Structural Instability of Gold and Bimetallic Nanowires Using Monte Carlo Simulation View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2019-06-22

AUTHORS

Vladimir Myasnichenko , Nickolay Sdobnyakov , Leoneed Kirilov , Rossen Mikhov , Stefka Fidanova

ABSTRACT

In this paper, we present a method for optimizing of metal nanostructures. The core of the method is a lattice Monte Carlo method with different lattices combined with an approach from molecular dynamics. Interaction between atoms is calculated using multi-body tight-binding model. The method allows solving of problems with periodic boundary conditions. It can be used for modeling of one-dimensional and two-dimensional atomic structures. If periodic boundary conditions are not given, we assume finite dimensions of the model lattice. In addition, automatic relaxation of the crystal lattice can be performed in order to minimize further the potential energy of the system. A computer implementation of the method is developed. It uses the commonly accepted XYZ format for describing atomic structures and passing input parameters. We perform two series of simulations to study the size, composition and temperature dependent surface segregation behaviors and structural atomic instability of Au–Ag nanowires. We found that the most stable mixing configuration of bimetallic nanowires has Ag-rich surface and Au-rich subsurface. More... »

PAGES

133-145

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-030-22723-4_9

DOI

http://dx.doi.org/10.1007/978-3-030-22723-4_9

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1117402917


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/2008/03", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Chemical Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0307", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Theoretical and Computational Chemistry", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Tver State University, Tver, Russia", 
          "id": "http://www.grid.ac/institutes/grid.438242.b", 
          "name": [
            "Tver State University, Tver, Russia"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Myasnichenko", 
        "givenName": "Vladimir", 
        "id": "sg:person.013562762060.25", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013562762060.25"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Tver State University, Tver, Russia", 
          "id": "http://www.grid.ac/institutes/grid.438242.b", 
          "name": [
            "Tver State University, Tver, Russia"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Sdobnyakov", 
        "givenName": "Nickolay", 
        "id": "sg:person.010244167706.80", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010244167706.80"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Institute of Information and Communication Technologies, Bulgarian Academy of Sciences, Sofia, Bulgaria", 
          "id": "http://www.grid.ac/institutes/grid.424988.b", 
          "name": [
            "Institute of Information and Communication Technologies, Bulgarian Academy of Sciences, Sofia, Bulgaria"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kirilov", 
        "givenName": "Leoneed", 
        "id": "sg:person.015700215743.52", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015700215743.52"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Institute of Information and Communication Technologies, Bulgarian Academy of Sciences, Sofia, Bulgaria", 
          "id": "http://www.grid.ac/institutes/grid.424988.b", 
          "name": [
            "Institute of Information and Communication Technologies, Bulgarian Academy of Sciences, Sofia, Bulgaria"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Mikhov", 
        "givenName": "Rossen", 
        "id": "sg:person.014434131110.58", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014434131110.58"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Institute of Information and Communication Technologies, Bulgarian Academy of Sciences, Sofia, Bulgaria", 
          "id": "http://www.grid.ac/institutes/grid.424988.b", 
          "name": [
            "Institute of Information and Communication Technologies, Bulgarian Academy of Sciences, Sofia, Bulgaria"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Fidanova", 
        "givenName": "Stefka", 
        "id": "sg:person.011173106320.18", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011173106320.18"
        ], 
        "type": "Person"
      }
    ], 
    "datePublished": "2019-06-22", 
    "datePublishedReg": "2019-06-22", 
    "description": "In this paper, we present a method for optimizing of metal nanostructures. The core of the method is a lattice Monte Carlo method with different lattices combined with an approach from molecular dynamics. Interaction between atoms is calculated using multi-body tight-binding model. The method allows solving of problems with periodic boundary conditions. It can be used for modeling of one-dimensional and two-dimensional atomic structures. If periodic boundary conditions are not given, we assume finite dimensions of the model lattice. In addition, automatic relaxation of the crystal lattice can be performed in order to minimize further the potential energy of the system. A computer implementation of the method is developed. It uses the commonly accepted XYZ format for describing atomic structures and passing input parameters. We perform two series of simulations to study the size, composition and temperature dependent surface segregation behaviors and structural atomic instability of Au\u2013Ag nanowires. We found that the most stable mixing configuration of bimetallic nanowires has Ag-rich surface and Au-rich subsurface.", 
    "editor": [
      {
        "familyName": "Fidanova", 
        "givenName": "Stefka", 
        "type": "Person"
      }
    ], 
    "genre": "chapter", 
    "id": "sg:pub.10.1007/978-3-030-22723-4_9", 
    "inLanguage": "en", 
    "isAccessibleForFree": false, 
    "isPartOf": {
      "isbn": [
        "978-3-030-22722-7", 
        "978-3-030-22723-4"
      ], 
      "name": "Recent Advances in Computational Optimization", 
      "type": "Book"
    }, 
    "keywords": [
      "atomic structure", 
      "two-dimensional atomic structure", 
      "bimetallic nanowires", 
      "periodic boundary conditions", 
      "metal nanostructures", 
      "binding model", 
      "Monte Carlo method", 
      "Monte Carlo simulations", 
      "surface segregation behavior", 
      "molecular dynamics", 
      "Carlo method", 
      "potential energy", 
      "nanowires", 
      "Carlo simulations", 
      "lattice", 
      "crystal lattice", 
      "different lattices", 
      "model lattice", 
      "structural instability", 
      "lattice Monte Carlo method", 
      "boundary conditions", 
      "atoms", 
      "finite dimensions", 
      "nanostructures", 
      "segregation behavior", 
      "energy", 
      "instability", 
      "simulations", 
      "relaxation", 
      "series of simulations", 
      "structure", 
      "Au-Ag", 
      "dynamics", 
      "surface", 
      "gold", 
      "input parameters", 
      "configuration", 
      "core", 
      "interaction", 
      "method", 
      "computer implementation", 
      "parameters", 
      "automatic relaxation", 
      "solving of problems", 
      "order", 
      "composition", 
      "conditions", 
      "dimensions", 
      "system", 
      "size", 
      "behavior", 
      "model", 
      "modeling", 
      "subsurface", 
      "series", 
      "solving", 
      "problem", 
      "addition", 
      "XYZ format", 
      "approach", 
      "optimizing", 
      "paper", 
      "format", 
      "implementation"
    ], 
    "name": "Structural Instability of Gold and Bimetallic Nanowires Using Monte Carlo Simulation", 
    "pagination": "133-145", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1117402917"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/978-3-030-22723-4_9"
        ]
      }
    ], 
    "publisher": {
      "name": "Springer Nature", 
      "type": "Organisation"
    }, 
    "sameAs": [
      "https://doi.org/10.1007/978-3-030-22723-4_9", 
      "https://app.dimensions.ai/details/publication/pub.1117402917"
    ], 
    "sdDataset": "chapters", 
    "sdDatePublished": "2022-05-10T10:50", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20220509/entities/gbq_results/chapter/chapter_385.jsonl", 
    "type": "Chapter", 
    "url": "https://doi.org/10.1007/978-3-030-22723-4_9"
  }
]
 

