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14 pages, 12344 KiB  
Article
Strain Characterization in Two-Dimensional Crystals
by Shizhe Feng and Zhiping Xu
Materials 2021, 14(16), 4460; https://doi.org/10.3390/ma14164460 - 9 Aug 2021
Cited by 9 | Viewed by 3865
Abstract
Two-dimensional (2D) crystals provides a material platform to explore the physics and chemistry at the single-atom scale, where surface characterization techniques can be applied straightforwardly. Recently there have been emerging interests in engineering materials through structural deformation or transformation. The strain field offers [...] Read more.
Two-dimensional (2D) crystals provides a material platform to explore the physics and chemistry at the single-atom scale, where surface characterization techniques can be applied straightforwardly. Recently there have been emerging interests in engineering materials through structural deformation or transformation. The strain field offers crucial information of lattice distortion and phase transformation in the native state or under external perturbation. Example problems with significance in science and engineering include the role of defects and dislocations in modulating material behaviors, and the process of fracture, where remarkable strain is built up in a local region, leading to the breakdown of materials. Strain is well defined in the continuum limit to measure the deformation, which can be alternatively calculated from the arrangement of atoms in discrete lattices through methods such as geometrical phase analysis from transmission electron imaging, bond distortion or virial stress from atomic structures obtained from molecular simulations. In this paper, we assess the accuracy of these methods in quantifying the strain field in 2D crystals through a number of examples, with a focus on their localized features at material imperfections. The sources of errors are discussed, providing a reference for reliable strain mapping. Full article
Show Figures

Figure 1

Figure 1
<p>Methods of strain characterization based on (<b>a</b>) GPA, (<b>b</b>) bond distortion and (<b>c</b>) virial stress. The scanning TEM (STEM) image in panel (<b>a</b>) is adapted from [<a href="#B4-materials-14-04460" class="html-bibr">4</a>] under the Creative Commons Attribution 4.0 International license.</p>
Full article ">Figure 2
<p>(<b>a</b>) A composite structure by patching an undeformed lattice (<b>left</b>) to a uniformly stretched one (<b>right</b>, strain along the <span class="html-italic">x</span> direction). (<b>b</b>) Uni-axial strain field calculated from GPA at <math display="inline"><semantics> <mrow> <mn>4</mn> <mo>%</mo> </mrow> </semantics></math> strain. Strain distribution along <span class="html-italic">x</span> is plotted as the inset in panel (<b>b</b>) for GPA using mask size of <math display="inline"><semantics> <mrow> <mi mathvariant="bold">g</mi> <mo>/</mo> <mn>4</mn> </mrow> </semantics></math> or <math display="inline"><semantics> <mrow> <mi mathvariant="bold">g</mi> <mo>/</mo> <mn>2</mn> </mrow> </semantics></math>. (<b>c</b>) Lagrangian strain estimation from GPA, bond and stress methods at strain of <math display="inline"><semantics> <mrow> <mn>4</mn> <mo>%</mo> <mo>,</mo> <mn>10</mn> <mo>%</mo> <mo>,</mo> <mn>15</mn> <mo>%</mo> </mrow> </semantics></math>. The Eulerian strain from GPA are plotted the solid lines in the bar representation. (<b>d</b>) Strain characterization for a stretched trapezoidal sample with a uniform strain gradient. Left and right ends (2 nm width) of the graphene lattice are displaced to apply a nominal strain of <math display="inline"><semantics> <mrow> <mi>ε</mi> <mo>=</mo> <mn>3.7</mn> <mo>%</mo> </mrow> </semantics></math> along the <span class="html-italic">x</span> direction. (<b>e</b>,<b>f</b>) Uni-axial strain fields calculated from (<b>e</b>) GPA and (<b>f</b>) bond methods. Strain distribution along the axis of mirror symmetry is plotted as inset in panel (<b>e</b>) for all the three methods.</p>
