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Statistical characterization of the yield stress of nanoparticles

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Liang Yang, Jianjun Bian, Weike Yuan, Gangfeng Wang

Materials Science · Submitted 20 Dec 2019

abstract compiled · 2026-09-23 · no language-model review

The authors' main claim Present study illuminates the statistical features of the yielding behavior of nanostructured elements.

how it is stated · asserted 0.98 read the record →

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arXiv ID1912.09712 (version 1)
Pith IDQVOASJSO, Pith's permanent record of this paper and its review
CitationGangfeng Wang, Jianjun Bian, Liang Yang, Weike Yuan. "Statistical characterization of the yield stress of nanoparticles." arXiv:1912.09712 (2019). https://pith.science/paper/QVOASJSO
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The compiled record

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Compiled by classifier-1.13.0 via TypeSafe API, question bank abstract-p1-20260923, 2026-09-23: 1 request, 5,434 input tokens.

What the abstract itself states, as probabilities: claims first 0.03 · states limitation 0.07 · human participants 0.01 · controlled comparison 0.03 · randomized assignment 0.01 · states quantitative result 0.44 · compares with prior results 0.05 · mentions code or data availability 0.02.

The abstract, sentence by sentence

arXiv listing abstract v1. Results and the main claim are underlined; .

Atomistic simulations are performed to study the statistical mechanical property of gold nanoparticles. It is demonstrated that the yielding behavior of gold nanoparticles is governed by dislocation nucleation around surface steps. Since the nucleation of dislocations is an activated process with the aid of thermal fluctuation, the yield stress at a specific temperature should exhibit a statistical distribution rather than a definite constant value. Molecular dynamics simulations reveal that the yield stress follows a Gaussian distribution at a specific temperature. As the temperature increases, the mean value of yield stress decreases while the width of distribution becomes larger. Based on numerical analysis, the dependence of the mean yield stress on temperature can be well described by a parabolic function. Present study illuminates the statistical features of the yielding behavior of nanostructured elements.

background contribution method result interpretation main claim

What the classifier reports for each sentence. The number is the probability it gave the label.
#sentencerolethe authors' own workstates the main conclusionstrength
s0 Atomistic simulations are performed to study the statistical mechanical property of gold nanoparticles. method 0.71 0.93 0.02 asserted 0.94
s1 It is demonstrated that the yielding behavior of gold nanoparticles is governed by dislocation nucleation around surface steps. result 0.94 0.84 0.36 asserted 1.00
s2 Since the nucleation of dislocations is an activated process with the aid of thermal fluctuation, the yield stress at a specific temperature should exhibit a statistical distribution rather than a definite constant value. interpretation 0.64 0.23 0.28 asserted 0.96
s3 Molecular dynamics simulations reveal that the yield stress follows a Gaussian distribution at a specific temperature. result 1.00 0.93 0.27 asserted 1.00
s4 As the temperature increases, the mean value of yield stress decreases while the width of distribution becomes larger. result 1.00 0.89 0.17 asserted 1.00
s5 Based on numerical analysis, the dependence of the mean yield stress on temperature can be well described by a parabolic function. result 0.99 0.92 0.16 asserted 0.95
s6 Present study illuminates the statistical features of the yielding behavior of nanostructured elements. contribution 0.76 0.83 0.40 asserted 0.98

What kind of paper the classifier reports this is: simulation study 1.00 · evidence from simulation or computation 1.00.

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Every quoted sentence on this record is the authors'. Every label is from Pith's closed vocabulary, with the probability shown beside it. Every number in the measurements table is the authors', checked by code. Record as JSON

The paper
Original abstract

Atomistic simulations are performed to study the statistical mechanical property of gold nanoparticles. It is demonstrated that the yielding behavior of gold nanoparticles is governed by dislocation nucleation around surface steps. Since the nucleation of dislocations is an activated process with the aid of thermal fluctuation, the yield stress at a specific temperature should exhibit a statistical distribution rather than a definite constant value. Molecular dynamics simulations reveal that the yield stress follows a Gaussian distribution at a specific temperature. As the temperature increases, the mean value of yield stress decreases while the width of distribution becomes larger. Based on numerical analysis, the dependence of the mean yield stress on temperature can be well described by a parabolic function. Present study illuminates the statistical features of the yielding behavior of nanostructured elements.

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