@article {1851,
	title = {Perspective: Machine learning in experimental solid mechanics},
	journal = {Journal of the Mechanics and Physics of Solids},
	volume = {173},
	year = {2023},
	month = {04},
	pages = {105231},
	doi = {10.1016/j.jmps.2023.105231},
	author = {Brodnik, N.R. and Muir, C. and Tulshibagwale, N. and Rossin, J. and Echlin, M.P. and Hamel, C.M. and Kramer, S.L.B. and Pollock, T.m. and Kiser, J.D. and Smith, C. and Daly, S.H.}
}
@article {1761,
	title = {Precipitate Shearing, Fault Energies, and Solute Segregation to Planar Faults in Ni-, CoNi-, and Co-Base Superalloys},
	journal = {Annual Review of Materials Research},
	volume = {51},
	year = {2021},
	pages = {209-240},
	abstract = {<p>
	The mechanical properties of superalloys are strongly governed by the resistance to shearing of ordered precipitates by dislocations. In the operating environments of superalloys, the stresses and temperatures present during thermomechanical loading influence the dislocation shearing dynamics, which involve diffusion and segregation processes that result in a diverse array of planar defects in the ordered L12 \&gamma;\&prime; precipitate phase. This review discusses the current understanding of high-temperature deformation mechanisms of \&gamma;\&prime; precipitates in two-phase Ni-, Co-, and CoNi-base superalloys. The sensitivity of planar fault energies to chemical composition results in a variety of unique deformation mechanisms, and methods to determine fault energies are therefore reviewed. The degree of chemical segregation in the vicinity of planar defects reveals an apparent phase transformation within the parent \&gamma;\&prime; phase. The kinetics of segregation to linear and planar defects play a significant role in high-temperature properties. Understanding and controlling fault energies and the associated dislocation dynamics provide a new pathway for the design of superalloys with exceptional properties.
</p>
},
	doi = {10.1146/annurev-matsci-102419-011433},
	url = {https://doi.org/10.1146/annurev-matsci-102419-011433},
	author = {Eggeler, Y.M. and Vamsi, K.V. and Pollock, T.m.}
}