Full article ">Figure 3
<p>Strain characterization for a graphene monolayer with a circular hole. (<b>a</b>) Uni-axial strain is applied along the <span class="html-italic">x</span>-direction. (<b>b</b>) Distribution of strain component <math display="inline"><semantics> <msub> <mi>ε</mi> <mrow> <mi>x</mi> <mi>x</mi> </mrow> </msub> </semantics></math> along the <math display="inline"><semantics> <mrow> <mn>1</mn> <mo>−</mo> <mn>1</mn> </mrow> </semantics></math> cross section annotated in panel (<b>a</b>). (<b>c</b>–<b>f</b>) <math display="inline"><semantics> <msub> <mi>ε</mi> <mrow> <mi>x</mi> <mi>x</mi> </mrow> </msub> </semantics></math> map calculated from (<b>c</b>) GPA, (<b>d</b>) bond distortion, (<b>e</b>) the theory of linear elasticity, and (<b>f</b>) virial stress.</p>
Full article ">Figure 4
<p>Strain characterization for a mode-I crack tip. (<b>a</b>) A pre-crack is created at the middle of left edge in the graphene monolayer. Strain is applied along <span class="html-italic">y</span> (the armchair direction) by deforming the simulation box. (<b>b</b>) <math display="inline"><semantics> <msub> <mi>ε</mi> <mrow> <mi>y</mi> <mi>y</mi> </mrow> </msub> </semantics></math> plotted along <span class="html-italic">x</span> from the tip. (<b>c</b>–<b>f</b>) <math display="inline"><semantics> <msub> <mi>ε</mi> <mrow> <mi>y</mi> <mi>y</mi> </mrow> </msub> </semantics></math> map calculated from (<b>c</b>) GPA, (<b>d</b>) bond distortion, (<b>e</b>) LEFM, and (<b>f</b>) virial stress.</p>
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<p>Strain characterization for isolated dislocations (<b>a</b>–<b>f</b>) and GBs (<b>g</b>–<b>k</b>). (<b>a</b>–<b>f</b>) <math display="inline"><semantics> <msub> <mi>ε</mi> <mrow> <mi>x</mi> <mi>x</mi> </mrow> </msub> </semantics></math> map calculated from (<b>b</b>) GPA, (<b>c</b>) the Foreman model with <math display="inline"><semantics> <mrow> <mi>a</mi> <mo>=</mo> <mn>3</mn> </mrow> </semantics></math>, (<b>e</b>) bond distortion, (<b>f</b>) virial stress. Panel (<b>d</b>) summaries <math display="inline"><semantics> <msub> <mi>ε</mi> <mrow> <mi>x</mi> <mi>x</mi> </mrow> </msub> </semantics></math> along the cross section <math display="inline"><semantics> <mrow> <mn>1</mn> <mo>−</mo> <mn>1</mn> </mrow> </semantics></math> annotated in panel (<b>a</b>), which also includes the theoretical predictions from isotropic linear elasticity and the Peierls–Nabarro model. (<b>g</b>–<b>k</b>) Strain component <math display="inline"><semantics> <msub> <mi>ε</mi> <mrow> <mi>x</mi> <mi>x</mi> </mrow> </msub> </semantics></math> and in-plane rotation <math display="inline"><semantics> <mi>φ</mi> </semantics></math> in panel (<b>j</b>) map calculated from (<b>h</b>,<b>j</b>) GPA and (<b>i</b>,<b>k</b>) bond distortion. Results are plotted for GBs with the twist angle between the neighboring domains of <math display="inline"><semantics> <mrow> <mi>ϕ</mi> <mo>=</mo> <msup> <mn>5</mn> <mo>∘</mo> </msup> </mrow> </semantics></math> (<b>h</b>,<b>i</b>) and <math display="inline"><semantics> <mrow> <mi>ϕ</mi> <mo>=</mo> <msup> <mn>30</mn> <mo>∘</mo> </msup> </mrow> </semantics></math> (<b>j</b>,<b>k</b>).</p>
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31 pages, 2290 KiB  
Review
Understanding Electronic Structure and Chemical Reactivity: Quantum-Information Perspective
by Roman F. Nalewajski
Appl. Sci. 2019, 9(6), 1262; https://doi.org/10.3390/app9061262 - 26 Mar 2019
Cited by 21 | Viewed by 3811
Abstract
Several applications of quantum mechanics and information theory to chemical reactivity problems are presented with emphasis on equivalence of variational principles for the constrained minima of the system electronic energy and its kinetic energy component, which also determines the overall gradient information. Continuities [...] Read more.
