Surface-Induced Phase Transition During Coalescence of Au Nanoparticles: A Molecular Dynamics Simulation Study

In this study, the melting and coalescence of Au nanoparticles were investigated using molecular dynamics simulation. The melting points of nanoparticles were calculated by studying the potential energy and Lindemann indices as a function of temperature. The simulations show that coalescence of two Au nanoparticles of the same size occurs at far lower temperatures than their corresponding melting temperature. For smaller nanoparticles, the difference between melting and coalescence temperature increases. Detailed analyses of the Lindemann indices and potential energy distribution across the nanoparticles show that the surface melting in nanoparticles begins at several hundred degrees below the melting point. This suggests that the coalescence is governed by the liquid-phase surface diffusion. Furthermore, the surface reduction during the coalescence accelerates its kinetics. It is found that for small enough particles and/or at elevated temperatures, the heat released due to the surface reduction result in a melting transition of the two attached nanoparticles.Comment: 15 pages, 4 figures, 1 table, full length articl

Thickening of T1 Precipitates during Aging of a High Purity Al−4Cu−1Li−0.25Mn Alloy

The age hardening response of a high-purity Al–4Cu–1Li–0.25Mn alloy (wt. %) during isothermal aging without and with an applied external load was investigated. Plate shaped nanometer size T1 (Al2CuLi) and θ′ (Al2Cu) hardening phases were formed. The precipitates were analyzed with respect to the development of their structure, size, number density, volume fraction and associated transformation strains by conducting transmission electron microscopy (TEM) and scanning transmission electron microscopy (STEM) studies in combination with geometrical phase analysis (GPA). Special attention was paid to the thickening of T1 phase. Two elementary types of single-layer T1 precipitate, one with a Li-rich (Type 1) and another with an Al-rich (Defect Type 1) central layer, were identified. The results show that the Defect Type 1 structure can act as a precursor for the Type 1 structure. The thickening of T1 precipitates occurs by alternative stacking of these two elementary structures. The thickening mechanism was analyzed based on the magnitude of strain associated with the precipitation transformation normal to its habit plane. Long-term aging and aging under load resulted in thicker and structurally defected T1 precipitates. Several types of defected precipitates were characterized and discussed. For θ′ precipitates, a ledge mechanism of thickening was observed. Compared to the normal aging, an external load applied to the peak aged state leads to small variations in the average sizes and volume fractions of the precipitates.DFG, 237105621, SPP 1713: Stark gekoppelte thermo-chemische und thermo-mechanische Zustände in Angewandten Materialie

Giant segregation transition as origin of liquid metal embrittlement in the Fe-Zn system

A giant Zn segregation transition is revealed using CALPHAD-integrated density-based modelling of Zn segregation into Fe grain boundaries (GBs). The results show that above a threshold of only a few atomic percent Zn in the alloy, a substantial amount of up to 60 at.% Zn can segregate to the GB. We also found that the amount of segregation significantly increases with decreasing temperature, while the required Zn content in the alloy for triggering the segregation transition decreases. Direct evidence of this Zn segregation transition is obtained using high-resolution scanning transmission electron microscopy. We trace the origin of the segregation transition and its temperature dependence back to the low cohesive energy of Zn and a miscibility gap in Fe-Zn GB, arising from the magnetic ordering effect, which is demonstrated by ab initio calculations. We show that the massive Zn segregation resulting from the segregation transition greatly assists with liquid wetting and reduces the work of separation along the GB. These findings reveal the fundamental origin of GB weakening and therefore liquid metal embrittlement in the Fe-Zn system.Comment: Original work, Letter, 14 pages including supplementary material (SM), 8 figures (3 in SM), 2 tables in S

Revealing in-plane grain boundary composition features through machine learning from atom probe tomography data

Grain boundaries (GBs) are planar lattice defects that govern the properties of many types of polycrystalline materials. Hence, their structures have been investigated in great detail. However, much less is known about their chemical features, owing to the experimental difficulties to probe these features at the atomic length scale inside bulk material specimens. Atom probe tomography (APT) is a tool capable of accomplishing this task, with an ability to quantify chemical characteristics at near-atomic scale. Using APT data sets, we present here a machine-learning-based approach for the automated quantification of chemical features of GBs. We trained a convolutional neural network (CNN) using twenty thousand synthesized images of grain interiors, GBs, or triple junctions. Such a trained CNN automatically detects the locations of GBs from APT data. Those GBs are then subjected to compositional mapping and analysis, including revealing their in-plane chemical decoration patterns. We applied this approach to experimentally obtained APT data sets pertaining to three case studies, namely, Ni-P, Pt-Au, and Al-Zn-Mg-Cu alloys. In the first case, we extracted GB-specific segregation features as a function of misorientation and coincidence site lattice character. Secondly, we revealed interfacial excesses and in-plane chemical features that could not have been found by standard compositional analyses. Lastly, we tracked the temporal evolution of chemical decoration from early-stage solute GB segregation in the dilute limit to interfacial phase separation, characterized by the evolution of complex composition patterns. This machine-learning-based approach provides quantitative, unbiased, and automated access to GB chemical analyses, serving as an enabling tool for new discoveries related to interface thermodynamics, kinetics, and the associated chemistry-structure-property relations

Interstitial segregation has the potential to mitigate liquid metal embrittlement in iron

The embrittlement of metallic alloys by liquid metals leads to catastrophic material failure and severely impacts their structural integrity. The weakening of grain boundaries by the ingress of liquid metal and preceding segregation in the solid are thought to promote early fracture. However, the potential of balancing between the segregation of cohesion-enhancing interstitial solutes and embrittling elements inducing grain boundary decohesion is not understood. Here, we unveil the mechanisms of how boron segregation mitigates the detrimental effects of the prime embrittler, zinc, in a $\Sigma 5\,[0\,0\,1]$ tilt grain boundary in $\alpha-$Fe ($4~at.\%$ Al). Zinc forms nanoscale segregation patterns inducing structurally and compositionally complex grain boundary states. Ab-initio simulations reveal that boron hinders zinc segregation and compensates for the zinc induced loss in grain boundary cohesion. Our work sheds new light on how interstitial solutes intimately modify grain boundaries, thereby opening pathways to use them as dopants for preventing disastrous material failure.Comment: 29 pages, 6 figures in the main text and 10 figures in the supplementar