The optimization of coal on-line analysis system based on signal-to-noise ratio evaluation View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2018-11

AUTHORS

JiaTong Li, WenBao Jia, DaQian Hei, PingKun Cai, Can Cheng, Yajun Tang

ABSTRACT

In the present study, the coal on-line analysis system is optimized, and the signal-to-noise ratio (SNR) is quantified and set as the evaluation criterion for device optimization. 3 cm lead with 3 cm polyethylene is set as moderator, and 13 cm lead is for a better shielding. Besides, the neutron generator is set at the center of device, and 72 cm is set as the better distance of axis between neutron generator and detector. Finally, by comparing with the previous experimental results, the Mean Absolute Percentage Error of element with the value less than 1% is improved after device optimization by SNR evaluation. More... »

PAGES

1279-1286

References to SciGraph publications

  • 2013-04. Optimization of a prompt gamma setup for analysis of environmental samples in JOURNAL OF RADIOANALYTICAL AND NUCLEAR CHEMISTRY
  • 2016-10. The background influence of cadmium detection in saline water using PGNAA technique in JOURNAL OF RADIOANALYTICAL AND NUCLEAR CHEMISTRY
  • 2015-06. Method for correcting thermal neutron self-shielding effect for aqueous bulk sample analysis by PGNAA technique in JOURNAL OF RADIOANALYTICAL AND NUCLEAR CHEMISTRY
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s10967-018-6173-x