Several applications of quantum mechanics and information theory to chemical reactivity problems are presented with emphasis on equivalence of variational principles for the constrained minima of the system electronic energy and its kinetic energy component, which also determines the overall gradient information. Continuities of molecular probability and current distributions, reflecting the modulus and phase components of molecular wavefunctions, respectively, are summarized. Resultant measures of the entropy/information descriptors of electronic states, combining the classical (probability) and nonclassical (phase/current) contributions, are introduced, and information production in quantum states is shown to be of a nonclassical origin. Importance of resultant information descriptors for distinguishing the bonded (entangled) and nonbonded (disentangled) states of reactants in acid(A)–base(B) systems is stressed and generalized entropy concepts are used to determine the phase equilibria in molecular systems. The grand-canonical principles for the minima of electronic energy and overall gradient information allow one to explore relations between energetic and information criteria of chemical reactivity in open molecules. The populational derivatives of electronic energy and resultant gradient information give identical predictions of electronic flows between reactants. The role of electronic kinetic energy (resultant gradient information) in chemical-bond formation is examined, the virial theorem implications for the Hammond postulate of reactivity theory are explored, and changes of the overall structure information in chemical processes are addressed. The frontier-electron basis of the hard (soft) acids and bases (HSAB) principle is reexamined and covalent/ionic characters of the intra- and inter-reactant communications in donor-acceptor systems are explored. The complementary A–B coordination is compared with its regional HSAB analog, and polarizational/relaxational flows in such reactive systems are explored. Full article
(This article belongs to the Special Issue The Application of Quantum Mechanics in Reactivity of Molecules)
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Figure 1

Figure 1
<p>Schematic diagram of the axial (bond) profiles, in section containing the “<span class="html-italic">z</span>” direction of the coordinate system (along the bond axis), of the external potential (<span class="html-italic">v</span>) and electron probability (<span class="html-italic">p</span>) in a diatomic molecule A–B demonstrating a negative character of the scalar product ∇<span class="html-italic">p</span>(<b><span class="html-italic">r</span></b>) ⋅∇<span class="html-italic">v</span>(<b><span class="html-italic">r</span></b>). It confirms the negative equilibrium contribution <span class="html-italic">σ<sub>I</sub><sup>eq.</sup></span>(axial) of the resultant gradient information (Equations (A20) and (A21)) and positive source <span class="html-italic">σ<sub>M</sub><sup>eq.</sup></span>(axial) of the resultant gradient entropy (Equation (A24)) in the bond formation process, due to the equilibrium current of Equation (18), <b><span class="html-italic">j</span></b><span class="html-italic"><sub>eq.</sub></span>(<b><span class="html-italic">r</span></b>) ∝ −∇<span class="html-italic">p</span>(<b><span class="html-italic">r</span></b>).</p>
Full article ">Figure 2
<p>Variations of the electronic energy Δ<span class="html-italic">E</span>(<span class="html-italic">R</span>) (solid line) with the internuclear distance <span class="html-italic">R</span> in a diatomic molecule and of its kinetic energy component Δ<span class="html-italic">T</span>(<span class="html-italic">R</span>) (broken line) determined by the virial theorem partition.4. Reactivity Implications of Molecular Virial Theorem.</p>
Full article ">Figure 3
<p>Variations of the electronic total (<span class="html-italic">E</span>) and kinetic (<span class="html-italic">T</span>) energies in exo-ergic (Δ<span class="html-italic">E<sub>r</sub></span> &lt; 0) or endo-ergic (Δ<span class="html-italic">E<sub>r</sub></span> &gt; 0) reactions (upper Panel (<b>a</b>)), and on the symmetrical BO potential energy surface (PES) (Δ<span class="html-italic">E<sub>r</sub></span> = 0) (lower Panel (<b>b</b>)).</p>
