Current-limiting challenges for all-spin logic devices View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2015-10-09

AUTHORS

Li Su, Youguang Zhang, Jacques-Olivier Klein, Yue Zhang, Arnaud Bournel, Albert Fert, Weisheng Zhao

ABSTRACT

All-spin logic device (ASLD) has attracted increasing interests as one of the most promising post-CMOS device candidates, thanks to its low power, non-volatility and logic-in-memory structure. Here we investigate the key current-limiting factors and develop a physics-based model of ASLD through nano-magnet switching, the spin transport properties and the breakdown characteristic of channel. First, ASLD with perpendicular magnetic anisotropy (PMA) nano-magnet is proposed to reduce the critical current (Ic0). Most important, the spin transport efficiency can be enhanced by analyzing the device structure, dimension, contact resistance as well as material parameters. Furthermore, breakdown current density (JBR) of spin channel is studied for the upper current limitation. As a result, we can deduce current-limiting conditions and estimate energy dissipation. Based on the model, we demonstrate ASLD with different structures and channel materials (graphene and copper). Asymmetric structure is found to be the optimal option for current limitations. Copper channel outperforms graphene in term of energy but seriously suffers from breakdown current limit. By exploring the current limit and performance tradeoffs, the optimization of ASLD is also discussed. This benchmarking model of ASLD opens up new prospects for design and implementation of future spintronics applications. More... »