    DOI

    http://dx.doi.org/10.1007/s10967-018-6173-x

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1106705816


    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/2008/0103", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Numerical and Computational Mathematics", 
            "type": "DefinedTerm"
          }, 
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/01", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Mathematical Sciences", 
            "type": "DefinedTerm"
          }
        ], 
        "author": [
          {
            "affiliation": {
              "alternateName": "Nanjing University of Aeronautics and Astronautics", 
              "id": "https://www.grid.ac/institutes/grid.64938.30", 
              "name": [
                "Department of Nuclear Science and Engineering, College of Materials Science and Engineering, Nanjing University of Aeronautics and Astronautics, 211106, Nanjing, China"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Li", 
            "givenName": "JiaTong", 
            "id": "sg:person.016477246610.91", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016477246610.91"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Nanjing University of Aeronautics and Astronautics", 
              "id": "https://www.grid.ac/institutes/grid.64938.30", 
              "name": [
                "Department of Nuclear Science and Engineering, College of Materials Science and Engineering, Nanjing University of Aeronautics and Astronautics, 211106, Nanjing, China", 
                "Collaborative Innovation Center of Radiation Medicine of Jiangsu Higher Education Institutions, 215000, Suzhou, China"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Jia", 
            "givenName": "WenBao", 
            "id": "sg:person.01256220355.94", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01256220355.94"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Nanjing University of Aeronautics and Astronautics", 
              "id": "https://www.grid.ac/institutes/grid.64938.30", 
              "name": [
                "Department of Nuclear Science and Engineering, College of Materials Science and Engineering, Nanjing University of Aeronautics and Astronautics, 211106, Nanjing, China", 
                "Collaborative Innovation Center of Radiation Medicine of Jiangsu Higher Education Institutions, 215000, Suzhou, China"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Hei", 
            "givenName": "DaQian", 
            "id": "sg:person.010512173621.38", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010512173621.38"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Nanjing University of Aeronautics and Astronautics", 
              "id": "https://www.grid.ac/institutes/grid.64938.30", 
              "name": [
                "Department of Nuclear Science and Engineering, College of Materials Science and Engineering, Nanjing University of Aeronautics and Astronautics, 211106, Nanjing, China"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Cai", 
            "givenName": "PingKun", 
            "id": "sg:person.0775462633.45", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0775462633.45"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Nanjing University of Aeronautics and Astronautics", 
              "id": "https://www.grid.ac/institutes/grid.64938.30", 
              "name": [
                "Department of Nuclear Science and Engineering, College of Materials Science and Engineering, Nanjing University of Aeronautics and Astronautics, 211106, Nanjing, China"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Cheng", 
            "givenName": "Can", 
            "id": "sg:person.01136640362.24", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01136640362.24"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Nanjing University of Aeronautics and Astronautics", 
              "id": "https://www.grid.ac/institutes/grid.64938.30", 
              "name": [
                "Department of Nuclear Science and Engineering, College of Materials Science and Engineering, Nanjing University of Aeronautics and Astronautics, 211106, Nanjing, China"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Tang", 
            "givenName": "Yajun", 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "sg:pub.10.1007/s10967-012-2045-y", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1008543093", 
              "https://doi.org/10.1007/s10967-012-2045-y"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s10967-015-3962-3", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1012410089", 
              "https://doi.org/10.1007/s10967-015-3962-3"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.nimb.2014.10.010", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1013265562"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s0168-9002(03)01123-9", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1014599007"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s0168-9002(03)01123-9", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1014599007"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.nimb.2004.05.038", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1014755780"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.radphyschem.2009.04.023", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1017608173"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.nima.2015.07.063", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1020595796"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.apradiso.2014.11.005", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1022009299"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.apradiso.2016.03.019", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1026370621"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s0969-8043(00)00206-2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1037823892"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.apradiso.2010.11.014", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1045936911"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.nimb.2010.10.006", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1048924753"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.nimb.2007.04.238", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1051096600"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s10967-016-4767-8", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1053080360", 
              "https://doi.org/10.1007/s10967-016-4767-8"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1063/1.1844472", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1057827092"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.13182/nse05-a2556", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1091174530"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.13182/nse07-a2652", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1091174612"
            ], 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2018-11", 
        "datePublishedReg": "2018-11-01", 
        "description": "In the present study, the coal on-line analysis system is optimized, and the signal-to-noise ratio (SNR) is quantified and set as the evaluation criterion for device optimization. 3 cm lead with 3 cm polyethylene is set as moderator, and 13 cm lead is for a better shielding. Besides, the neutron generator is set at the center of device, and 72 cm is set as the better distance of axis between neutron generator and detector. Finally, by comparing with the previous experimental results, the Mean Absolute Percentage Error of element with the value less than 1% is improved after device optimization by SNR evaluation.", 
        "genre": "research_article", 
        "id": "sg:pub.10.1007/s10967-018-6173-x", 
        "inLanguage": [
          "en"
        ], 
        "isAccessibleForFree": false, 
        "isPartOf": [
          {
            "id": "sg:journal.1094634", 
            "issn": [
              "0236-5731", 
              "1588-2780"
            ], 
            "name": "Journal of Radioanalytical and Nuclear Chemistry", 
            "type": "Periodical"
          }, 
          {
            "issueNumber": "2", 
            "type": "PublicationIssue"
          }, 
          {
            "type": "PublicationVolume", 
            "volumeNumber": "318"
          }
        ], 
        "name": "The optimization of coal on-line analysis system based on signal-to-noise ratio evaluation", 
        "pagination": "1279-1286", 
        "productId": [
          {
            "name": "readcube_id", 
            "type": "PropertyValue", 
            "value": [
              "b849ce04eb6a9516dff143696a7d74c4b689214a84537095a09f2c91e74e1f56"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1007/s10967-018-6173-x"
            ]
          }, 
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1106705816"
            ]
          }
        ], 
        "sameAs": [
          "https://doi.org/10.1007/s10967-018-6173-x", 
          "https://app.dimensions.ai/details/publication/pub.1106705816"
        ], 
        "sdDataset": "articles", 
        "sdDatePublished": "2019-04-10T16:50", 
        "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_8669_00000562.jsonl", 
        "type": "ScholarlyArticle", 
        "url": "https://link.springer.com/10.1007%2Fs10967-018-6173-x"
      }
    ]
     

    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/s10967-018-6173-x'

    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/s10967-018-6173-x'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s10967-018-6173-x'

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

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s10967-018-6173-x'


     

