Extensive atomistic simulations based on the quasiparticle (QA) approach are performed to determine the momentous aspects of the displacive fcc/bcc phase transformation in a binary system. We demonstrate that the QA is able to predict the major struc
tural characteristics of fcc/bcc phase transformations, including the growth of a bcc nuclei in a fcc matrix, and eventually the formation of an internally twinned structure consisting in two variants with Kurdjumov-Sachs orientation relationship. At atomic level, we determine the defect structure of twinning boundaries and fcc/bcc interfaces, and identify the main mechanism for their propagation. In details, it is shown that twin boundaries are propagated by the propagation of screw dislocations in fcc along the <-1-11>_{alpha} direction, while the propagation of fcc screw dislocations along coherent terrace edges is the pivotal vector of the fcc/bcc transformation. The simulation results are compared with our TEM and HRTEM observations of Fe-rich bcc twinned particle embedded in the fcc Cu-rich matrix in the Cu-Fe-Co system.
Snowflake growth provides us with a fascinating example of spontaneous pattern formation in nature. Attempts to understand this phenomenon have led to important insights in non-equilibrium dynamics observed in various active scientific fields, rangin
g from pattern formation in physical and chemical systems, to self-assembly problems in biology. Yet, very few models currently succeed in reproducing the diversity of snowflake forms in three dimensions, and the link between model parameters and thermodynamic quantities is not established. Here, we report a modified phase field model that describes the subtlety of the ice vapour phase transition, through anisotropic water molecules attachment and condensation, surface diffusion, and strong anisotropic surface tension, that guarantee the anisotropy, faceting and dendritic growth of snowflakes. We demonstrate that this model reproduces the growth dynamics of the most challenging morphologies of snowflakes from the Nakaya diagram. We find that the growth dynamics of snow crystals matches the selection theory, consistently with previous experimental observations.
Understanding ballistic effects caused by ion beam irradiation, and linking them with induced structure can be a key point for controlling and predicting the microstructure of irradiated materials. For this purpose, we have investigated ballistic eff
ects from an ion mixing formalism point of view. The displacement cascades in copper and AgCu alloy were obtained using binary collision approximation (BCA) and molecular dynamics (MD) simulations. We employed BCA-based code MARLOWE for its ability to simulate high energy displacement cascades. A first set of simulations was performed using both methods on pure copper for energies ranging from 0.5 keV to 20 keV. The results of BCA and MD simulations are compared, evidencing rationally parametrized MARLOWE to be predictive. A second set of simulations was then carried out using BCA only. Following experimental studies, AgCu alloy was subjected to 1 MeV krypton ions. MARLOW simulations are found to be in good agreement with experimental results.
The study makes use of polynomial chaos expansions to compute Sobol indices within the frame of a global sensitivity analysis of hydro-dispersive parameters in a simplified vertical cross-section of a segment of the subsurface of the Paris Basin. App
lying conservative ranges, the uncertainty in 78 input variables is propagated upon the mean lifetime expectancy of water molecules departing from a specific location within a highly confining layer situated in the middle of the model domain. Lifetime expectancy is a hydrogeological performance measure pertinent to safety analysis with respect to subsurface contaminants, such as radionuclides. The sensitivity analysis indicates that the variability in the mean lifetime expectancy can be sufficiently explained by the uncertainty in the petrofacies, ie the sets of porosity and hydraulic conductivity, of only a few layers of the model. The obtained results provide guidance regarding the uncertainty modeling in future investigations employing detailed numerical models of the subsurface of the Paris Basin. Moreover, the study demonstrates the high efficiency of sparse polynomial chaos expansions in computing Sobol indices for high-dimensional models.