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<p>Schematic diagram of the in situ chemical potentials <span class="html-italic">μ</span><sub>CT</sub>(B→A), determining the effective internal charge transfer (CT) from basic (B) reactant to its acidic (A) partner in A–B complexes, for their alternative hard (H) and soft (S) combinations. The subsystem hardnesses reflect the HOMO-LUMO gaps in their orbital energies.</p>
Full article ">Figure 5
<p>Polarizational {P<span class="html-italic"><sub>α</sub></span> = (<span class="html-italic">a</span><span class="html-italic"><sub>α</sub></span>→<span class="html-italic">b</span><span class="html-italic"><sub>α</sub></span>)} and charge-transfer {CT<span class="html-italic"><sub>α</sub></span> = (<span class="html-italic">b</span><span class="html-italic"><sub>α</sub></span>→<span class="html-italic">a</span><span class="html-italic"><sub>β</sub></span>)} electron flows, (<span class="html-italic">α</span>, <span class="html-italic">β</span>≠<span class="html-italic">α</span>) ∈ {A, B}, involving the acidic A = (<span class="html-italic">a</span><sub>A</sub>|<span class="html-italic">b</span><sub>A</sub>) and basic B = (<span class="html-italic">a</span><sub>B</sub>|<span class="html-italic">b</span><sub>B</sub>) reactants in the complementary arrangement R<span class="html-italic"><sub>c</sub></span> of their acidic (<span class="html-italic">a</span>) and basic (<span class="html-italic">b</span>) fragments, with the chemically “hard” (acidic) fragment of one substrate facing the chemically “soft” (basic) part of its reaction partner. The polarizational flows {P<span class="html-italic"><sub>α</sub></span>} (black arrows) in the mutually closed substrates, relative to the substrate “promolecular” references, preserve the overall numbers of electrons of isolated reactants {<span class="html-italic">α</span><sup>0</sup>}, while the two partial {CT<span class="html-italic"><sub>i</sub></span>} fluxes (white arrows), from the basic fragment of one reactant to the acidic part of the other reactant, generate a substantial resultant B→A transfer of <span class="html-italic">N</span><sub>CT</sub> = CT<sub>1</sub> − CT<sub>2</sub> electrons between the mutually open reactants. These hypothetical electron flows in such a “complementary complex” are seen to produce an effective concerted (“circular”) flux of electrons between the four fragments invoked in this regional “functional” partition, which precludes an exaggerated depletion or concentration of electrons on any fragment of reactive system.</p>
Full article ">Figure 6
<p>Polarizational {P<span class="html-italic"><sub>α</sub></span> = (<span class="html-italic">b</span><span class="html-italic"><sub>α</sub></span>→<span class="html-italic">a</span><span class="html-italic"><sub>α</sub></span>)} and charge-transfer, CT<sub>1</sub> = (<span class="html-italic">b</span><sub>B</sub>→<span class="html-italic">b</span><sub>A</sub>) and CT<sub>2</sub> = (<span class="html-italic">a</span><sub>B</sub>→<span class="html-italic">a</span><sub>A</sub>), electron flows, involving the acidic A = (<span class="html-italic">a</span><sub>A</sub>|<span class="html-italic">b</span><sub>A</sub>) and basic B = (<span class="html-italic">a</span><sub>B</sub>|<span class="html-italic">b</span><sub>B</sub>) reactants in the regional HSAB complex R<sub>HSAB</sub>, in which the chemically hard (acidic) and soft (basic) fragments of one reactant coordinate to the like fragment of the other substrate. The two partial {CT<span class="html-italic"><sub>i</sub></span>} fluxes (white arrows) now generate a moderate overall B→A transfer of <span class="html-italic">N</span><sub>CT</sub> = CT<sub>1</sub> + CT<sub>2</sub> electrons between the mutually open reactants. These hypothetical electron flows in the regional HSAB complex are seen to produce a disconcerted pattern of fluxes producing an exaggerated outflow of electrons from <span class="html-italic">b</span><sub>B</sub> and and their accentuated inflow to <span class="html-italic">a</span><sub>A</sub>.</p>
Full article ">
41321 KiB  
Article
Idealized vs. Realistic Microstructures: An Atomistic Simulation Case Study on γ/γ Microstructures
by Aruna Prakash and Erik Bitzek
Materials 2017, 10(1), 88; https://doi.org/10.3390/ma10010088 - 23 Jan 2017
Cited by 14 | Viewed by 8339
Abstract
Single-crystal Ni-base superalloys, consisting of a two-phase γ/ γ microstructure, retain high strengths at elevated temperatures and are key materials for high temperature applications, like, e.g., turbine blades of aircraft engines. The lattice misfit between the γ and γ phases [...] Read more.