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

    150 TRIPLES      21 PREDICATES      44 URIs      19 LITERALS      7 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1007/s10967-018-6173-x schema:about anzsrc-for:01
    2 anzsrc-for:0103
    3 schema:author Nc0911cb69cd04564afb24fce5c541cdf
    4 schema:citation sg:pub.10.1007/s10967-012-2045-y
    5 sg:pub.10.1007/s10967-015-3962-3
    6 sg:pub.10.1007/s10967-016-4767-8
    7 https://doi.org/10.1016/j.apradiso.2010.11.014
    8 https://doi.org/10.1016/j.apradiso.2014.11.005
    9 https://doi.org/10.1016/j.apradiso.2016.03.019
    10 https://doi.org/10.1016/j.nima.2015.07.063
    11 https://doi.org/10.1016/j.nimb.2004.05.038
    12 https://doi.org/10.1016/j.nimb.2007.04.238
    13 https://doi.org/10.1016/j.nimb.2010.10.006
    14 https://doi.org/10.1016/j.nimb.2014.10.010
    15 https://doi.org/10.1016/j.radphyschem.2009.04.023
    16 https://doi.org/10.1016/s0168-9002(03)01123-9
    17 https://doi.org/10.1016/s0969-8043(00)00206-2
    18 https://doi.org/10.1063/1.1844472
    19 https://doi.org/10.13182/nse05-a2556
    20 https://doi.org/10.13182/nse07-a2652
    21 schema:datePublished 2018-11
    22 schema:datePublishedReg 2018-11-01
    23 schema:description In the present study, the coal on-line analysis system is optimized, and the signal-to-noise ratio (SNR) is quantified and set as the evaluation criterion for device optimization. 3 cm lead with 3 cm polyethylene is set as moderator, and 13 cm lead is for a better shielding. Besides, the neutron generator is set at the center of device, and 72 cm is set as the better distance of axis between neutron generator and detector. Finally, by comparing with the previous experimental results, the Mean Absolute Percentage Error of element with the value less than 1% is improved after device optimization by SNR evaluation.
    24 schema:genre research_article
    25 schema:inLanguage en
    26 schema:isAccessibleForFree false
    27 schema:isPartOf N373efb5a23ca413180877595c6166ae6
    28 N69ecacf0802a412ca2ecb335808d80cb
    29 sg:journal.1094634
    30 schema:name The optimization of coal on-line analysis system based on signal-to-noise ratio evaluation
    31 schema:pagination 1279-1286
    32 schema:productId N1210b5728fa2436385c4d4c0cd8da6b0
    33 Ncaf5a6f0076345048e2814ef432db2e5
    34 Nf7ec1f4762d840c2b6af70ab4be4d043
    35 schema:sameAs https://app.dimensions.ai/details/publication/pub.1106705816
    36 https://doi.org/10.1007/s10967-018-6173-x
    37 schema:sdDatePublished 2019-04-10T16:50
    38 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    39 schema:sdPublisher N646c3e5412de4187afcae43627539761
    40 schema:url https://link.springer.com/10.1007%2Fs10967-018-6173-x
    41 sgo:license sg:explorer/license/
    42 sgo:sdDataset articles
    43 rdf:type schema:ScholarlyArticle
    44 N1210b5728fa2436385c4d4c0cd8da6b0 schema:name dimensions_id
    45 schema:value pub.1106705816
    46 rdf:type schema:PropertyValue
    47 N12ed8fcd170f4916ada701eb37ed8f1f rdf:first sg:person.010512173621.38
    48 rdf:rest Nf7e00603e124406088597f58646bac60
    49 N373efb5a23ca413180877595c6166ae6 schema:volumeNumber 318
    50 rdf:type schema:PublicationVolume
    51 N646c3e5412de4187afcae43627539761 schema:name Springer Nature - SN SciGraph project
    52 rdf:type schema:Organization
    53 N66cf35b1d09f4aeb894e0c1b0352f33f rdf:first sg:person.01136640362.24
    54 rdf:rest Nbf7b09c3f585485da354fb143b4e5c91
    55 N69ecacf0802a412ca2ecb335808d80cb schema:issueNumber 2
    56 rdf:type schema:PublicationIssue
    57 N979602d0b65c42b2b397cd6fb7fc9766 rdf:first sg:person.01256220355.94
    58 rdf:rest N12ed8fcd170f4916ada701eb37ed8f1f
    59 Nad568e419aaf45a498a9db3252945aea schema:affiliation https://www.grid.ac/institutes/grid.64938.30
    60 schema:familyName Tang
    61 schema:givenName Yajun
    62 rdf:type schema:Person
    63 Nbf7b09c3f585485da354fb143b4e5c91 rdf:first Nad568e419aaf45a498a9db3252945aea
    64 rdf:rest rdf:nil
    65 Nc0911cb69cd04564afb24fce5c541cdf rdf:first sg:person.016477246610.91
    66 rdf:rest N979602d0b65c42b2b397cd6fb7fc9766
    67 Ncaf5a6f0076345048e2814ef432db2e5 schema:name readcube_id
    68 schema:value b849ce04eb6a9516dff143696a7d74c4b689214a84537095a09f2c91e74e1f56
    69 rdf:type schema:PropertyValue
    70 Nf7e00603e124406088597f58646bac60 rdf:first sg:person.0775462633.45
    71 rdf:rest N66cf35b1d09f4aeb894e0c1b0352f33f
    72 Nf7ec1f4762d840c2b6af70ab4be4d043 schema:name doi
    73 schema:value 10.1007/s10967-018-6173-x
    74 rdf:type schema:PropertyValue
    75 anzsrc-for:01 schema:inDefinedTermSet anzsrc-for:
    76 schema:name Mathematical Sciences
    77 rdf:type schema:DefinedTerm
    78 anzsrc-for:0103 schema:inDefinedTermSet anzsrc-for:
    79 schema:name Numerical and Computational Mathematics
