Low-field electron mobility evaluation in silicon nanowire transistors using an extended hydrodynamic model View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2018-12

AUTHORS

Orazio Muscato, Tina Castiglione, Vincenza Di Stefano, Armando Coco

ABSTRACT

Silicon nanowires (SiNWs) are quasi-one-dimensional structures in which electrons are spatially confined in two directions and they are free to move in the orthogonal direction. The subband decomposition and the electrostatic force field are obtained by solving the Schrödinger–Poisson coupled system. The electron transport along the free direction can be tackled using a hydrodynamic model, formulated by taking the moments of the multisubband Boltzmann equation. We shall introduce an extended hydrodynamic model where closure relations for the fluxes and production terms have been obtained by means of the Maximum Entropy Principle of Extended Thermodynamics, and in which the main scattering mechanisms such as those with phonons and surface roughness have been considered. By using this model, the low-field mobility of a Gate-All-Around SiNW transistor has been evaluated. More... »

PAGES

14

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/s13362-018-0056-1

DOI

http://dx.doi.org/10.1186/s13362-018-0056-1

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1110465241


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": "University of Catania", 
          "id": "https://www.grid.ac/institutes/grid.8158.4", 
          "name": [
            "Department of Mathematics and Computer Science, University of Catania, Catania, Italy"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Muscato", 
        "givenName": "Orazio", 
        "id": "sg:person.012236764106.80", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012236764106.80"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Catania", 
          "id": "https://www.grid.ac/institutes/grid.8158.4", 
          "name": [
            "Department of Mathematics and Computer Science, University of Catania, Catania, Italy"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Castiglione", 
        "givenName": "Tina", 
        "id": "sg:person.07627323005.78", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07627323005.78"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Catania", 
          "id": "https://www.grid.ac/institutes/grid.8158.4", 
          "name": [
            "Department of Mathematics and Computer Science, University of Catania, Catania, Italy"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Di Stefano", 
        "givenName": "Vincenza", 
        "id": "sg:person.07432774361.38", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07432774361.38"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Oxford Brookes University", 
          "id": "https://www.grid.ac/institutes/grid.7628.b", 
          "name": [
            "School of Engineering, Computing and Mathematics, Oxford Brookes University, Oxford, UK"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Coco", 
        "givenName": "Armando", 
        "id": "sg:person.010370025231.77", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010370025231.77"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1063/1.2977758", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1001193523"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3390/e19010036", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1002611120"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/s11671-016-1249-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003432658", 
          "https://doi.org/10.1186/s11671-016-1249-4"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/s11671-016-1249-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003432658", 
          "https://doi.org/10.1186/s11671-016-1249-4"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10825-008-0188-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015933839", 
          "https://doi.org/10.1007/s10825-008-0188-4"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevb.84.085313", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017092005"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevb.84.085313", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017092005"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3390/e18100368", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1022821045"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/s11671-016-1396-7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1022890337", 
          "https://doi.org/10.1186/s11671-016-1396-7"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/s11671-016-1396-7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1022890337", 
          "https://doi.org/10.1186/s11671-016-1396-7"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1063/1.4946754", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1026251765"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10825-008-0238-y", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027329491", 
          "https://doi.org/10.1007/s10825-008-0238-y"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jcp.2012.11.047", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029551976"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1088/0957-4484/18/31/315202", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034390392"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3390/s140100245", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1038393670"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10825-010-0341-8", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039229913", 
          "https://doi.org/10.1007/s10825-010-0341-8"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10825-010-0341-8", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039229913", 
          "https://doi.org/10.1007/s10825-010-0341-8"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.sse.2006.03.041", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1049753104"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/nl300930m", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1056219343"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/nl9034384", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1056222271"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/nl9034384", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1056222271"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1063/1.2001158", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1057835315"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1063/1.2802586", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1057868531"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1063/1.3650249", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1057991808"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1063/1.365396", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1057992570"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1063/1.4842835", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1058087168"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/led.2006.873381", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061353358"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/ted.2005.848077", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061591633"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/ted.2005.850945", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061591714"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/ted.2007.902712", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061592610"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/ted.2007.902901", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061592630"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/ted.2007.909206", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061592750"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/ted.2007.913560", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061592836"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/ted.2008.920233", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061593123"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/ted.2008.926230", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061593198"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/ted.2010.2078821", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061594076"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3762/bjnano.5.141", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1071378710"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/23324309.2017.1318402", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1090218615"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/iedm.2002.1175936", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1094449739"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1109503086", 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1109503086", 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2018-12", 
    "datePublishedReg": "2018-12-01", 
    "description": "Silicon nanowires (SiNWs) are quasi-one-dimensional structures in which electrons are spatially confined in two directions and they are free to move in the orthogonal direction. The subband decomposition and the electrostatic force field are obtained by solving the Schr\u00f6dinger\u2013Poisson coupled system. The electron transport along the free direction can be tackled using a hydrodynamic model, formulated by taking the moments of the multisubband Boltzmann equation. We shall introduce an extended hydrodynamic model where closure relations for the fluxes and production terms have been obtained by means of the Maximum Entropy Principle of Extended Thermodynamics, and in which the main scattering mechanisms such as those with phonons and surface roughness have been considered. By using this model, the low-field mobility of a Gate-All-Around SiNW transistor has been evaluated.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1186/s13362-018-0056-1", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": true, 
    "isPartOf": [
      {
        "id": "sg:journal.1136389", 
        "issn": [
          "2190-5983"
        ], 
        "name": "Journal of Mathematics in Industry", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "8"
      }
    ], 
    "name": "Low-field electron mobility evaluation in silicon nanowire transistors using an extended hydrodynamic model", 
    "pagination": "14", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "aa570ba22c69076839399bd384a39503facf491e15d58c900b04bfc32b6d2418"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1186/s13362-018-0056-1"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1110465241"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1186/s13362-018-0056-1", 
      "https://app.dimensions.ai/details/publication/pub.1110465241"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T08:20", 
    "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/v90/0000000290_0000000290/records_34892_00000000.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://link.springer.com/10.1186%2Fs13362-018-0056-1"
  }
]
 

