerm
82 anzsrc-for:0303 schema:inDefinedTermSet anzsrc-for:
83 schema:name Macromolecular and Materials Chemistry
84 rdf:type schema:DefinedTerm
85 sg:journal.1294783 schema:issn 1598-5032
86 2092-7673
87 schema:name Macromolecular Research
88 rdf:type schema:Periodical
89 sg:person.01004521447.50 schema:affiliation https://www.grid.ac/institutes/grid.15444.30
90 schema:familyName Ahn
91 schema:givenName Sung Hoon
92 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01004521447.50
93 rdf:type schema:Person
94 sg:person.010427104517.13 schema:affiliation https://www.grid.ac/institutes/grid.418979.a
95 schema:familyName Lee
96 schema:givenName Hyung-Keun
97 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010427104517.13
98 rdf:type schema:Person
99 sg:person.012444663541.35 schema:affiliation https://www.grid.ac/institutes/grid.15444.30
100 schema:familyName Kim
101 schema:givenName Jong Hak
102 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012444663541.35
103 rdf:type schema:Person
104 sg:person.01303350323.14 schema:affiliation https://www.grid.ac/institutes/grid.15444.30
105 schema:familyName Roh
106 schema:givenName Dong Kyu
107 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01303350323.14
108 rdf:type schema:Person
109 sg:person.01341252607.80 schema:affiliation https://www.grid.ac/institutes/grid.15444.30
110 schema:familyName Kim
111 schema:givenName Sang Jin
112 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01341252607.80
113 rdf:type schema:Person
114 sg:person.07536040525.33 schema:affiliation https://www.grid.ac/institutes/grid.410898.c
115 schema:familyName Jung
116 schema:givenName Bumsuk
117 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07536040525.33
118 rdf:type schema:Person
119 sg:pub.10.1007/s13233-011-1116-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039868377
120 https://doi.org/10.1007/s13233-011-1116-1
121 rdf:type schema:CreativeWork
122 sg:pub.10.1007/s13233-012-0159-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003887732
123 https://doi.org/10.1007/s13233-012-0159-2
124 rdf:type schema:CreativeWork
125 sg:pub.10.1038/nmat2989 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013047794
126 https://doi.org/10.1038/nmat2989
127 rdf:type schema:CreativeWork
128 https://doi.org/10.1002/adfm.200800436 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000282250
129 rdf:type schema:CreativeWork
130 https://doi.org/10.1002/adfm.201101520 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051792084
131 rdf:type schema:CreativeWork
132 https://doi.org/10.1002/adma.201103799 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048100941
133 rdf:type schema:CreativeWork
134 https://doi.org/10.1016/j.memsci.2004.07.005 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005707585
135 rdf:type schema:CreativeWork
136 https://doi.org/10.1016/j.memsci.2007.01.022 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034976835
137 rdf:type schema:CreativeWork
138 https://doi.org/10.1016/j.memsci.2008.01.015 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000030801
139 rdf:type schema:CreativeWork
140 https://doi.org/10.1016/j.memsci.2008.04.030 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033561600
141 rdf:type schema:CreativeWork
142 https://doi.org/10.1016/j.memsci.2009.02.016 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039988193
143 rdf:type schema:CreativeWork
144 https://doi.org/10.1016/j.memsci.2009.08.037 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017049789
145 rdf:type schema:CreativeWork
146 https://doi.org/10.1016/j.seppur.2013.03.052 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009422454
147 rdf:type schema:CreativeWork
148 https://doi.org/10.1021/ie8019032 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031679582
149 rdf:type schema:CreativeWork
150 https://doi.org/10.1021/ma060128m schema:sameAs https://app.dimensions.ai/details/publication/pub.1056191761
151 rdf:type schema:CreativeWork
152 https://doi.org/10.1021/ma2001838 schema:sameAs https://app.dimensions.ai/details/publication/pub.1056195102
153 rdf:type schema:CreativeWork
154 https://doi.org/10.1021/ma202415t schema:sameAs https://app.dimensions.ai/details/publication/pub.1056195959
155 rdf:type schema:CreativeWork
156 https://doi.org/10.1039/c1cc10540j schema:sameAs https://app.dimensions.ai/details/publication/pub.1028624471
157 rdf:type schema:CreativeWork
158 https://doi.org/10.1039/c2cc17535e schema:sameAs https://app.dimensions.ai/details/publication/pub.1023025871
159 rdf:type schema:CreativeWork
160 https://doi.org/10.1039/c2ee23080a schema:sameAs https://app.dimensions.ai/details/publication/pub.1041422966
161 rdf:type schema:CreativeWork
162 https://doi.org/10.1039/c2jm31037f schema:sameAs https://app.dimensions.ai/details/publication/pub.1028638454
163 rdf:type schema:CreativeWork
164 https://doi.org/10.1039/c2ra20748f schema:sameAs https://app.dimensions.ai/details/publication/pub.1002129160
165 rdf:type schema:CreativeWork
166 https://doi.org/10.1088/0957-4484/23/11/115604 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016303684
167 rdf:type schema:CreativeWork
168 https://doi.org/10.1126/science.1146744 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048738723
169 rdf:type schema:CreativeWork
170 https://doi.org/10.1149/1.1824032 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003166169
171 rdf:type schema:CreativeWork
172 https://www.grid.ac/institutes/grid.15444.30 schema:alternateName Yonsei University
173 schema:name Department of Chemical and Biomolecular Engineering, Yonsei University, 120-749, Seoul, Korea
174 rdf:type schema:Organization
175 https://www.grid.ac/institutes/grid.410898.c schema:alternateName Myongji University
176 schema:name Department of Environmental Engineering and Energy, Myongji University, 499-728, Gyeonggi, Korea
177 rdf:type schema:Organization
178 https://www.grid.ac/institutes/grid.418979.a schema:alternateName Korea Institute of Energy Research
179 schema:name Korea Institute of Energy Research, 305-343, Daejeon, Korea
180 rdf:type schema:Organization
 




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


...