PAGES

14905

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/srep14905

DOI

http://dx.doi.org/10.1038/srep14905

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1016880494

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/26449410


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": "French National Centre for Scientific Research", 
          "id": "https://www.grid.ac/institutes/grid.4444.0", 
          "name": [
            "Fert Beijing Institute, Univ. Beihang, 100191, Beijing, China", 
            "School of Electrical & Information Engineering, Beihang Univ, Beijing 100191, Peoples R China", 
            "Institut d\u2019Electronique Fondamentale, Univ. Paris-Sud, F-91405 Orsay, France", 
            "UMR 8622, CNRS, F-91405 Orsay, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Su", 
        "givenName": "Li", 
        "id": "sg:person.0664064361.00", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0664064361.00"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Beihang University", 
          "id": "https://www.grid.ac/institutes/grid.64939.31", 
          "name": [
            "Fert Beijing Institute, Univ. Beihang, 100191, Beijing, China", 
            "School of Electrical & Information Engineering, Beihang Univ, Beijing 100191, Peoples R China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Zhang", 
        "givenName": "Youguang", 
        "id": "sg:person.011121515023.92", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011121515023.92"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "French National Centre for Scientific Research", 
          "id": "https://www.grid.ac/institutes/grid.4444.0", 
          "name": [
            "Institut d\u2019Electronique Fondamentale, Univ. Paris-Sud, F-91405 Orsay, France", 
            "UMR 8622, CNRS, F-91405 Orsay, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Klein", 
        "givenName": "Jacques-Olivier", 
        "id": "sg:person.01350004514.92", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01350004514.92"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Beihang University", 
          "id": "https://www.grid.ac/institutes/grid.64939.31", 
          "name": [
            "Fert Beijing Institute, Univ. Beihang, 100191, Beijing, China", 
            "School of Electrical & Information Engineering, Beihang Univ, Beijing 100191, Peoples R China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Zhang", 
        "givenName": "Yue", 
        "id": "sg:person.013070747175.57", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013070747175.57"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "French National Centre for Scientific Research", 
          "id": "https://www.grid.ac/institutes/grid.4444.0", 
          "name": [
            "Institut d\u2019Electronique Fondamentale, Univ. Paris-Sud, F-91405 Orsay, France", 
            "UMR 8622, CNRS, F-91405 Orsay, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Bournel", 
        "givenName": "Arnaud", 
        "id": "sg:person.01073224027.37", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01073224027.37"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Unit\u00e9 Mixte de Physique CNRS/Thales", 
          "id": "https://www.grid.ac/institutes/grid.462731.5", 
          "name": [
            "Fert Beijing Institute, Univ. Beihang, 100191, Beijing, China", 
            "School of Electrical & Information Engineering, Beihang Univ, Beijing 100191, Peoples R China", 
            "Unit\u00e9 Mixte de Physique CNRS-Thales, F-91767 Palaiseau, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Fert", 
        "givenName": "Albert", 
        "id": "sg:person.01223731431.19", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01223731431.19"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "French National Centre for Scientific Research", 
          "id": "https://www.grid.ac/institutes/grid.4444.0", 
          "name": [
            "Fert Beijing Institute, Univ. Beihang, 100191, Beijing, China", 
            "School of Electrical & Information Engineering, Beihang Univ, Beijing 100191, Peoples R China", 
            "Institut d\u2019Electronique Fondamentale, Univ. Paris-Sud, F-91405 Orsay, France", 
            "UMR 8622, CNRS, F-91405 Orsay, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Zhao", 
        "givenName": "Weisheng", 
        "id": "sg:person.016636512717.27", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016636512717.27"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1063/1.4913303", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1001741894"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1063/1.4892924", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1002068914"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nmat2024", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1002220407", 
          "https://doi.org/10.1038/nmat2024"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevb.67.052409", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003482526"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevb.67.052409", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003482526"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/35066533", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006965625", 
          "https://doi.org/10.1038/35066533"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/35066533", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006965625", 
          "https://doi.org/10.1038/35066533"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/revmodphys.76.323", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007326605"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/revmodphys.76.323", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007326605"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0304-8853(96)00062-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007328853"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nnano.2008.1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007469159", 
          "https://doi.org/10.1038/nnano.2008.1"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jmmm.2011.08.001", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007574650"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1063/1.3147183", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1010631524"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevb.62.r4790", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012531780"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevb.62.r4790", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012531780"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nmat3046", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1018724173", 
          "https://doi.org/10.1038/nmat3046"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/nl300584r", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1021511021"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/nl204545q", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1021683789"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nnano.2010.31", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1022452901", 
          "https://doi.org/10.1038/nnano.2010.31"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nnano.2010.31", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1022452901", 