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.10.1007/978-3-030-22723-4_9'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-3-030-22723-4_9'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-3-030-22723-4_9'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-3-030-22723-4_9'


 

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

155 TRIPLES      23 PREDICATES      89 URIs      82 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/978-3-030-22723-4_9 schema:about anzsrc-for:03
2 anzsrc-for:0307
3 schema:author N76d69e44fe1145d6befa8d004bf37877
4 schema:datePublished 2019-06-22
5 schema:datePublishedReg 2019-06-22
6 schema:description In this paper, we present a method for optimizing of metal nanostructures. The core of the method is a lattice Monte Carlo method with different lattices combined with an approach from molecular dynamics. Interaction between atoms is calculated using multi-body tight-binding model. The method allows solving of problems with periodic boundary conditions. It can be used for modeling of one-dimensional and two-dimensional atomic structures. If periodic boundary conditions are not given, we assume finite dimensions of the model lattice. In addition, automatic relaxation of the crystal lattice can be performed in order to minimize further the potential energy of the system. A computer implementation of the method is developed. It uses the commonly accepted XYZ format for describing atomic structures and passing input parameters. We perform two series of simulations to study the size, composition and temperature dependent surface segregation behaviors and structural atomic instability of Au–Ag nanowires. We found that the most stable mixing configuration of bimetallic nanowires has Ag-rich surface and Au-rich subsurface.
7 schema:editor Nf98a3d760bde42898497d6539d3632c6
8 schema:genre chapter
9 schema:inLanguage en
10 schema:isAccessibleForFree false
11 schema:isPartOf Ncd5ddba09fa8478cb5f3c73e5e6696d6
12 schema:keywords Au-Ag
13 Carlo method
14 Carlo simulations
15 Monte Carlo method
16 Monte Carlo simulations
17 XYZ format
18 addition
19 approach
20 atomic structure
21 atoms
22 automatic relaxation
23 behavior
24 bimetallic nanowires
25 binding model
26 boundary conditions
27 composition
28 computer implementation
29 conditions
30 configuration
31 core
32 crystal lattice
33 different lattices
34 dimensions
35 dynamics
36 energy
37 finite dimensions
38 format
39 gold
40 implementation
41 input parameters
42 instability
43 interaction
44 lattice
45 lattice Monte Carlo method
46 metal nanostructures
47 method
48 model
49 model lattice
50 modeling
51 molecular dynamics
52 nanostructures
53 nanowires
54 optimizing
55 order
56 paper
57 parameters
58 periodic boundary conditions
59 potential energy
60 problem
61 relaxation
62 segregation behavior
63 series
64 series of simulations
65 simulations
66 size
67 solving
68 solving of problems
69 structural instability
70 structure
71 subsurface
72 surface
73 surface segregation behavior
74 system
75 two-dimensional atomic structure
76 schema:name Structural Instability of Gold and Bimetallic Nanowires Using Monte Carlo Simulation
77 schema:pagination 133-145
78 schema:productId N370bbcab582d48cabdfd292b29332b6e
79 N7d71409a186d428db2818f9d4a664421
80 schema:publisher Nc0e09d03f24a4eeaa7dab1af2da66323
81 schema:sameAs https://app.dimensions.ai/details/publication/pub.1117402917
82 https://doi.org/10.1007/978-3-030-22723-4_9
83 schema:sdDatePublished 2022-05-10T10:50
84 schema:sdLicense https://scigraph.springernature.com/explorer/license/
85 schema:sdPublisher N126f7cede21b47148c5bf90b03ec549a