    80 rdf:type schema:DefinedTerm
    81 sg:journal.1094634 schema:issn 0236-5731
    82 1588-2780
    83 schema:name Journal of Radioanalytical and Nuclear Chemistry
    84 rdf:type schema:Periodical
    85 sg:person.010512173621.38 schema:affiliation https://www.grid.ac/institutes/grid.64938.30
    86 schema:familyName Hei
    87 schema:givenName DaQian
    88 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010512173621.38
    89 rdf:type schema:Person
    90 sg:person.01136640362.24 schema:affiliation https://www.grid.ac/institutes/grid.64938.30
    91 schema:familyName Cheng
    92 schema:givenName Can
    93 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01136640362.24
    94 rdf:type schema:Person
    95 sg:person.01256220355.94 schema:affiliation https://www.grid.ac/institutes/grid.64938.30
    96 schema:familyName Jia
    97 schema:givenName WenBao
    98 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01256220355.94
    99 rdf:type schema:Person
    100 sg:person.016477246610.91 schema:affiliation https://www.grid.ac/institutes/grid.64938.30
    101 schema:familyName Li
    102 schema:givenName JiaTong
    103 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016477246610.91
    104 rdf:type schema:Person
    105 sg:person.0775462633.45 schema:affiliation https://www.grid.ac/institutes/grid.64938.30
    106 schema:familyName Cai
    107 schema:givenName PingKun
    108 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0775462633.45
    109 rdf:type schema:Person
    110 sg:pub.10.1007/s10967-012-2045-y schema:sameAs https://app.dimensions.ai/details/publication/pub.1008543093
    111 https://doi.org/10.1007/s10967-012-2045-y
    112 rdf:type schema:CreativeWork
    113 sg:pub.10.1007/s10967-015-3962-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012410089
    114 https://doi.org/10.1007/s10967-015-3962-3
    115 rdf:type schema:CreativeWork
    116 sg:pub.10.1007/s10967-016-4767-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053080360
    117 https://doi.org/10.1007/s10967-016-4767-8
    118 rdf:type schema:CreativeWork
    119 https://doi.org/10.1016/j.apradiso.2010.11.014 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045936911
    120 rdf:type schema:CreativeWork
    121 https://doi.org/10.1016/j.apradiso.2014.11.005 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022009299
    122 rdf:type schema:CreativeWork
    123 https://doi.org/10.1016/j.apradiso.2016.03.019 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026370621
    124 rdf:type schema:CreativeWork
    125 https://doi.org/10.1016/j.nima.2015.07.063 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020595796
    126 rdf:type schema:CreativeWork
    127 https://doi.org/10.1016/j.nimb.2004.05.038 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014755780
    128 rdf:type schema:CreativeWork
    129 https://doi.org/10.1016/j.nimb.2007.04.238 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051096600
    130 rdf:type schema:CreativeWork
    131 https://doi.org/10.1016/j.nimb.2010.10.006 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048924753
    132 rdf:type schema:CreativeWork
    133 https://doi.org/10.1016/j.nimb.2014.10.010 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013265562
    134 rdf:type schema:CreativeWork
    135 https://doi.org/10.1016/j.radphyschem.2009.04.023 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017608173
    136 rdf:type schema:CreativeWork
    137 https://doi.org/10.1016/s0168-9002(03)01123-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014599007
    138 rdf:type schema:CreativeWork
    139 https://doi.org/10.1016/s0969-8043(00)00206-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037823892
    140 rdf:type schema:CreativeWork
    141 https://doi.org/10.1063/1.1844472 schema:sameAs https://app.dimensions.ai/details/publication/pub.1057827092
    142 rdf:type schema:CreativeWork
    143 https://doi.org/10.13182/nse05-a2556 schema:sameAs https://app.dimensions.ai/details/publication/pub.1091174530
    144 rdf:type schema:CreativeWork
    145 https://doi.org/10.13182/nse07-a2652 schema:sameAs https://app.dimensions.ai/details/publication/pub.1091174612
    146 rdf:type schema:CreativeWork
    147 https://www.grid.ac/institutes/grid.64938.30 schema:alternateName Nanjing University of Aeronautics and Astronautics
    148 schema:name Collaborative Innovation Center of Radiation Medicine of Jiangsu Higher Education Institutions, 215000, Suzhou, China
    149 Department of Nuclear Science and Engineering, College of Materials Science and Engineering, Nanjing University of Aeronautics and Astronautics, 211106, Nanjing, China
    150 rdf:type schema:Organization
     




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


    ...