Single-crystal Ni-base superalloys, consisting of a two-phase γ/ γ microstructure, retain high strengths at elevated temperatures and are key materials for high temperature applications, like, e.g., turbine blades of aircraft engines. The lattice misfit between the γ and γ phases results in internal stresses, which significantly influence the deformation and creep behavior of the material. Large-scale atomistic simulations that are often used to enhance our understanding of the deformation mechanisms in such materials must accurately account for such misfit stresses. In this work, we compare the internal stresses in both idealized and experimentally-informed, i.e., more realistic, γ/ γ microstructures. The idealized samples are generated by assuming, as is frequently done, a periodic arrangement of cube-shaped γ particles with planar γ/ γ interfaces. The experimentally-informed samples are generated from two different sources to produce three different samples—the scanning electron microscopy micrograph-informed quasi-2D atomistic sample and atom probe tomography-informed stoichiometric and non-stoichiometric atomistic samples. Additionally, we compare the stress state of an idealized embedded cube microstructure with finite element simulations incorporating 3D periodic boundary conditions. Subsequently, we study the influence of the resulting stress state on the evolution of dislocation loops in the different samples. The results show that the stresses in the atomistic and finite element simulations are almost identical. Furthermore, quasi-2D boundary conditions lead to a significantly different stress state and, consequently, different evolution of the dislocation loop, when compared to samples with fully 3D boundary conditions. Full article
(This article belongs to the Section Advanced Materials Characterization)
Show Figures

Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Simulation setup of the idealized samples used in the current work. (<b>a</b>) Schematic picture of the idealized <span class="html-italic">γ</span>/<math display="inline"> <semantics> <msup> <mi>γ</mi> <mo>′</mo> </msup> </semantics> </math> microstructure showing cube-shaped <math display="inline"> <semantics> <msup> <mi>γ</mi> <mo>′</mo> </msup> </semantics> </math> particles embedded in a matrix; (<b>b</b>) Atomistic model of the idealized <span class="html-italic">γ</span>/<math display="inline"> <semantics> <msup> <mi>γ</mi> <mo>′</mo> </msup> </semantics> </math> microstructure. Due to symmetry, only one cube-shaped <math display="inline"> <semantics> <msup> <mi>γ</mi> <mo>′</mo> </msup> </semantics> </math> particle, highlighted in black in (a), of a length of 75 nm embedded in a matrix of a width of 25 nm, is used in the simulations. The atomistic sample contains approximately 90 million atoms. periodic boundary conditions (PBCs) are imposed in all directions. The <math display="inline"> <semantics> <msup> <mi>γ</mi> <mo>′</mo> </msup> </semantics> </math> particle is shown as a transparent surface for visualization purposes; (<b>c</b>) Meshed structure for FE simulations. The dimensions correspond to that of the atomistic structure in (a). PBCs are imposed in all directions using external control nodes. The elements in <math display="inline"> <semantics> <msup> <mi>γ</mi> <mo>′</mo> </msup> </semantics> </math> are colored grey, whilst those in <span class="html-italic">γ</span> are colored green; (<b>d</b>) Quasi-2D simulation sample with planar interfaces. This setup corresponds to a planar cut of the idealized <span class="html-italic">γ</span>/<math display="inline"> <semantics> <msup> <mi>γ</mi> <mo>′</mo> </msup> </semantics> </math> microstructure and extrusion along the thickness direction so as to obtain two orthogonal and two parallel channels. PBCs are imposed only along the thickness (<math display="inline"> <semantics> <mrow> <mi>z</mi> <mo>|</mo> <mo>|</mo> <mo>[</mo> <mn>001</mn> <mo>]</mo> </mrow> </semantics> </math>) direction. Color code (for the atomistic simulation samples): Ni atoms are colored grey, whilst the Al atoms are colored black.</p>