86 schema:url https://doi.org/10.1007/978-3-030-22723-4_9
87 sgo:license sg:explorer/license/
88 sgo:sdDataset chapters
89 rdf:type schema:Chapter
90 N01b59fe21574418ebf235347fbc9a48b rdf:first sg:person.014434131110.58
91 rdf:rest Nd258e3cb51e84092bf88d27e4d831e64
92 N032914544b7544f2b4345e30aace3aa9 rdf:first sg:person.015700215743.52
93 rdf:rest N01b59fe21574418ebf235347fbc9a48b
94 N126f7cede21b47148c5bf90b03ec549a schema:name Springer Nature - SN SciGraph project
95 rdf:type schema:Organization
96 N370bbcab582d48cabdfd292b29332b6e schema:name dimensions_id
97 schema:value pub.1117402917
98 rdf:type schema:PropertyValue
99 N3b8dcf47358b455793d972bb27f2dd14 schema:familyName Fidanova
100 schema:givenName Stefka
101 rdf:type schema:Person
102 N76d69e44fe1145d6befa8d004bf37877 rdf:first sg:person.013562762060.25
103 rdf:rest N85950e85557e4e7b9279cb0aec1507c4
104 N7d71409a186d428db2818f9d4a664421 schema:name doi
105 schema:value 10.1007/978-3-030-22723-4_9
106 rdf:type schema:PropertyValue
107 N85950e85557e4e7b9279cb0aec1507c4 rdf:first sg:person.010244167706.80
108 rdf:rest N032914544b7544f2b4345e30aace3aa9
109 Nc0e09d03f24a4eeaa7dab1af2da66323 schema:name Springer Nature
110 rdf:type schema:Organisation
111 Ncd5ddba09fa8478cb5f3c73e5e6696d6 schema:isbn 978-3-030-22722-7
112 978-3-030-22723-4
113 schema:name Recent Advances in Computational Optimization
114 rdf:type schema:Book
115 Nd258e3cb51e84092bf88d27e4d831e64 rdf:first sg:person.011173106320.18
116 rdf:rest rdf:nil
117 Nf98a3d760bde42898497d6539d3632c6 rdf:first N3b8dcf47358b455793d972bb27f2dd14
118 rdf:rest rdf:nil
119 anzsrc-for:03 schema:inDefinedTermSet anzsrc-for:
120 schema:name Chemical Sciences
121 rdf:type schema:DefinedTerm
122 anzsrc-for:0307 schema:inDefinedTermSet anzsrc-for:
123 schema:name Theoretical and Computational Chemistry
124 rdf:type schema:DefinedTerm
125 sg:person.010244167706.80 schema:affiliation grid-institutes:grid.438242.b
126 schema:familyName Sdobnyakov
127 schema:givenName Nickolay
128 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010244167706.80
129 rdf:type schema:Person
130 sg:person.011173106320.18 schema:affiliation grid-institutes:grid.424988.b
131 schema:familyName Fidanova
132 schema:givenName Stefka
133 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011173106320.18
134 rdf:type schema:Person
135 sg:person.013562762060.25 schema:affiliation grid-institutes:grid.438242.b
136 schema:familyName Myasnichenko
137 schema:givenName Vladimir
138 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013562762060.25
139 rdf:type schema:Person
140 sg:person.014434131110.58 schema:affiliation grid-institutes:grid.424988.b
141 schema:familyName Mikhov
142 schema:givenName Rossen
143 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014434131110.58
144 rdf:type schema:Person
145 sg:person.015700215743.52 schema:affiliation grid-institutes:grid.424988.b
146 schema:familyName Kirilov
147 schema:givenName Leoneed
148 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015700215743.52
149 rdf:type schema:Person
150 grid-institutes:grid.424988.b schema:alternateName Institute of Information and Communication Technologies, Bulgarian Academy of Sciences, Sofia, Bulgaria
151 schema:name Institute of Information and Communication Technologies, Bulgarian Academy of Sciences, Sofia, Bulgaria
152 rdf:type schema:Organization
153 grid-institutes:grid.438242.b schema:alternateName Tver State University, Tver, Russia
154 schema:name Tver State University, Tver, Russia
155 rdf:type schema:Organization
 




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


...