Quantifying the origin of metallic glass formation View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2016-01-20

AUTHORS

W. L. Johnson, J. H. Na, M. D. Demetriou

ABSTRACT

The waiting time to form a crystal in a unit volume of homogeneous undercooled liquid exhibits a pronounced minimum τX* at a ‘nose temperature’ T* located between the glass transition temperature Tg, and the crystal melting temperature, TL. Turnbull argued that τX* should increase rapidly with the dimensionless ratio trg=Tg/TL. Angell introduced a dimensionless ‘fragility parameter’, m, to characterize the fall of atomic mobility with temperature above Tg. Both trg and m are widely thought to play a significant role in determining τX*. Here we survey and assess reported data for TL, Tg, trg, m and τX* for a broad range of metallic glasses with widely varying τX*. By analysing this database, we derive a simple empirical expression for τX*(trg, m) that depends exponentially on trg and m, and two fitting parameters. A statistical analysis shows that knowledge of trg and m alone is therefore sufficient to predict τX* within estimated experimental errors. Surprisingly, the liquid/crystal interfacial free energy does not appear in this expression for τX*. More... »

PAGES

10313

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/ncomms10313

DOI

http://dx.doi.org/10.1038/ncomms10313

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1008045042

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/26786966


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/2008/09", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Engineering", 
        "type": "DefinedTerm"
      }, 
      {
        "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"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Department of Materials Science, Keck Laboratory of Engineering, 138-78 California Institute of Technology, 91125, Pasadena, California, USA", 
          "id": "http://www.grid.ac/institutes/grid.20861.3d", 
          "name": [
            "Department of Materials Science, Keck Laboratory of Engineering, 138-78 California Institute of Technology, 91125, Pasadena, California, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Johnson", 
        "givenName": "W. L.", 
        "id": "sg:person.01046505045.39", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01046505045.39"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Glassimetal Technology Inc., 2670 Walnut St. Ave., 91107, Pasadena, California, USA", 
          "id": "http://www.grid.ac/institutes/None", 
          "name": [
            "Glassimetal Technology Inc., 2670 Walnut St. Ave., 91107, Pasadena, California, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Na", 
        "givenName": "J. H.", 
        "id": "sg:person.012212207105.46", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012212207105.46"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Glassimetal Technology Inc., 2670 Walnut St. Ave., 91107, Pasadena, California, USA", 
          "id": "http://www.grid.ac/institutes/None", 
          "name": [
            "Department of Materials Science, Keck Laboratory of Engineering, 138-78 California Institute of Technology, 91125, Pasadena, California, USA", 
            "Glassimetal Technology Inc., 2670 Walnut St. Ave., 91107, Pasadena, California, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Demetriou", 
        "givenName": "M. D.", 
        "id": "sg:person.01341434145.41", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01341434145.41"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1557/mrs2007.127", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1067969209", 
          "https://doi.org/10.1557/mrs2007.127"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1557/s0883769400053252", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1067964161", 
          "https://doi.org/10.1557/s0883769400053252"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/187869b0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1018841532", 
          "https://doi.org/10.1038/187869b0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nature13617", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1010259132", 
          "https://doi.org/10.1038/nature13617"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11661-998-0002-8", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1049886192", 
          "https://doi.org/10.1007/s11661-998-0002-8"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/srep06441", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034596228", 
          "https://doi.org/10.1038/srep06441"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/339363a0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048171872", 
          "https://doi.org/10.1038/339363a0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nmat4292", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003486437", 
          "https://doi.org/10.1038/nmat4292"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2016-01-20", 
    "datePublishedReg": "2016-01-20", 
    "description": "The waiting time to form a crystal in a unit volume of homogeneous undercooled liquid exhibits a pronounced minimum \u03c4X* at a \u2018nose temperature\u2019 T* located between the glass transition temperature Tg, and the crystal melting temperature, TL. Turnbull argued that \u03c4X* should increase rapidly with the dimensionless ratio trg=Tg/TL. Angell introduced a dimensionless \u2018fragility parameter\u2019, m, to characterize the fall of atomic mobility with temperature above Tg. Both trg and m are widely thought to play a significant role in determining \u03c4X*. Here we survey and assess reported data for TL, Tg, trg, m and \u03c4X* for a broad range of metallic glasses with widely varying \u03c4X*. By analysing this database, we derive a simple empirical expression for \u03c4X*(trg, m) that depends exponentially on trg and m, and two fitting parameters. A statistical analysis shows that knowledge of trg and m alone is therefore sufficient to predict \u03c4X* within estimated experimental errors. Surprisingly, the liquid/crystal interfacial free energy does not appear in this expression for \u03c4X*.", 
    "genre": "article", 
    "id": "sg:pub.10.1038/ncomms10313", 
    "isAccessibleForFree": true, 
    "isPartOf": [
      {
        "id": "sg:journal.1043282", 
        "issn": [
          "2041-1723"
        ], 
        "name": "Nature Communications", 
        "publisher": "Springer Nature", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "7"
      }
    ], 
    "keywords": [
      "fitting parameters", 
      "simple empirical expression", 
      "\u03c4x", 
      "metallic glass formation", 
      "statistical analysis", 
      "glass formation", 
      "temperature Tg", 
      "free energy", 
      "experimental error", 
      "fragility parameter", 
      "transition temperature Tg", 
      "parameters", 
      "empirical expression", 
      "dimensionless", 
      "metallic glasses", 
      "undercooled liquid", 
      "glass transition temperature Tg", 
      "atomic mobility", 
      "error", 
      "unit volume", 
      "crystals", 
      "interfacial free energy", 
      "temperature", 
      "Tl", 
      "Turnbull", 
      "broad range", 
      "Tg/Tl", 
      "energy", 
      "glass", 
      "Angell", 
      "liquid", 
      "range", 
      "analysis", 
      "time", 
      "data", 
      "significant role", 
      "expression", 
      "origin", 
      "TRG", 
      "mobility", 
      "volume", 
      "knowledge", 
      "formation", 
      "Tg", 
      "nose temperature", 
      "database", 
      "role", 
      "fall"
    ], 
    "name": "Quantifying the origin of metallic glass formation", 
    "pagination": "10313", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1008045042"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1038/ncomms10313"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "26786966"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1038/ncomms10313", 
      "https://app.dimensions.ai/details/publication/pub.1008045042"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2022-09-02T16:00", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20220902/entities/gbq_results/article/article_691.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://doi.org/10.1038/ncomms10313"
  }
]
 