Full article ">Figure 2
<p>Simulation setup of the realistic samples used in the current work. (<b>a</b>) SEM-micrograph of a Ni-base superalloy Astra1 with the <span class="html-italic">γ</span>/<math display="inline"> <semantics> <msup> <mi>γ</mi> <mo>′</mo> </msup> </semantics> </math> microstructure [<a href="#B31-materials-10-00088" class="html-bibr">31</a>]. The atomistic sample corresponds to the region of interest marked in red; (<b>b</b>) SEM micrograph-informed quasi-2D atomistic sample with dimensions identical to sample S2p in <a href="#materials-10-00088-f001" class="html-fig">Figure 1</a>d. The channel thickness is 25 nm, and PBCs are imposed only along the thickness of the sample; (<b>c</b>) Atom probe tomography (APT) dataset with only Re (magenta), Ni (grey) and Al (black) atoms shown. Only the cuboidal region marked in red is used for further sample generation; (<b>d</b>) APT-informed stoichiometric atomistic sample; (<b>e</b>) Local concentration of Al in the region of interest in the APT sample; (<b>f</b>) APT-informed non-stoichiometric atomistic sample using the local concentrations of Al and Ni in the original APT data. Color code (for the atomistic simulation samples): Ni atoms are colored grey, whilst the Al atoms are colored black.</p>
Full article ">Figure 3
<p>Internal stress distribution in the different samples used in the current work: (<b>a</b>) FEM sample <span class="html-italic">S</span><math display="inline"> <semantics> <msub> <mrow/> <mrow> <mi>F</mi> <mi>E</mi> </mrow> </msub> </semantics> </math>; (<b>b</b>) Atomistic sample <span class="html-italic">S</span><math display="inline"> <semantics> <msub> <mrow/> <mrow> <mi>c</mi> <mi>u</mi> <mi>b</mi> </mrow> </msub> </semantics> </math>; (<b>c</b>) To help facilitate comparison with other atomistic samples, sample <span class="html-italic">S</span><math display="inline"> <semantics> <msub> <mrow/> <mrow> <mi>c</mi> <mi>u</mi> <mi>b</mi> </mrow> </msub> </semantics> </math> is shifted periodically so that the channels are now in the center of the picture; (<b>d</b>) Atomistic sample <span class="html-italic">S</span><math display="inline"> <semantics> <msub> <mrow/> <mrow> <mn>2</mn> <mi>D</mi> <mi>p</mi> </mrow> </msub> </semantics> </math>; (<b>e</b>) Atomistic sample <span class="html-italic">S</span><math display="inline"> <semantics> <msub> <mrow/> <mrow> <mn>2</mn> <mi>D</mi> <mi>S</mi> <mi>E</mi> <mi>M</mi> </mrow> </msub> </semantics> </math> obtained by digitizing SEM micrograph; (<b>f</b>) APT-informed atomistic sample <span class="html-italic">S</span><math display="inline"> <semantics> <msub> <mrow/> <mrow> <mi>A</mi> <mi>P</mi> <mi>T</mi> <mo>,</mo> <mi>s</mi> <mi>t</mi> <mi>o</mi> <mi>i</mi> </mrow> </msub> </semantics> </math> with stoichiometric chemical composition; (<b>g</b>) APT-informed atomistic sample <span class="html-italic">S</span><math display="inline"> <semantics> <msub> <mrow/> <mrow> <mi>A</mi> <mi>P</mi> <mi>T</mi> <mo>,</mo> <mi>n</mi> <mi>o</mi> <mi>n</mi> <mo>−</mo> <mi>s</mi> <mi>t</mi> <mi>o</mi> <mi>i</mi> </mrow> </msub> </semantics> </math> with non-stoichiometric chemical composition. All samples are oriented such that <math display="inline"> <semantics> <mrow> <mi>x</mi> <mo>∥</mo> <mo>[</mo> <mn>100</mn> <mo>]</mo> </mrow> </semantics> </math> and <math display="inline"> <semantics> <mrow> <mi>y</mi> <mo>∥</mo> <mo>[</mo> <mn>010</mn> <mo>]</mo> </mrow> </semantics> </math>. All atomistic samples share the same color bar.</p>