          "https://doi.org/10.1038/nnano.2010.31"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1126/science.1065389", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1024794148"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevlett.106.256801", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1028050463"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevlett.106.256801", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1028050463"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1063/1.3567772", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030443313"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/416713a", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032410236", 
          "https://doi.org/10.1038/416713a"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/416713a", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032410236", 
          "https://doi.org/10.1038/416713a"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1063/1.3491804", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1043814591"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nnano.2014.214", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1043969832", 
          "https://doi.org/10.1038/nnano.2014.214"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nature05833", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048657821", 
          "https://doi.org/10.1038/nature05833"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevb.62.r16267", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052651266"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevb.62.r16267", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052651266"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nmat1849", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052791836", 
          "https://doi.org/10.1038/nmat1849"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/nl204236u", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1056219144"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/nl402547m", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1056220271"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/nn500533b", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1056225922"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1063/1.1371251", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1057699998"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1063/1.1834982", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1057825711"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1063/1.3056141", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1057901479"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1063/1.322842", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1057921413"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1063/1.367113", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1057996537"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevb.54.9353", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1060582968"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevb.54.9353", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1060582968"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevb.64.184420", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1060601205"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevb.64.184420", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1060601205"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevb.88.104426", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1060642141"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevb.88.104426", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1060642141"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevlett.96.037201", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1060831600"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevlett.96.037201", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1060831600"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/5.573737", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061179702"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/jproc.2014.2361767", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061297970"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/mc.2003.1250885", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061386903"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2015-10-09", 
    "datePublishedReg": "2015-10-09", 
    "description": "All-spin logic device (ASLD) has attracted increasing interests as one of the most promising post-CMOS device candidates, thanks to its low power, non-volatility and logic-in-memory structure. Here we investigate the key current-limiting factors and develop a physics-based model of ASLD through nano-magnet switching, the spin transport properties and the breakdown characteristic of channel. First, ASLD with perpendicular magnetic anisotropy (PMA) nano-magnet is proposed to reduce the critical current (Ic0). Most important, the spin transport efficiency can be enhanced by analyzing the device structure, dimension, contact resistance as well as material parameters. Furthermore, breakdown current density (JBR) of spin channel is studied for the upper current limitation. As a result, we can deduce current-limiting conditions and estimate energy dissipation. Based on the model, we demonstrate ASLD with different structures and channel materials (graphene and copper). Asymmetric structure is found to be the optimal option for current limitations. Copper channel outperforms graphene in term of energy but seriously suffers from breakdown current limit. By exploring the current limit and performance tradeoffs, the optimization of ASLD is also discussed. This benchmarking model of ASLD opens up new prospects for design and implementation of future spintronics applications. ", 
    "genre": "research_article", 
    "id": "sg:pub.10.1038/srep14905", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": true, 
    "isPartOf": [
      {
        "id": "sg:journal.1045337", 
        "issn": [
          "2045-2322"
        ], 
        "name": "Scientific Reports", 
        "type": "Periodical"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "5"
      }
    ], 
    "name": "Current-limiting challenges for all-spin logic devices", 
    "pagination": "14905", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "506da7b68ccd08602a40a1cd0ad7d4bf24e5f7bfbdbdf9e74aff9c67ebbf28ea"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "26449410"
        ]
      }, 
      {
        "name": "nlm_unique_id", 
        "type": "PropertyValue", 
        "value": [
          "101563288"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1038/srep14905"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1016880494"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1038/srep14905", 
      "https://app.dimensions.ai/details/publication/pub.1016880494"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-10T19:45", 
    "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_8681_00000424.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "http://www.nature.com/srep/2015/151009/srep14905/full/srep14905.html"
  }
]
 

