Domain structures and stacking sequences of Mg-Zn-Y long-period stacking ordered (LPSO) structures predicted by Deep-learning Potential

YN Wang and XY Wang and WR Jiang and H Wang and FZ Dai, MATERIALS TODAY COMMUNICATIONS, 38, 108301 (2024).

DOI: 10.1016/j.mtcomm.2024.108301

Employing a novel Deep Potential, we comprehensively investigate interstitial atom variations, in -plane domain structures, and out-plane stacking sequences in Mg-Zn-Y long-period stacking ordered (LPSO) structures. Leveraging hybrid Monte Carlo/Molecular Dynamics simulations, we elucidate four distinct in -plane cluster patterns (P0, P1, P2, and P3) and determine the ratio of Mg and Y interstitial atoms (91.5 % and 7.1 %, respectively, with 1.5% of interstitial sites unoccupied). We provide a 3D visualization indicating P0+Mg's superior stability through detailed energy calculations. Additionally, we explore 18R and 14H out-plane stacking sequences, revealing minute energy differences surmountable by thermal activation at typical annealing temperatures (approximately 773 K). This elucidates the diverse in -plane and out-plane structures observed experimentally. Our comprehensive computational investigation illustrates the intricate differences between LPSO structures, unveiling their inherent stability, arrangement, and interplay between distinct stacking sequences.

Return to Publications page