Advanced metallic alloys can benefit from clusters of dopant atoms and intermetallic particles to improve their performance. Suhas Eswarappa Prameela, Peng Yi, Michael Falk and Tim Weihs discuss how atomic-scale defects can be used to form these clusters and particles.
This is a preview of subscription content, access via your institution
Relevant articles
Open Access articles citing this article.
-
Computed entropy spectra for grain boundary segregation in polycrystals
npj Computational Materials Open Access 12 April 2024
Access options
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$29.99 / 30 days
cancel any time
Subscribe to this journal
Receive 12 digital issues and online access to articles
$99.00 per year
only $8.25 per issue
Buy this article
- Purchase on Springer Link
- Instant access to full article PDF
Prices may be subject to local taxes which are calculated during checkout
References
Sun, W. et al. Precipitation strengthening of aluminum alloys by room-temperature cyclic plasticity. Science 363, 972–975 (2019).
Nie, J. F., Zhu, Y. M., Liu, J. Z. & Fang, X. Y. Periodic segregation of solute atoms in fully coherent twin boundaries. Science 340, 957–960 (2013).
Yang, Z. et al. Precipitation of binary quasicrystals along dislocations. Nat. Commun. 9, 809 (2018).
Prameela, S. E. et al. Deformation assisted nucleation of continuous nanoprecipitates in Mg-Al alloys. Materialia 9, 100583 (2019).
Peng, S., Wei, Y. & Gao, H. Nanoscale precipitates as sustainable dislocation sources for enhanced ductility and high strength. PNAS 117, 5204–5209 (2020).
Kuzmina, M., Herbig, M., Ponge, D., Sandlöbes, S. & Raabe, D. Linear complexions: confined chemical and structural states at dislocations. Science 349, 1080–1083 (2015).
Titus, M. S. et al. Solute segregation and deviation from bulk thermodynamics at nanoscale crystalline defects. Sci. Adv. 2, e1601796 (2016).
Katnagallu, S. et al. Imaging individual solute atoms at crystalline imperfections in metals. New J. Phys. 21, 123020 (2019).
Knaster, J., Moeslang, A. & Muroga, T. Materials research for fusion. Nat. Phys. 12, 424–434 (2016).
Kalidindi, S. R. Feature engineering of material structure for AI-based materials knowledge systems. J. Appl. Phys. 128, 041103 (2020).
Acknowledgements
The authors would like to acknowledge financial support from CCDC Army Research Laboratory, cooperative agreement number W911NF- 12-2-0022 for the Materials in Extreme Dynamic Environments Consortium. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the CCDC Army Research Laboratory or the U.S. Government.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Competing interests
The authors declare no competing interests.
Rights and permissions
About this article
Cite this article
Eswarappa Prameela, S., Yi, P., Falk, M.L. et al. Strategic control of atomic-scale defects for tuning properties in metals. Nat Rev Phys 3, 148–149 (2021). https://doi.org/10.1038/s42254-021-00287-5
Published:
Issue Date:
DOI: https://doi.org/10.1038/s42254-021-00287-5
This article is cited by
-
Computed entropy spectra for grain boundary segregation in polycrystals
npj Computational Materials (2024)
-
Precipitation during creep in magnesium–aluminum alloys
Continuum Mechanics and Thermodynamics (2021)