  Refractory multi-principal element alloys (RMPEAs) are promising materials
for high-temperature structural applications. Here, we investigate the role of
chemical short-range ordering (CSRO) on dislocation glide in two model RMPEAs -
TaNbTi and MoNbTi - using a multi-scale modeling approach. A highly accurate
machine learning interatomic potential was developed for the Mo-Ta-Nb-Ti system
and used to demonstrate that MoNbTi exhibits a much greater degree of SRO than
TaNbTi and the local composition has a direct effect on the unstable stacking
fault energies (USFE). From mesoscale phase-field dislocation dynamics
simulations, we find that increasing SRO leads to higher mean USFEs, thereby
increasing the stress required for dislocation glide. The gliding dislocations
experience significant hardening due to pinning and depinning caused by random
compositional fluctuations, with higher SRO decreasing the degree of USFE
dispersion and hence, amount of hardening. Finally, we show how the morphology
of an expanding dislocation loop is affected by the applied stress, with higher
SRO requiring higher applied stresses to achieve smooth screw dislocation
glide.
