arXiv subjects

Zuoyong Zhang

Publications and source records attributed to Zuoyong Zhang.

4 recordsLinked to original sources

arXiv2026

Predicting co-segregation in alloys with solute-solute interactions

The co-segregation of impurities in systems with multiple solute species has been widely recognized as an effective strategy for tailoring material properties. However, reliable predictions of co-segregation behavior remain a significant challenge for alloy design in these systems. In this work, we develop an extended dual-solute (DS) segregation framework to semi-quantitatively predict co-segregation behavior with solute-solute interactions, including both homoatomic and heteroatomic contributions. A machine-learning workflow is first established to predict the pairwise segregation energy to construct the DS segregation energy spectra that intrinsically include both types of solute-solute interactions. The resulting spectral information is then used to determine the upper and lower bounds of segregation for individual solute species. When applied to magnesium-based ternary systems constructed by alloying Mg with any two of the 11 candidate solute species (Ag, Al, Ca, Co, Cu, Gd, Nd, Ni, Pb, Pd, and Zn), the extended DS segregation framework is successfully validated by hybrid molecular dynamics/Monte Carlo simulations and experimental results available in the literature. Furthermore, we introduce a design strategy to promote co-segregation by incorporating additional solute species that exhibit attractive interactions with existing solutes, thereby enabling enhanced co-segregation even in the presence of strong site competition. These results underscore the critical role of solute-solute interactions in governing co-segregation behavior and provide a predictive pathway for the design and optimization of alloys.

cond-mat.mtrl-sci↗

arXiv2026

Disconnection formation via segregation-induced grain boundary phase transitions

Disconnections, long recognized as the key mediators of grain boundary (GB) kinetics in polycrystalline materials, have traditionally been understood to nucleate through thermal or mechanical activation. In this work, using atomistic simulations, we reveal a distinct nucleation mechanism driven exclusively by solute interstitial segregation across multiple substitutional binary alloy systems (e.g., Al-Ni, Al-Fe). This process exhibits zero-nucleation energy barriers, contrasting sharply with the nucleation mechanisms in pure systems. We identify states that are activated through segregation-induced GB phase transitions: (i) isolated disconnections or phase junctions that promote GB migration and disappear with continuous segregation, and (ii) composite disconnections that are formed via two oppositely oriented isolated disconnections. The disconnections are mechanically robust, suppressing shear-coupled migration and instead resulting in GB amorphization and pure sliding under applied shear loading. The long-range stress fields associated with these composite disconnections further attract solute atoms and assist the nucleation of precipitates. These disconnections, absent in pure materials, follow unique nucleation pathways as confirmed through dichromatic pattern analysis and persist across different alloy chemistries and crystal structures. Our findings demonstrate that solute interstitial segregation provides a powerful and previously unrecognized pathway for barrier-free disconnection formation, thereby fundamentally extending current understanding of GB kinetics in alloy systems.

cond-mat.mtrl-sci↗

arXiv2025

Grain boundary interstitial segregation in substitutional binary alloys

Grain boundary (GB) segregation is a powerful approach for optimizing the thermal and mechanical properties of metal alloys. In this study, we report significant GB interstitial segregation in a representative substitutional binary alloy system (Al-Ni) through atomistic simulations, challenging prevailing assumptions in the literature. Our findings show that Ni atoms preferentially segregate to interstitial sites within numerous kite-like GB structures in the Al bicrystals. An intriguing interplanar interstitial segregation pattern was also observed and analyzed. Additionally, interstitial segregation can induce unexpected GB transitions, such as kite transitions and nano-faceting, due to the existence of small interstitial sites. Building upon these observations, we developed a robust method to systematically identify the interstitial candidate sites for accommodating solutes at GBs. This approach combines site detection with structural filtering to produce distributions of interstitial sites that closely match atomistic simulation results. Applied to nanocrystalline alloys, this method enabled the calculation of interstitial segregation energies, significantly improving GB segregation predictions for the Al-Ni system. Furthermore, machine learning models using smooth overlap of atomic positions descriptors successfully predicted per-site interstitial segregation energy. This study highlights the critical role of GB interstitial segregation in advancing our understanding of solute behavior and provides valuable insights for designing next-generation alloys.

cond-mat.mtrl-sci↗

arXiv2024

Grain boundary segregation prediction with a dual-solute model

Solute segregation along grain boundaries (GBs) profoundly affects their thermodynamic and kinetic behaviors in polycrystalline materials. Recently, the spectral approach has emerged as a powerful tool to predict GB segregation. However, previous GB segregation predictions using this method relied heavily on single-solute segregation energy spectrum without solute-solute interactions, which were often incorporated through a fitting parameter. In this work, we developed a dual-solute model whose segregation energy spectrum intrinsically incorporates solute-solute interactions. It was first validated for GB segregation prediction in the Al-Mg system and then extended to several other distinct binary alloy systems. The dual-solute model shows significant improvement over the single-solute model and can accurately predict the real segregation states obtained by hybrid Molecular Dynamics/Monte Carlo simulations within a broad temperature range with different solute concentrations before forming secondary phases. This dual-solute model provides an effective method for accurately predicting GB segregation in nanocrystalline metals.

cond-mat.mtrl-sci↗