Evidence map›Paper›PMID 40731633›Full record

ArticleMaterials (Basel, Switzerland)2025

Mechanical Properties of CuZr Amorphous Metallic Nanofoam at Various Temperatures Investigated by Molecular Dynamics Simulation.

Yuhang Zhang, Hongjian Zhou, Xiuming Liu

Abstract read
In one paragraph

Article in Materials (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Yuhang ZhangHubei Digital Manufacturing Key Laboratory, School of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan 430070, China.ORCID 0000-0001-7129-7241
Hongjian ZhouSchool of Mechanical & Electrical Engineering, Wuhan Institute of Technology, Wuhan 430205, China.
Xiuming LiuInstitute of Technological Sciences, Wuhan University, Wuhan 430072, China.

Funding

Fundamental Research Funds for the Central Universities 104972025RSCbs0024Hubei Provincial Natural Science Foundation of China 2025AFB161
6 · The paper itself

Abstract

Metallic nanofoams with amorphous structures demonstrate exceptional properties and significant potential for diverse applications. However, their mechanical properties at different temperatures are still unclear. By using molecular dynamics simulation, this study investigates the mechanical responses of representative CuZr amorphous metallic nanofoam (AMNF) under uniaxial tension and compression at various temperatures. Our results reveal that the mechanical properties, such as Young's modulus, yield stress, and maximum stress, exhibit notable temperature sensitivity and tension-compression asymmetry. Under tensile loading, the Young's modulus, yield strength, and peak stress exhibit significant reductions of approximately 30.5%, 33.3%, and 32.9%, respectively, as the temperature increases from 100 K to 600 K. Similarly, under compressive loading, these mechanical properties experience even greater declines, with the Young's modulus, yield strength, and peak stress decreasing by about 34.5%, 38.0%, and 41.7% over the same temperature range. The tension-compression asymmetry in yield strength is temperature independent. Interestingly, the tension-compression asymmetry in elastic modulus becomes more pronounced at elevated temperatures, which is attributed to the influence of surface energy effects. This phenomenon is further amplified by the increased disparity in surface-area-to-volume ratio variations between tensile and compressive loading at higher temperatures. Additionally, as the temperature rises, despite material softening, the structural resistance under large tensile strains improves due to delayed ligament degradation and more uniform deformation distribution, delaying global failure.

Indexed as

amorphous metalsmechanical propertiesmolecular dynamicsnanoporous materialstemperature effects

Identifiers

PMID40731633
PMCPMC12300922

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.