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.10.1186/s13362-018-0056-1'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/s13362-018-0056-1'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/s13362-018-0056-1'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/s13362-018-0056-1'


 

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

193 TRIPLES      21 PREDICATES      62 URIs      19 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1186/s13362-018-0056-1 schema:about anzsrc-for:09
2 anzsrc-for:0912
3 schema:author N5a6ea746499c4886b10f93bbbdeffe9d
4 schema:citation sg:pub.10.1007/s10825-008-0188-4
5 sg:pub.10.1007/s10825-008-0238-y
6 sg:pub.10.1007/s10825-010-0341-8
7 sg:pub.10.1186/s11671-016-1249-4
8 sg:pub.10.1186/s11671-016-1396-7
9 https://app.dimensions.ai/details/publication/pub.1109503086
10 https://doi.org/10.1016/j.jcp.2012.11.047
11 https://doi.org/10.1016/j.sse.2006.03.041
12 https://doi.org/10.1021/nl300930m
13 https://doi.org/10.1021/nl9034384
14 https://doi.org/10.1063/1.2001158
15 https://doi.org/10.1063/1.2802586
16 https://doi.org/10.1063/1.2977758
17 https://doi.org/10.1063/1.3650249
18 https://doi.org/10.1063/1.365396
19 https://doi.org/10.1063/1.4842835
20 https://doi.org/10.1063/1.4946754
21 https://doi.org/10.1080/23324309.2017.1318402
22 https://doi.org/10.1088/0957-4484/18/31/315202
23 https://doi.org/10.1103/physrevb.84.085313
24 https://doi.org/10.1109/iedm.2002.1175936
25 https://doi.org/10.1109/led.2006.873381
26 https://doi.org/10.1109/ted.2005.848077
27 https://doi.org/10.1109/ted.2005.850945
28 https://doi.org/10.1109/ted.2007.902712
29 https://doi.org/10.1109/ted.2007.902901
30 https://doi.org/10.1109/ted.2007.909206
31 https://doi.org/10.1109/ted.2007.913560
32 https://doi.org/10.1109/ted.2008.920233
33 https://doi.org/10.1109/ted.2008.926230
34 https://doi.org/10.1109/ted.2010.2078821
35 https://doi.org/10.3390/e18100368
36 https://doi.org/10.3390/e19010036
37 https://doi.org/10.3390/s140100245
38 https://doi.org/10.3762/bjnano.5.141
39 schema:datePublished 2018-12
40 schema:datePublishedReg 2018-12-01
41 schema:description Silicon nanowires (SiNWs) are quasi-one-dimensional structures in which electrons are spatially confined in two directions and they are free to move in the orthogonal direction. The subband decomposition and the electrostatic force field are obtained by solving the Schrödinger–Poisson coupled system. The electron transport along the free direction can be tackled using a hydrodynamic model, formulated by taking the moments of the multisubband Boltzmann equation. We shall introduce an extended hydrodynamic model where closure relations for the fluxes and production terms have been obtained by means of the Maximum Entropy Principle of Extended Thermodynamics, and in which the main scattering mechanisms such as those with phonons and surface roughness have been considered. By using this model, the low-field mobility of a Gate-All-Around SiNW transistor has been evaluated.
42 schema:genre research_article
43 schema:inLanguage en
44 schema:isAccessibleForFree true
45 schema:isPartOf Na25dbdd8533c4082a3fc64d8ce4d2d90
46 Nd81b5f3ecc4949c4bf2308f7fb31717a
47 sg:journal.1136389
48 schema:name Low-field electron mobility evaluation in silicon nanowire transistors using an extended hydrodynamic model
49 schema:pagination 14
50 schema:productId Nb968b88a744b45ad8a5e7a5f1f94d1dd
51 Nc9e93025624d4e178ef10452938e6a96
52 Nca6f3d3d226f46558baeacaae0aae1ec
53 schema:sameAs https://app.dimensions.ai/details/publication/pub.1110465241
54 https://doi.org/10.1186/s13362-018-0056-1
55 schema:sdDatePublished 2019-04-11T08:20
56 schema:sdLicense https://scigraph.springernature.com/explorer/license/
57 schema:sdPublisher Ne503aa15c5be4ae1be62f1b3cb6b579d
58 schema:url https://link.springer.com/10.1186%2Fs13362-018-0056-1
59 sgo:license sg:explorer/license/
60 sgo:sdDataset articles
61 rdf:type schema:ScholarlyArticle
62 N28e14f1681854260adbdaba59e4bd50d rdf:first sg:person.07627323005.78