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.10.1038/srep14905'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1038/srep14905'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1038/srep14905'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1038/srep14905'


 

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

245 TRIPLES      21 PREDICATES      66 URIs      19 LITERALS      8 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1038/srep14905 schema:about anzsrc-for:09
2 anzsrc-for:0912
3 schema:author N519aa0500a974505a7aa690c6bd0c6b7
4 schema:citation sg:pub.10.1038/35066533
5 sg:pub.10.1038/416713a
6 sg:pub.10.1038/nature05833
7 sg:pub.10.1038/nmat1849
8 sg:pub.10.1038/nmat2024
9 sg:pub.10.1038/nmat3046
10 sg:pub.10.1038/nnano.2008.1
11 sg:pub.10.1038/nnano.2010.31
12 sg:pub.10.1038/nnano.2014.214
13 https://doi.org/10.1016/0304-8853(96)00062-5
14 https://doi.org/10.1016/j.jmmm.2011.08.001
15 https://doi.org/10.1021/nl204236u
16 https://doi.org/10.1021/nl204545q
17 https://doi.org/10.1021/nl300584r
18 https://doi.org/10.1021/nl402547m
19 https://doi.org/10.1021/nn500533b
20 https://doi.org/10.1063/1.1371251
21 https://doi.org/10.1063/1.1834982
22 https://doi.org/10.1063/1.3056141
23 https://doi.org/10.1063/1.3147183
24 https://doi.org/10.1063/1.322842
25 https://doi.org/10.1063/1.3491804
26 https://doi.org/10.1063/1.3567772
27 https://doi.org/10.1063/1.367113
28 https://doi.org/10.1063/1.4892924
29 https://doi.org/10.1063/1.4913303
30 https://doi.org/10.1103/physrevb.54.9353
31 https://doi.org/10.1103/physrevb.62.r16267
32 https://doi.org/10.1103/physrevb.62.r4790
33 https://doi.org/10.1103/physrevb.64.184420
34 https://doi.org/10.1103/physrevb.67.052409
35 https://doi.org/10.1103/physrevb.88.104426
36 https://doi.org/10.1103/physrevlett.106.256801
37 https://doi.org/10.1103/physrevlett.96.037201
38 https://doi.org/10.1103/revmodphys.76.323
39 https://doi.org/10.1109/5.573737
40 https://doi.org/10.1109/jproc.2014.2361767
41 https://doi.org/10.1109/mc.2003.1250885
42 https://doi.org/10.1126/science.1065389
43 schema:datePublished 2015-10-09
44 schema:datePublishedReg 2015-10-09
45 schema:description All-spin logic device (ASLD) has attracted increasing interests as one of the most promising post-CMOS device candidates, thanks to its low power, non-volatility and logic-in-memory structure. Here we investigate the key current-limiting factors and develop a physics-based model of ASLD through nano-magnet switching, the spin transport properties and the breakdown characteristic of channel. First, ASLD with perpendicular magnetic anisotropy (PMA) nano-magnet is proposed to reduce the critical current (Ic0). Most important, the spin transport efficiency can be enhanced by analyzing the device structure, dimension, contact resistance as well as material parameters. Furthermore, breakdown current density (JBR) of spin channel is studied for the upper current limitation. As a result, we can deduce current-limiting conditions and estimate energy dissipation. Based on the model, we demonstrate ASLD with different structures and channel materials (graphene and copper). Asymmetric structure is found to be the optimal option for current limitations. Copper channel outperforms graphene in term of energy but seriously suffers from breakdown current limit. By exploring the current limit and performance tradeoffs, the optimization of ASLD is also discussed. This benchmarking model of ASLD opens up new prospects for design and implementation of future spintronics applications.
46 schema:genre research_article
47 schema:inLanguage en
48 schema:isAccessibleForFree true
49 schema:isPartOf N4455508c965a4d55b559af0e9ea19577
50 sg:journal.1045337
51 schema:name Current-limiting challenges for all-spin logic devices
52 schema:pagination 14905
53 schema:productId N36d81cc05b344bddb57b739b97a4a2a0
54 Nbd4dd07addb14862b1a70ea355d7591d
55 Nc36f9bc88fad41a1b4436691db50e6ae
56 Nd666b0a974684b54b538f29e691151c3
57 Ne862e19420bc4814978f190f3bd8884a
58 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016880494
59 https://doi.org/10.1038/srep14905
60 schema:sdDatePublished 2019-04-10T19:45
61 schema:sdLicense https://scigraph.springernature.com/explorer/license/
62 schema:sdPublisher N520bc1a014c74840b44f0c91c1601c95
63 schema:url http://www.nature.com/srep/2015/151009/srep14905/full/srep14905.html
64 sgo:license sg:explorer/license/
65 sgo:sdDataset articles
66 rdf:type schema:ScholarlyArticle
67 N22895ae89cdc4bca8b1709ce5ad8c702 rdf:first sg:person.01223731431.19
68 rdf:rest N7d0fdf71985c4822bae52bbac3b63834
69 N36d81cc05b344bddb57b739b97a4a2a0 schema:name readcube_id
70 schema:value 506da7b68ccd08602a40a1cd0ad7d4bf24e5f7bfbdbdf9e74aff9c67ebbf28ea
71 rdf:type schema:PropertyValue
72 N43d72621a5ce4056bf144f21900b0a10 rdf:first sg:person.01073224027.37
73 rdf:rest N22895ae89cdc4bca8b1709ce5ad8c702
74 N4455508c965a4d55b559af0e9ea19577 schema:volumeNumber 5
75 rdf:type schema:PublicationVolume
76 N519aa0500a974505a7aa690c6bd0c6b7 rdf:first sg:person.0664064361.00
77 rdf:rest Na788847e12c5421fae481725029c2332
