Electromagnetic and Mechanical Properties of the Nanocomposites of Polyacrylonitrile/Carbon Nanotubes View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2018-12

AUTHORS

L. V. Kozhitov, A. V. Shadrinov, D. G. Muratov, E. Yu. Korovin, A. V. Popkova

ABSTRACT

Films of carbon-polymer nanocomposite polyacrylonitrile/single-wall carbon nanotubes (PAN/SWCNTs) with various filler concentrations varying from 0.5 to 30 wt % are synthesized. It is found that use of fillers as the SWCNTs in a polymer composite based on PAN significantly influences the mechanical properties of the polymer; in particular the tensile strength increases. Studying the electrophysical properties shows that the electric conductivity increases by two orders of magnitude due to the degree of percolation and by 7 orders of magnitude in comparison with pure PAN, on introducing SWCNT fillers ranging from 0.5 to 30 wt %. Thermal analyses of the nanocomposite are carried out and they show that the thermal stability of the samples increases and the weight losses decrease at an increase of the SWCNT concentration. The dielectric capacitivity and the coefficients of reflection, transfer, and absorption in the terahertz range are measured. It is found that the coefficient of reflection nonlinearly depends on the concentration of carbon nanotubes (CNTs). The minimum reflection coefficient of 0.55 per unit values is observed at the concentration of 0.5 wt %, whereas materials with an SWCNT concentration of more than 5 wt % show almost the same reflection coefficient at s sufficiently low transfer coefficient. More... »

PAGES

589-597

Identifiers

URI

http://scigraph.springernature.com/pub.10.1134/s106373971808005x

DOI

http://dx.doi.org/10.1134/s106373971808005x

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1112900850


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/2008/0912", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Materials 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": "National University of Science and Technology", 
          "id": "https://www.grid.ac/institutes/grid.35043.31", 
          "name": [
            "National University of Science and Technology MISiS, Moscow, Russia"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kozhitov", 
        "givenName": "L. V.", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "National University of Science and Technology", 
          "id": "https://www.grid.ac/institutes/grid.35043.31", 
          "name": [
            "National University of Science and Technology MISiS, Moscow, Russia"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Shadrinov", 
        "givenName": "A. V.", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "A.V.Topchiev Institute of Petrochemical Synthesis", 
          "id": "https://www.grid.ac/institutes/grid.423490.8", 
          "name": [
            "National University of Science and Technology MISiS, Moscow, Russia", 
            "Topchiev Institute of Petrochemical Synthesis, Russian Academy of Sciences, Moscow, Russia"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Muratov", 
        "givenName": "D. G.", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Tomsk State University", 
          "id": "https://www.grid.ac/institutes/grid.77602.34", 
          "name": [
            "Tomsk State University, Tomsk, Russia"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Korovin", 
        "givenName": "E. Yu.", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Tver State University", 
          "id": "https://www.grid.ac/institutes/grid.438242.b", 
          "name": [
            "Tver State University, Tver, Russia"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Popkova", 
        "givenName": "A. V.", 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1016/j.jmmm.2011.06.070", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1001865500"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.matlet.2012.12.069", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1009703620"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.progpolymsci.2013.08.009", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1010291494"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.matlet.2011.09.036", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1021424793"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1155/2011/648324", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025041270"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.4236/ojcm.2013.32003", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1033138953"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11182-013-9909-7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1041354594", 
          "https://doi.org/10.1007/s11182-013-9909-7"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10854-017-6561-y", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1084027409", 
          "https://doi.org/10.1007/s10854-017-6561-y"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10854-017-6561-y", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1084027409", 
          "https://doi.org/10.1007/s10854-017-6561-y"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2018-12", 
    "datePublishedReg": "2018-12-01", 
    "description": "Films of carbon-polymer nanocomposite polyacrylonitrile/single-wall carbon nanotubes (PAN/SWCNTs) with various filler concentrations varying from 0.5 to 30 wt % are synthesized. It is found that use of fillers as the SWCNTs in a polymer composite based on PAN significantly influences the mechanical properties of the polymer; in particular the tensile strength increases. Studying the electrophysical properties shows that the electric conductivity increases by two orders of magnitude due to the degree of percolation and by 7 orders of magnitude in comparison with pure PAN, on introducing SWCNT fillers ranging from 0.5 to 30 wt %. Thermal analyses of the nanocomposite are carried out and they show that the thermal stability of the samples increases and the weight losses decrease at an increase of the SWCNT concentration. The dielectric capacitivity and the coefficients of reflection, transfer, and absorption in the terahertz range are measured. It is found that the coefficient of reflection nonlinearly depends on the concentration of carbon nanotubes (CNTs). The minimum reflection coefficient of 0.55 per unit values is observed at the concentration of 0.5 wt %, whereas materials with an SWCNT concentration of more than 5 wt % show almost the same reflection coefficient at s sufficiently low transfer coefficient.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1134/s106373971808005x", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1136391", 
        "issn": [
          "1063-7397", 
          "1608-3415"
        ], 
        "name": "Russian Microelectronics", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "8", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "47"
      }
    ], 
    "name": "Electromagnetic and Mechanical Properties of the Nanocomposites of Polyacrylonitrile/Carbon Nanotubes", 
    "pagination": "589-597", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "c0462853aad492b44ccc8e87065972b3399e35c370b12d1a63a427f52efa6e74"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1134/s106373971808005x"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1112900850"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1134/s106373971808005x", 
      "https://app.dimensions.ai/details/publication/pub.1112900850"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T12:35", 
    "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/v90/0000000363_0000000363/records_70027_00000003.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://link.springer.com/10.1134%2FS106373971808005X"
  }
]
 