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/ncomms10313'

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/ncomms10313'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1038/ncomms10313'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1038/ncomms10313'


 

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

158 TRIPLES      21 PREDICATES      81 URIs      65 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1038/ncomms10313 schema:about anzsrc-for:09
2 anzsrc-for:0912
3 schema:author N324e15c6c7ff46ee950a9ac63a18885d
4 schema:citation sg:pub.10.1007/s11661-998-0002-8
5 sg:pub.10.1038/187869b0
6 sg:pub.10.1038/339363a0
7 sg:pub.10.1038/nature13617
8 sg:pub.10.1038/nmat4292
9 sg:pub.10.1038/srep06441
10 sg:pub.10.1557/mrs2007.127
11 sg:pub.10.1557/s0883769400053252
12 schema:datePublished 2016-01-20
13 schema:datePublishedReg 2016-01-20
14 schema:description The waiting time to form a crystal in a unit volume of homogeneous undercooled liquid exhibits a pronounced minimum τX* at a ‘nose temperature’ T* located between the glass transition temperature Tg, and the crystal melting temperature, TL. Turnbull argued that τX* should increase rapidly with the dimensionless ratio trg=Tg/TL. Angell introduced a dimensionless ‘fragility parameter’, m, to characterize the fall of atomic mobility with temperature above Tg. Both trg and m are widely thought to play a significant role in determining τX*. Here we survey and assess reported data for TL, Tg, trg, m and τX* for a broad range of metallic glasses with widely varying τX*. By analysing this database, we derive a simple empirical expression for τX*(trg, m) that depends exponentially on trg and m, and two fitting parameters. A statistical analysis shows that knowledge of trg and m alone is therefore sufficient to predict τX* within estimated experimental errors. Surprisingly, the liquid/crystal interfacial free energy does not appear in this expression for τX*.
15 schema:genre article
16 schema:isAccessibleForFree true
17 schema:isPartOf N19f17c10dc1f4812a5ad9b5262daff38
18 Neda26d0c6081468fa23723fe057e9991
19 sg:journal.1043282
20 schema:keywords Angell
21 TRG
22 Tg
23 Tg/Tl
24 Tl
25 Turnbull
26 analysis
27 atomic mobility
28 broad range
29 crystals
30 data
31 database
32 dimensionless
33 empirical expression
34 energy
35 error
36 experimental error
37 expression
38 fall
39 fitting parameters
40 formation
41 fragility parameter
42 free energy
43 glass
44 glass formation
45 glass transition temperature Tg
46 interfacial free energy
47 knowledge
48 liquid
49 metallic glass formation
50 metallic glasses
51 mobility
52 nose temperature
53 origin
54 parameters
55 range
56 role
57 significant role
58 simple empirical expression
59 statistical analysis
60 temperature
61 temperature Tg
62 time
63 transition temperature Tg
64 undercooled liquid
65 unit volume
66 volume
67 τx
68 schema:name Quantifying the origin of metallic glass formation
69 schema:pagination 10313
70 schema:productId N02a628da73014e3d990e76c18c52c90d
71 N594812c70ba847e9a1f3446587f82750
72 Ne0ac6b7ceeb34127bfa20665a91b585c
73 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008045042
74 https://doi.org/10.1038/ncomms10313
75 schema:sdDatePublished 2022-09-02T16:00
76 schema:sdLicense https://scigraph.springernature.com/explorer/license/
77 schema:sdPublisher N8ce21618af794c7a92b40de3e9e466d0
78 schema:url https://doi.org/10.1038/ncomms10313
79 sgo:license sg:explorer/license/
80 sgo:sdDataset articles
81 rdf:type schema:ScholarlyArticle
82 N02a628da73014e3d990e76c18c52c90d schema:name pubmed_id
83 schema:value 26786966
84 rdf:type schema:PropertyValue
85 N19f17c10dc1f4812a5ad9b5262daff38 schema:issueNumber 1
86 rdf:type schema:PublicationIssue
87 N324e15c6c7ff46ee950a9ac63a18885d rdf:first sg:person.01046505045.39
88 rdf:rest Nf7645a0e4e0c4c6c8a5ea6e16d746fae
89 N594812c70ba847e9a1f3446587f82750 schema:name doi