78 N520bc1a014c74840b44f0c91c1601c95 schema:name Springer Nature - SN SciGraph project
79 rdf:type schema:Organization
80 N790009f8ece841ef999000a1ac77bee6 rdf:first sg:person.013070747175.57
81 rdf:rest N43d72621a5ce4056bf144f21900b0a10
82 N7d0fdf71985c4822bae52bbac3b63834 rdf:first sg:person.016636512717.27
83 rdf:rest rdf:nil
84 Na788847e12c5421fae481725029c2332 rdf:first sg:person.011121515023.92
85 rdf:rest Nfe1a846960794e51b0820353b38fe172
86 Nbd4dd07addb14862b1a70ea355d7591d schema:name dimensions_id
87 schema:value pub.1016880494
88 rdf:type schema:PropertyValue
89 Nc36f9bc88fad41a1b4436691db50e6ae schema:name doi
90 schema:value 10.1038/srep14905
91 rdf:type schema:PropertyValue
92 Nd666b0a974684b54b538f29e691151c3 schema:name nlm_unique_id
93 schema:value 101563288
94 rdf:type schema:PropertyValue
95 Ne862e19420bc4814978f190f3bd8884a schema:name pubmed_id
96 schema:value 26449410
97 rdf:type schema:PropertyValue
98 Nfe1a846960794e51b0820353b38fe172 rdf:first sg:person.01350004514.92
99 rdf:rest N790009f8ece841ef999000a1ac77bee6
100 anzsrc-for:09 schema:inDefinedTermSet anzsrc-for:
101 schema:name Engineering
102 rdf:type schema:DefinedTerm
103 anzsrc-for:0912 schema:inDefinedTermSet anzsrc-for:
104 schema:name Materials Engineering
105 rdf:type schema:DefinedTerm
106 sg:journal.1045337 schema:issn 2045-2322
107 schema:name Scientific Reports
108 rdf:type schema:Periodical
109 sg:person.01073224027.37 schema:affiliation https://www.grid.ac/institutes/grid.4444.0
110 schema:familyName Bournel
111 schema:givenName Arnaud
112 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01073224027.37
113 rdf:type schema:Person
114 sg:person.011121515023.92 schema:affiliation https://www.grid.ac/institutes/grid.64939.31
115 schema:familyName Zhang
116 schema:givenName Youguang
117 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011121515023.92
118 rdf:type schema:Person
119 sg:person.01223731431.19 schema:affiliation https://www.grid.ac/institutes/grid.462731.5
120 schema:familyName Fert
121 schema:givenName Albert
122 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01223731431.19
123 rdf:type schema:Person
124 sg:person.013070747175.57 schema:affiliation https://www.grid.ac/institutes/grid.64939.31
125 schema:familyName Zhang
126 schema:givenName Yue
127 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013070747175.57
128 rdf:type schema:Person
129 sg:person.01350004514.92 schema:affiliation https://www.grid.ac/institutes/grid.4444.0
130 schema:familyName Klein
131 schema:givenName Jacques-Olivier
132 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01350004514.92
133 rdf:type schema:Person
134 sg:person.016636512717.27 schema:affiliation https://www.grid.ac/institutes/grid.4444.0
135 schema:familyName Zhao
136 schema:givenName Weisheng
137 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016636512717.27
138 rdf:type schema:Person
139 sg:person.0664064361.00 schema:affiliation https://www.grid.ac/institutes/grid.4444.0
140 schema:familyName Su
141 schema:givenName Li
142 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0664064361.00
143 rdf:type schema:Person
144 sg:pub.10.1038/35066533 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006965625
145 https://doi.org/10.1038/35066533
146 rdf:type schema:CreativeWork
147 sg:pub.10.1038/416713a schema:sameAs https://app.dimensions.ai/details/publication/pub.1032410236
148 https://doi.org/10.1038/416713a
149 rdf:type schema:CreativeWork
150 sg:pub.10.1038/nature05833 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048657821
151 https://doi.org/10.1038/nature05833
152 rdf:type schema:CreativeWork
153 sg:pub.10.1038/nmat1849 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052791836
154 https://doi.org/10.1038/nmat1849
155 rdf:type schema:CreativeWork
156 sg:pub.10.1038/nmat2024 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002220407
157 https://doi.org/10.1038/nmat2024
158 rdf:type schema:CreativeWork
159 sg:pub.10.1038/nmat3046 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018724173
160 https://doi.org/10.1038/nmat3046
161 rdf:type schema:CreativeWork
162 sg:pub.10.1038/nnano.2008.1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007469159
163 https://doi.org/10.1038/nnano.2008.1
164 rdf:type schema:CreativeWork
165 sg:pub.10.1038/nnano.2010.31 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022452901
166 https://doi.org/10.1038/nnano.2010.31
167 rdf:type schema:CreativeWork
168 sg:pub.10.1038/nnano.2014.214 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043969832
169 https://doi.org/10.1038/nnano.2014.214
170 rdf:type schema:CreativeWork
171 https://doi.org/10.1016/0304-8853(96)00062-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007328853
172 rdf:type schema:CreativeWork
173 https://doi.org/10.1016/j.jmmm.2011.08.001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007574650
174 rdf:type schema:CreativeWork
175 https://doi.org/10.1021/nl204236u schema:sameAs https://app.dimensions.ai/details/publication/pub.1056219144
176 rdf:type schema:CreativeWork