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/s106373971808005x'

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/s106373971808005x'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1134/s106373971808005x'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1134/s106373971808005x'


 

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

120 TRIPLES      21 PREDICATES      35 URIs      19 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1134/s106373971808005x schema:about anzsrc-for:09
2 anzsrc-for:0912
3 schema:author Nc95391e5abec4e4d82a47a1571ad224e
4 schema:citation sg:pub.10.1007/s10854-017-6561-y
5 sg:pub.10.1007/s11182-013-9909-7
6 https://doi.org/10.1016/j.jmmm.2011.06.070
7 https://doi.org/10.1016/j.matlet.2011.09.036
8 https://doi.org/10.1016/j.matlet.2012.12.069
9 https://doi.org/10.1016/j.progpolymsci.2013.08.009
10 https://doi.org/10.1155/2011/648324
11 https://doi.org/10.4236/ojcm.2013.32003
12 schema:datePublished 2018-12
13 schema:datePublishedReg 2018-12-01
14 schema:description Films of carbon-polymer nanocomposite polyacrylonitrile/single-wall carbon nanotubes (PAN/SWCNTs) with various filler concentrations varying from 0.5 to 30 wt % are synthesized. It is found that use of fillers as the SWCNTs in a polymer composite based on PAN significantly influences the mechanical properties of the polymer; in particular the tensile strength increases. Studying the electrophysical properties shows that the electric conductivity increases by two orders of magnitude due to the degree of percolation and by 7 orders of magnitude in comparison with pure PAN, on introducing SWCNT fillers ranging from 0.5 to 30 wt %. Thermal analyses of the nanocomposite are carried out and they show that the thermal stability of the samples increases and the weight losses decrease at an increase of the SWCNT concentration. The dielectric capacitivity and the coefficients of reflection, transfer, and absorption in the terahertz range are measured. It is found that the coefficient of reflection nonlinearly depends on the concentration of carbon nanotubes (CNTs). The minimum reflection coefficient of 0.55 per unit values is observed at the concentration of 0.5 wt %, whereas materials with an SWCNT concentration of more than 5 wt % show almost the same reflection coefficient at s sufficiently low transfer coefficient.
15 schema:genre research_article
16 schema:inLanguage en
17 schema:isAccessibleForFree false
18 schema:isPartOf Nba32b3bf240d48768bb5f4f9888419dd
19 Ndba86cc3ba8c449fa3c25cacdd228a0f
20 sg:journal.1136391
21 schema:name Electromagnetic and Mechanical Properties of the Nanocomposites of Polyacrylonitrile/Carbon Nanotubes
22 schema:pagination 589-597
23 schema:productId N6899b6e6c8ff4a4b8c62ff4948ae8c31
24 N9a6353e5689c44fa8ed91edd5f339670
25 Nf949f834761e4d5bbe2f463457ceee5f
26 schema:sameAs https://app.dimensions.ai/details/publication/pub.1112900850
27 https://doi.org/10.1134/s106373971808005x
28 schema:sdDatePublished 2019-04-11T12:35
29 schema:sdLicense https://scigraph.springernature.com/explorer/license/
30 schema:sdPublisher N6cfd069c1a2548e3b0c22188d925c5d0
31 schema:url https://link.springer.com/10.1134%2FS106373971808005X
32 sgo:license sg:explorer/license/
33 sgo:sdDataset articles
34 rdf:type schema:ScholarlyArticle
35 N17f25c711ef3463b9370ce4fef826a42 rdf:first Na84d4d385aac46799e5b886955889ded
36 rdf:rest rdf:nil
37 N311cca0bf950477db0065b842ce852e3 schema:affiliation https://www.grid.ac/institutes/grid.77602.34
38 schema:familyName Korovin
39 schema:givenName E. Yu.
40 rdf:type schema:Person
41 N6899b6e6c8ff4a4b8c62ff4948ae8c31 schema:name dimensions_id
42 schema:value pub.1112900850
43 rdf:type schema:PropertyValue
44 N6cfd069c1a2548e3b0c22188d925c5d0 schema:name Springer Nature - SN SciGraph project
45 rdf:type schema:Organization
46 N895fdc6bfb5e4c5684634f9acd0847cc rdf:first Nc3459e22c09d42328579faf2ebd2ed0b
47 rdf:rest Nefebdefbb6424592ad6bd63e3e8f2186
48 N8dbed73bbe3d4425bec8c2b48e425bea rdf:first N311cca0bf950477db0065b842ce852e3
