ArticleScanning2017
In Situ SEM Torsion Test of Metallic Glass Microwires Based on Micro Robotic Manipulation.
Article in Scanning, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Microwires, such as metallic, semiconductor, and polymer microwires and carbon fibers, have stimulated great interest due to their importance in various structural and functional applications. Particularly, metallic glass (MG) microwires, because of their amorphous atoms arrangement, have some unique mechanical properties compared with traditional metals. Despite the fact that substantial research efforts have been made on the mechanical characterizations of metallic glass microwires under tension or flexural bending, the mechanical properties of microwires under torsional loading have not been well studied, mainly due to the experimental difficulties, such as the detection of torsion angle, quantitative measurement of the torsional load, and the alignment between the specimen and torque meter. In this work, we implemented the in situ SEM torsion tests of individual La
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Registered trials
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.