177 https://doi.org/10.1021/nl204545q schema:sameAs https://app.dimensions.ai/details/publication/pub.1021683789
178 rdf:type schema:CreativeWork
179 https://doi.org/10.1021/nl300584r schema:sameAs https://app.dimensions.ai/details/publication/pub.1021511021
180 rdf:type schema:CreativeWork
181 https://doi.org/10.1021/nl402547m schema:sameAs https://app.dimensions.ai/details/publication/pub.1056220271
182 rdf:type schema:CreativeWork
183 https://doi.org/10.1021/nn500533b schema:sameAs https://app.dimensions.ai/details/publication/pub.1056225922
184 rdf:type schema:CreativeWork
185 https://doi.org/10.1063/1.1371251 schema:sameAs https://app.dimensions.ai/details/publication/pub.1057699998
186 rdf:type schema:CreativeWork
187 https://doi.org/10.1063/1.1834982 schema:sameAs https://app.dimensions.ai/details/publication/pub.1057825711
188 rdf:type schema:CreativeWork
189 https://doi.org/10.1063/1.3056141 schema:sameAs https://app.dimensions.ai/details/publication/pub.1057901479
190 rdf:type schema:CreativeWork
191 https://doi.org/10.1063/1.3147183 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010631524
192 rdf:type schema:CreativeWork
193 https://doi.org/10.1063/1.322842 schema:sameAs https://app.dimensions.ai/details/publication/pub.1057921413
194 rdf:type schema:CreativeWork
195 https://doi.org/10.1063/1.3491804 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043814591
196 rdf:type schema:CreativeWork
197 https://doi.org/10.1063/1.3567772 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030443313
198 rdf:type schema:CreativeWork
199 https://doi.org/10.1063/1.367113 schema:sameAs https://app.dimensions.ai/details/publication/pub.1057996537
200 rdf:type schema:CreativeWork
201 https://doi.org/10.1063/1.4892924 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002068914
202 rdf:type schema:CreativeWork
203 https://doi.org/10.1063/1.4913303 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001741894
204 rdf:type schema:CreativeWork
205 https://doi.org/10.1103/physrevb.54.9353 schema:sameAs https://app.dimensions.ai/details/publication/pub.1060582968
206 rdf:type schema:CreativeWork
207 https://doi.org/10.1103/physrevb.62.r16267 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052651266
208 rdf:type schema:CreativeWork
209 https://doi.org/10.1103/physrevb.62.r4790 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012531780
210 rdf:type schema:CreativeWork
211 https://doi.org/10.1103/physrevb.64.184420 schema:sameAs https://app.dimensions.ai/details/publication/pub.1060601205
212 rdf:type schema:CreativeWork
213 https://doi.org/10.1103/physrevb.67.052409 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003482526
214 rdf:type schema:CreativeWork
215 https://doi.org/10.1103/physrevb.88.104426 schema:sameAs https://app.dimensions.ai/details/publication/pub.1060642141
216 rdf:type schema:CreativeWork
217 https://doi.org/10.1103/physrevlett.106.256801 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028050463
218 rdf:type schema:CreativeWork
219 https://doi.org/10.1103/physrevlett.96.037201 schema:sameAs https://app.dimensions.ai/details/publication/pub.1060831600
220 rdf:type schema:CreativeWork
221 https://doi.org/10.1103/revmodphys.76.323 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007326605
222 rdf:type schema:CreativeWork
223 https://doi.org/10.1109/5.573737 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061179702
224 rdf:type schema:CreativeWork
225 https://doi.org/10.1109/jproc.2014.2361767 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061297970
226 rdf:type schema:CreativeWork
227 https://doi.org/10.1109/mc.2003.1250885 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061386903
228 rdf:type schema:CreativeWork
229 https://doi.org/10.1126/science.1065389 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024794148
230 rdf:type schema:CreativeWork
231 https://www.grid.ac/institutes/grid.4444.0 schema:alternateName French National Centre for Scientific Research
232 schema:name Fert Beijing Institute, Univ. Beihang, 100191, Beijing, China
233 Institut d’Electronique Fondamentale, Univ. Paris-Sud, F-91405 Orsay, France
234 School of Electrical & Information Engineering, Beihang Univ, Beijing 100191, Peoples R China
235 UMR 8622, CNRS, F-91405 Orsay, France
236 rdf:type schema:Organization
237 https://www.grid.ac/institutes/grid.462731.5 schema:alternateName Unité Mixte de Physique CNRS/Thales
238 schema:name Fert Beijing Institute, Univ. Beihang, 100191, Beijing, China
239 School of Electrical & Information Engineering, Beihang Univ, Beijing 100191, Peoples R China
240 Unité Mixte de Physique CNRS-Thales, F-91767 Palaiseau, France
241 rdf:type schema:Organization
242 https://www.grid.ac/institutes/grid.64939.31 schema:alternateName Beihang University
243 schema:name Fert Beijing Institute, Univ. Beihang, 100191, Beijing, China
244 School of Electrical & Information Engineering, Beihang Univ, Beijing 100191, Peoples R China
245 rdf:type schema:Organization
 




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


...