High strain rate persistence of the strength anomaly in the L12 intermetallic compound Ni3Si evidenced by nanoindentation testing.

Saved in:
Bibliographic Details
Title: High strain rate persistence of the strength anomaly in the L12 intermetallic compound Ni3Si evidenced by nanoindentation testing.
Authors: Merle, Benoit1 (AUTHOR) benoit.merle@uni-kassel.de, Walker, Christopher C.2 (AUTHOR), Zenk, Christopher H.3 (AUTHOR), Pharr, George M.2 (AUTHOR)
Source: Acta Materialia. Jan2025, Vol. 284, pN.PAG-N.PAG. 1p.
Subjects: Strain rate, Intermetallic compounds, Jet engines, Nanoindentation tests, High temperatures
Abstract: L1 2 intermetallic compounds are essential constituents of the nickel-based superalloys widely used in jet engines. They derive their exceptional high-temperature mechanical properties from the yield strength anomaly mechanism. Despite potential safety implications for collisions, e.g. bird strikes, conclusive evidence of its persistence at high strain rates has remained elusive. This is mostly due to experimental limitations, which are overcome here by combining high strain rate and high temperature testing within a single nanoindentation testing system to investigate the evolution of the strength anomaly in the L1 2 single-phase Ni 3 Si for strain rates between 0.1 and 100 s−1. High strain rates are found to extend the anomalous behavior toward higher temperatures, while the onset and peak temperatures of the strength anomaly remain largely insensitive to the applied strain rate. These experimental findings validate basic assumptions from the Paidar–Pope–Vitek (PPV) theory of its origin. In addition, high strain rates are found to increase the peak anomalous hardness, owing to the overall positive strain rate sensitivity of the L1 2 compound. [Display omitted] [ABSTRACT FROM AUTHOR]
Copyright of Acta Materialia is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
Be the first to leave a comment!
You must be logged in first