63 rdf:rest N6f97d3a5d839465a8c57acefea59d77e
64 N366a4d5f1a6f4ef5a7d2032172283070 rdf:first sg:person.010370025231.77
65 rdf:rest rdf:nil
66 N5a6ea746499c4886b10f93bbbdeffe9d rdf:first sg:person.012236764106.80
67 rdf:rest N28e14f1681854260adbdaba59e4bd50d
68 N6f97d3a5d839465a8c57acefea59d77e rdf:first sg:person.07432774361.38
69 rdf:rest N366a4d5f1a6f4ef5a7d2032172283070
70 Na25dbdd8533c4082a3fc64d8ce4d2d90 schema:issueNumber 1
71 rdf:type schema:PublicationIssue
72 Nb968b88a744b45ad8a5e7a5f1f94d1dd schema:name dimensions_id
73 schema:value pub.1110465241
74 rdf:type schema:PropertyValue
75 Nc9e93025624d4e178ef10452938e6a96 schema:name readcube_id
76 schema:value aa570ba22c69076839399bd384a39503facf491e15d58c900b04bfc32b6d2418
77 rdf:type schema:PropertyValue
78 Nca6f3d3d226f46558baeacaae0aae1ec schema:name doi
79 schema:value 10.1186/s13362-018-0056-1
80 rdf:type schema:PropertyValue
81 Nd81b5f3ecc4949c4bf2308f7fb31717a schema:volumeNumber 8
82 rdf:type schema:PublicationVolume
83 Ne503aa15c5be4ae1be62f1b3cb6b579d schema:name Springer Nature - SN SciGraph project
84 rdf:type schema:Organization
85 anzsrc-for:09 schema:inDefinedTermSet anzsrc-for:
86 schema:name Engineering
87 rdf:type schema:DefinedTerm
88 anzsrc-for:0912 schema:inDefinedTermSet anzsrc-for:
89 schema:name Materials Engineering
90 rdf:type schema:DefinedTerm
91 sg:journal.1136389 schema:issn 2190-5983
92 schema:name Journal of Mathematics in Industry
93 rdf:type schema:Periodical
94 sg:person.010370025231.77 schema:affiliation https://www.grid.ac/institutes/grid.7628.b
95 schema:familyName Coco
96 schema:givenName Armando
97 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010370025231.77
98 rdf:type schema:Person
99 sg:person.012236764106.80 schema:affiliation https://www.grid.ac/institutes/grid.8158.4
100 schema:familyName Muscato
101 schema:givenName Orazio
102 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012236764106.80
103 rdf:type schema:Person
104 sg:person.07432774361.38 schema:affiliation https://www.grid.ac/institutes/grid.8158.4
105 schema:familyName Di Stefano
106 schema:givenName Vincenza
107 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07432774361.38
108 rdf:type schema:Person
109 sg:person.07627323005.78 schema:affiliation https://www.grid.ac/institutes/grid.8158.4
110 schema:familyName Castiglione
111 schema:givenName Tina
112 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07627323005.78
113 rdf:type schema:Person
114 sg:pub.10.1007/s10825-008-0188-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015933839
115 https://doi.org/10.1007/s10825-008-0188-4
116 rdf:type schema:CreativeWork
117 sg:pub.10.1007/s10825-008-0238-y schema:sameAs https://app.dimensions.ai/details/publication/pub.1027329491
118 https://doi.org/10.1007/s10825-008-0238-y
119 rdf:type schema:CreativeWork
120 sg:pub.10.1007/s10825-010-0341-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039229913
121 https://doi.org/10.1007/s10825-010-0341-8
122 rdf:type schema:CreativeWork
123 sg:pub.10.1186/s11671-016-1249-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003432658
124 https://doi.org/10.1186/s11671-016-1249-4
125 rdf:type schema:CreativeWork
126 sg:pub.10.1186/s11671-016-1396-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022890337
127 https://doi.org/10.1186/s11671-016-1396-7
128 rdf:type schema:CreativeWork
129 https://app.dimensions.ai/details/publication/pub.1109503086 schema:CreativeWork
130 https://doi.org/10.1016/j.jcp.2012.11.047 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029551976
131 rdf:type schema:CreativeWork
132 https://doi.org/10.1016/j.sse.2006.03.041 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049753104
133 rdf:type schema:CreativeWork
134 https://doi.org/10.1021/nl300930m schema:sameAs https://app.dimensions.ai/details/publication/pub.1056219343
135 rdf:type schema:CreativeWork
136 https://doi.org/10.1021/nl9034384 schema:sameAs https://app.dimensions.ai/details/publication/pub.1056222271
137 rdf:type schema:CreativeWork