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<p>Stress profile (stress component <math display="inline"> <semantics> <msub> <mi>σ</mi> <mrow> <mi>x</mi> <mi>x</mi> </mrow> </msub> </semantics> </math>) along an internal face diagonal in the different samples. The path used in each sample is marked in white in the corresponding sample (see inset). (<b>a</b>) Atomistic sample <span class="html-italic">S</span><math display="inline"> <semantics> <msub> <mrow/> <mrow> <mi>c</mi> <mi>u</mi> <mi>b</mi> </mrow> </msub> </semantics> </math> and FEM sample <span class="html-italic">S</span><math display="inline"> <semantics> <msub> <mrow/> <mrow> <mi>F</mi> <mi>E</mi> </mrow> </msub> </semantics> </math>; (<b>b</b>) Atomistic samples <span class="html-italic">S</span><math display="inline"> <semantics> <msub> <mrow/> <mrow> <mn>2</mn> <mi>D</mi> <mi>p</mi> </mrow> </msub> </semantics> </math> and <span class="html-italic">S</span><math display="inline"> <semantics> <msub> <mrow/> <mrow> <mn>2</mn> <mi>D</mi> <mi>S</mi> <mi>E</mi> <mi>M</mi> </mrow> </msub> </semantics> </math>; four different paths are used in sample <span class="html-italic">S</span><math display="inline"> <semantics> <msub> <mrow/> <mrow> <mn>2</mn> <mi>D</mi> <mi>S</mi> <mi>E</mi> <mi>M</mi> </mrow> </msub> </semantics> </math>. Since the corresponding paths are identical in sample <span class="html-italic">S</span><math display="inline"> <semantics> <msub> <mrow/> <mrow> <mn>2</mn> <mi>D</mi> <mi>p</mi> </mrow> </msub> </semantics> </math>, only one path is shown. (<b>c</b>) APT-informed stoichiometric sample <span class="html-italic">S</span><math display="inline"> <semantics> <msub> <mrow/> <mrow> <mi>A</mi> <mi>P</mi> <mi>T</mi> <mo>,</mo> <mi>s</mi> <mi>t</mi> <mi>o</mi> <mi>i</mi> </mrow> </msub> </semantics> </math> and non-stoichiometric sample <span class="html-italic">S</span><math display="inline"> <semantics> <msub> <mrow/> <mrow> <mi>A</mi> <mi>P</mi> <mi>T</mi> <mo>,</mo> <mi>n</mi> <mi>o</mi> <mi>n</mi> <mo>−</mo> <mi>s</mi> <mi>t</mi> <mi>o</mi> <mi>i</mi> </mrow> </msub> </semantics> </math>. For all atomistic samples, stress profiles were obtained by extracting atoms inside a cylinder along the path considered. Results for five different cylinder radii (<math display="inline"> <semantics> <mrow> <mi>r</mi> <mo>=</mo> <mn>1</mn> <mo>,</mo> <mn>2</mn> <mo>,</mo> <mn>3</mn> <mo>,</mo> <mn>4</mn> <mo>,</mo> <mn>5</mn> </mrow> </semantics> </math> nm) are shown.</p>
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<p>Evolution of a dislocation loop in the different atomistic samples. Top row: sample <span class="html-italic">S</span><math display="inline"> <semantics> <msub> <mrow/> <mrow> <mi>c</mi> <mi>u</mi> <mi>b</mi> </mrow> </msub> </semantics> </math> (Cube sample); Central row: SEM micrograph informed sample <span class="html-italic">S</span><math display="inline"> <semantics> <msub> <mrow/> <mrow> <mn>2</mn> <mi>D</mi> <mi>S</mi> <mi>E</mi> <mi>M</mi> </mrow> </msub> </semantics> </math>. Bottom row: APT-informed sample <span class="html-italic">S</span><math display="inline"> <semantics> <msub> <mrow/> <mrow> <mi>A</mi> <mi>P</mi> <mi>T</mi> <mo>,</mo> <mi>s</mi> <mi>t</mi> <mi>o</mi> <mi>i</mi> </mrow> </msub> </semantics> </math> with the stoichiometric chemical composition. The <math display="inline"> <semantics> <msup> <mi>γ</mi> <mo>′</mo> </msup> </semantics> </math> particle is enclosed by a semi-transparent surface. For clarity, only atoms identified as defects are shown. In samples <span class="html-italic">S</span><math display="inline"> <semantics> <msub> <mrow/> <mrow> <mi>c</mi> <mi>u</mi> <mi>b</mi> </mrow> </msub> </semantics> </math> and <span class="html-italic">S</span><math display="inline"> <semantics> <msub> <mrow/> <mrow> <mi>A</mi> <mi>P</mi> <mi>T</mi> <mo>,</mo> <mi>s</mi> <mi>t</mi> <mi>o</mi> <mi>i</mi> </mrow> </msub> </semantics> </math>, with