90 schema:value 10.1038/ncomms10313
91 rdf:type schema:PropertyValue
92 N8ce21618af794c7a92b40de3e9e466d0 schema:name Springer Nature - SN SciGraph project
93 rdf:type schema:Organization
94 Na1564989e1af4f69bbfebc5a576640b3 rdf:first sg:person.01341434145.41
95 rdf:rest rdf:nil
96 Ne0ac6b7ceeb34127bfa20665a91b585c schema:name dimensions_id
97 schema:value pub.1008045042
98 rdf:type schema:PropertyValue
99 Neda26d0c6081468fa23723fe057e9991 schema:volumeNumber 7
100 rdf:type schema:PublicationVolume
101 Nf7645a0e4e0c4c6c8a5ea6e16d746fae rdf:first sg:person.012212207105.46
102 rdf:rest Na1564989e1af4f69bbfebc5a576640b3
103 anzsrc-for:09 schema:inDefinedTermSet anzsrc-for:
104 schema:name Engineering
105 rdf:type schema:DefinedTerm
106 anzsrc-for:0912 schema:inDefinedTermSet anzsrc-for:
107 schema:name Materials Engineering
108 rdf:type schema:DefinedTerm
109 sg:journal.1043282 schema:issn 2041-1723
110 schema:name Nature Communications
111 schema:publisher Springer Nature
112 rdf:type schema:Periodical
113 sg:person.01046505045.39 schema:affiliation grid-institutes:grid.20861.3d
114 schema:familyName Johnson
115 schema:givenName W. L.
116 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01046505045.39
117 rdf:type schema:Person
118 sg:person.012212207105.46 schema:affiliation grid-institutes:None
119 schema:familyName Na
120 schema:givenName J. H.
121 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012212207105.46
122 rdf:type schema:Person
123 sg:person.01341434145.41 schema:affiliation grid-institutes:None
124 schema:familyName Demetriou
125 schema:givenName M. D.
126 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01341434145.41
127 rdf:type schema:Person
128 sg:pub.10.1007/s11661-998-0002-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049886192
129 https://doi.org/10.1007/s11661-998-0002-8
130 rdf:type schema:CreativeWork
131 sg:pub.10.1038/187869b0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018841532
132 https://doi.org/10.1038/187869b0
133 rdf:type schema:CreativeWork
134 sg:pub.10.1038/339363a0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048171872
135 https://doi.org/10.1038/339363a0
136 rdf:type schema:CreativeWork
137 sg:pub.10.1038/nature13617 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010259132
138 https://doi.org/10.1038/nature13617
139 rdf:type schema:CreativeWork
140 sg:pub.10.1038/nmat4292 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003486437
141 https://doi.org/10.1038/nmat4292
142 rdf:type schema:CreativeWork
143 sg:pub.10.1038/srep06441 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034596228
144 https://doi.org/10.1038/srep06441
145 rdf:type schema:CreativeWork
146 sg:pub.10.1557/mrs2007.127 schema:sameAs https://app.dimensions.ai/details/publication/pub.1067969209
147 https://doi.org/10.1557/mrs2007.127
148 rdf:type schema:CreativeWork
149 sg:pub.10.1557/s0883769400053252 schema:sameAs https://app.dimensions.ai/details/publication/pub.1067964161
150 https://doi.org/10.1557/s0883769400053252
151 rdf:type schema:CreativeWork
152 grid-institutes:None schema:alternateName Glassimetal Technology Inc., 2670 Walnut St. Ave., 91107, Pasadena, California, USA
153 schema:name Department of Materials Science, Keck Laboratory of Engineering, 138-78 California Institute of Technology, 91125, Pasadena, California, USA
154 Glassimetal Technology Inc., 2670 Walnut St. Ave., 91107, Pasadena, California, USA
155 rdf:type schema:Organization
156 grid-institutes:grid.20861.3d schema:alternateName Department of Materials Science, Keck Laboratory of Engineering, 138-78 California Institute of Technology, 91125, Pasadena, California, USA
157 schema:name Department of Materials Science, Keck Laboratory of Engineering, 138-78 California Institute of Technology, 91125, Pasadena, California, USA
158 rdf:type schema:Organization
 




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


...