138 https://doi.org/10.1063/1.2001158 schema:sameAs https://app.dimensions.ai/details/publication/pub.1057835315
139 rdf:type schema:CreativeWork
140 https://doi.org/10.1063/1.2802586 schema:sameAs https://app.dimensions.ai/details/publication/pub.1057868531
141 rdf:type schema:CreativeWork
142 https://doi.org/10.1063/1.2977758 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001193523
143 rdf:type schema:CreativeWork
144 https://doi.org/10.1063/1.3650249 schema:sameAs https://app.dimensions.ai/details/publication/pub.1057991808
145 rdf:type schema:CreativeWork
146 https://doi.org/10.1063/1.365396 schema:sameAs https://app.dimensions.ai/details/publication/pub.1057992570
147 rdf:type schema:CreativeWork
148 https://doi.org/10.1063/1.4842835 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058087168
149 rdf:type schema:CreativeWork
150 https://doi.org/10.1063/1.4946754 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026251765
151 rdf:type schema:CreativeWork
152 https://doi.org/10.1080/23324309.2017.1318402 schema:sameAs https://app.dimensions.ai/details/publication/pub.1090218615
153 rdf:type schema:CreativeWork
154 https://doi.org/10.1088/0957-4484/18/31/315202 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034390392
155 rdf:type schema:CreativeWork
156 https://doi.org/10.1103/physrevb.84.085313 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017092005
157 rdf:type schema:CreativeWork
158 https://doi.org/10.1109/iedm.2002.1175936 schema:sameAs https://app.dimensions.ai/details/publication/pub.1094449739
159 rdf:type schema:CreativeWork
160 https://doi.org/10.1109/led.2006.873381 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061353358
161 rdf:type schema:CreativeWork
162 https://doi.org/10.1109/ted.2005.848077 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061591633
163 rdf:type schema:CreativeWork
164 https://doi.org/10.1109/ted.2005.850945 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061591714
165 rdf:type schema:CreativeWork
166 https://doi.org/10.1109/ted.2007.902712 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061592610
167 rdf:type schema:CreativeWork
168 https://doi.org/10.1109/ted.2007.902901 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061592630
169 rdf:type schema:CreativeWork
170 https://doi.org/10.1109/ted.2007.909206 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061592750
171 rdf:type schema:CreativeWork
172 https://doi.org/10.1109/ted.2007.913560 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061592836
173 rdf:type schema:CreativeWork
174 https://doi.org/10.1109/ted.2008.920233 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061593123
175 rdf:type schema:CreativeWork
176 https://doi.org/10.1109/ted.2008.926230 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061593198
177 rdf:type schema:CreativeWork
178 https://doi.org/10.1109/ted.2010.2078821 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061594076
179 rdf:type schema:CreativeWork
180 https://doi.org/10.3390/e18100368 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022821045
181 rdf:type schema:CreativeWork
182 https://doi.org/10.3390/e19010036 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002611120
183 rdf:type schema:CreativeWork
184 https://doi.org/10.3390/s140100245 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038393670
185 rdf:type schema:CreativeWork
186 https://doi.org/10.3762/bjnano.5.141 schema:sameAs https://app.dimensions.ai/details/publication/pub.1071378710
187 rdf:type schema:CreativeWork
188 https://www.grid.ac/institutes/grid.7628.b schema:alternateName Oxford Brookes University
189 schema:name School of Engineering, Computing and Mathematics, Oxford Brookes University, Oxford, UK
190 rdf:type schema:Organization
191 https://www.grid.ac/institutes/grid.8158.4 schema:alternateName University of Catania
192 schema:name Department of Mathematics and Computer Science, University of Catania, Catania, Italy
193 rdf:type schema:Organization
 




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


...