fully-3D boundary conditions, the dislocation loop cuts through the <math display="inline"> <semantics> <msup> <mi>γ</mi> <mo>′</mo> </msup> </semantics> </math> precipitate. By contrast, in sample <span class="html-italic">S</span><math display="inline"> <semantics> <msub> <mrow/> <mrow> <mn>2</mn> <mi>D</mi> <mi>S</mi> <mi>E</mi> <mi>M</mi> </mrow> </msub> </semantics> </math> (with quasi-2D BC), only deposition of the loop is observed. Evolution of the loop in sample <span class="html-italic">S</span><math display="inline"> <semantics> <msub> <mrow/> <mrow> <mn>2</mn> <mi>D</mi> <mi>p</mi> </mrow> </msub> </semantics> </math> shows the same characteristics as that of sample <span class="html-italic">S</span><math display="inline"> <semantics> <msub> <mrow/> <mrow> <mn>2</mn> <mi>D</mi> <mi>S</mi> <mi>E</mi> <mi>M</mi> </mrow> </msub> </semantics> </math> and is hence not shown here for the sake of brevity. Likewise, since the loop collapses even under applied strain in sample <span class="html-italic">S</span><math display="inline"> <semantics> <msub> <mrow/> <mrow> <mi>A</mi> <mi>P</mi> <mi>T</mi> <mo>,</mo> <mi>n</mi> <mi>o</mi> <mi>n</mi> <mo>−</mo> <mi>s</mi> <mi>t</mi> <mi>o</mi> <mi>i</mi> </mrow> </msub> </semantics> </math> (APT-informed non-stoichiometric sample), the evolution of the loop is also not shown. The color code denotes defects as identified by AtomViewer [<a href="#B43-materials-10-00088" class="html-bibr">43</a>,<a href="#B44-materials-10-00088" class="html-bibr">44</a>]: red, stacking fault (lighter shade used to denote complex stacking fault in <math display="inline"> <semantics> <msup> <mi>γ</mi> <mo>′</mo> </msup> </semantics> </math> phase); blue, antiphase boundary; white, other defects.</p>
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Article
Lattice Strain Due to an Atomic Vacancy
by Shidong Li, Michael S. Sellers, Cemal Basaran, Andrew J. Schultz and David A. Kofke
Int. J. Mol. Sci. 2009, 10(6), 2798-2808; https://doi.org/10.3390/ijms10062798 - 19 Jun 2009
Cited by 43 | Viewed by 13875
Abstract
Volumetric strain can be divided into two parts: strain due to bond distance change and strain due to vacancy sources and sinks. In this paper, efforts are focused on studying the atomic lattice strain due to a vacancy in an FCC metal lattice [...] Read more.
Volumetric strain can be divided into two parts: strain due to bond distance change and strain due to vacancy sources and sinks. In this paper, efforts are focused on studying the atomic lattice strain due to a vacancy in an FCC metal lattice with molecular dynamics simulation (MDS). The result has been compared with that from a continuum mechanics method. It is shown that using a continuum mechanics approach yields constitutive results similar to the ones obtained based purely on molecular dynamics considerations. Full article
(This article belongs to the Special Issue Composite Materials)
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Graphical abstract
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<p>A plot of first-nearest neighbor distance from center of an atom (or void), versus simulation time steps in molecular dynamic simulations. Filled black circles indicated a full lattice and open circles indicate a vacancy, where the atom is removed at 10 ps into the data collection run. Average neighbor positions before and after atom removal are 2.891 +/–0.009 and 2.831 +/–0.010, respectively.</p>
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<p>Void model in continuum mechanics domain.</p>
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<p>Free body diagram under spherical coordinate system.</p>
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<p>Plane strain element under compressive load.</p>
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