49 rdf:rest N17f25c711ef3463b9370ce4fef826a42
50 N9a6353e5689c44fa8ed91edd5f339670 schema:name readcube_id
51 schema:value c0462853aad492b44ccc8e87065972b3399e35c370b12d1a63a427f52efa6e74
52 rdf:type schema:PropertyValue
53 Na7bedd3e157e4c588355ba1db4425fda schema:affiliation https://www.grid.ac/institutes/grid.423490.8
54 schema:familyName Muratov
55 schema:givenName D. G.
56 rdf:type schema:Person
57 Na84d4d385aac46799e5b886955889ded schema:affiliation https://www.grid.ac/institutes/grid.438242.b
58 schema:familyName Popkova
59 schema:givenName A. V.
60 rdf:type schema:Person
61 Naea3d4703c3e4673a7be7eb021126dfd schema:affiliation https://www.grid.ac/institutes/grid.35043.31
62 schema:familyName Kozhitov
63 schema:givenName L. V.
64 rdf:type schema:Person
65 Nba32b3bf240d48768bb5f4f9888419dd schema:volumeNumber 47
66 rdf:type schema:PublicationVolume
67 Nc3459e22c09d42328579faf2ebd2ed0b schema:affiliation https://www.grid.ac/institutes/grid.35043.31
68 schema:familyName Shadrinov
69 schema:givenName A. V.
70 rdf:type schema:Person
71 Nc95391e5abec4e4d82a47a1571ad224e rdf:first Naea3d4703c3e4673a7be7eb021126dfd
72 rdf:rest N895fdc6bfb5e4c5684634f9acd0847cc
73 Ndba86cc3ba8c449fa3c25cacdd228a0f schema:issueNumber 8
74 rdf:type schema:PublicationIssue
75 Nefebdefbb6424592ad6bd63e3e8f2186 rdf:first Na7bedd3e157e4c588355ba1db4425fda
76 rdf:rest N8dbed73bbe3d4425bec8c2b48e425bea
77 Nf949f834761e4d5bbe2f463457ceee5f schema:name doi
78 schema:value 10.1134/s106373971808005x
79 rdf:type schema:PropertyValue
80 anzsrc-for:09 schema:inDefinedTermSet anzsrc-for:
81 schema:name Engineering
82 rdf:type schema:DefinedTerm
83 anzsrc-for:0912 schema:inDefinedTermSet anzsrc-for:
84 schema:name Materials Engineering
85 rdf:type schema:DefinedTerm
86 sg:journal.1136391 schema:issn 1063-7397
87 1608-3415
88 schema:name Russian Microelectronics
89 rdf:type schema:Periodical
90 sg:pub.10.1007/s10854-017-6561-y schema:sameAs https://app.dimensions.ai/details/publication/pub.1084027409
91 https://doi.org/10.1007/s10854-017-6561-y
92 rdf:type schema:CreativeWork
93 sg:pub.10.1007/s11182-013-9909-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041354594
94 https://doi.org/10.1007/s11182-013-9909-7
95 rdf:type schema:CreativeWork
96 https://doi.org/10.1016/j.jmmm.2011.06.070 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001865500
97 rdf:type schema:CreativeWork
98 https://doi.org/10.1016/j.matlet.2011.09.036 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021424793
99 rdf:type schema:CreativeWork
100 https://doi.org/10.1016/j.matlet.2012.12.069 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009703620
101 rdf:type schema:CreativeWork
102 https://doi.org/10.1016/j.progpolymsci.2013.08.009 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010291494
103 rdf:type schema:CreativeWork
104 https://doi.org/10.1155/2011/648324 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025041270
105 rdf:type schema:CreativeWork
106 https://doi.org/10.4236/ojcm.2013.32003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033138953
107 rdf:type schema:CreativeWork
108 https://www.grid.ac/institutes/grid.35043.31 schema:alternateName National University of Science and Technology
109 schema:name National University of Science and Technology MISiS, Moscow, Russia
110 rdf:type schema:Organization
111 https://www.grid.ac/institutes/grid.423490.8 schema:alternateName A.V.Topchiev Institute of Petrochemical Synthesis
112 schema:name National University of Science and Technology MISiS, Moscow, Russia
113 Topchiev Institute of Petrochemical Synthesis, Russian Academy of Sciences, Moscow, Russia
114 rdf:type schema:Organization
115 https://www.grid.ac/institutes/grid.438242.b schema:alternateName Tver State University
116 schema:name Tver State University, Tver, Russia
117 rdf:type schema:Organization
118 https://www.grid.ac/institutes/grid.77602.34 schema:alternateName Tomsk State University
119 schema:name Tomsk State University, Tomsk, Russia
120 rdf:type schema:Organization
 




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


...