Concentration dependence of the crystal nucleation kinetics in undercooled Cu-Ge melts.

The crystallization temperature of deeply undercooled Cu-Ge alloy melts is repeatedly measured. A statistical analysis is applied on the undercooling distributions obtained from nine different compositions, ranging from the pure semimetal (Ge) to the pure metal (Cu). By considering each undercooling distribution as an inhomogeneous Poisson process, the nucleation rates for every composition are calculated. The Thompson-Spaepen model for homogeneous nucleation in binary alloys is applied, enabling the estimation of nucleation parameters, such as kinetic pre-factors and interfacial energies, as a function of composition. Furthermore, the Turnbull coefficient α, a dimensionless solid-liquid interfacial energy constant, is also calculated as a function of alloy constitution, suggesting a dependence on the liquid composition. The composition-dependent changes of α are of considerable importance, since the α is originally defined for pure systems as a quantity dependent on crystal structure, and is nevertheless used for describing nucleation kinetics of binary and glass forming multi-component alloy systems.

Impact of plastic deformation and shear band formation on the boson heat capacity peak of a bulk metallic glass.

The effect of annealing on the low-temperature heat capacity of a bulk Pd38.5Ni40P21.5 metallic glass is investigated for as-quenched and deformed (rolled) states. Although the boson heat capacity peak increases with increasing strain, it relaxes faster and to a lower level compared to that of the as-quenched state after annealing treatments both below and above the glass transition temperature Tg. The glass is found to retain a certain "memory" on the room-temperature plastic deformation even after annealing above Tg. Indications for two counteracting processes that might be related to different types of shear bands are observed.

Analysis of medium-range order based on simulated segmented ring detector STEM-images: amorphous Si.

Properties of amorphous materials are connected to the local structure at the nanoscale, which is typically described in terms of short- and medium-range order (SRO, MRO). Variable resolution fluctuation electron microscopy (VR-FEM) is a sensitive method to characterize the underlying characteristic length scale of MRO of amorphous samples (Voyles, Gibson and Treacy, J. Electron Microsc. 49 (2000) 259). VR-FEM data was acquired using scanning transmission electron microscopy (STEM), collecting a large number of nano-beam diffraction patterns (NBDPs) with various probe sizes. Here we present an advanced method to accelerate the calculation of simulated FEM normalized variance profiles using a newly developed simulation and analysis approach with segmented ring detectors using the program STEMcl (Radek et al., Ultramicroscopy 188 (2018) 24). VR-FEM simulations are based on structures obtained from molecular dynamics (MD) simulations. A comparison between simulated and experimental VR-FEM profiles with respect to peak position, ratio and shape (and intensity) show good agreement. Moreover, a crystalline cluster of 1 nm in size was embedded into the MD box to test the validity of the paracrystalline approximation with the pair-persistence analysis suggested by Gibson et al. (Gibson, Treacy and Voyles, Ultramicroscopy 83 (2000) 169). The corresponding VR-FEM simulation and calculation of MROs yield close results to the size of the initially embedded crystalline cluster, which supports both the paracrystalline approach and the validity of the segmented detector simulation. Additionally, we conclude that continuous random network (CRN) amorphous silicon models contain a higher degree of MRO than experimentally expected.

STEMcl-A multi-GPU multislice algorithm for simulation of large structure and imaging parameter series.

Electron microscopy images are interference patterns and can generally not be interpreted in a straight forward manner. Typically, time consuming numerical simulations have to be employed to separate specimen features from imaging artifacts. Directly comparing numerical predictions to experimental results, realistic simulation box sizes and varying imaging parameters are needed. In this work, we introduce an accelerated multislice algorithm, named STEMcl, that is capable of simulating series of large super cells typical for defective and amorphous systems, in addition to parameter series using the massive parallelization accessible in today's commercial PC-hardware, e.g. graphics processing units (GPUs). A new numerical approach is used to overcome the memory constraint limiting the maximum computable system size. This approach creates the possibility to study systematically the contrast formation arising by structural differences. STEM simulations of structure series of a crystalline Si and an amorphous CuZr system are presented and the contrast formation of vacancies/voids are studied. The detectability of vacancies/voids in STEM experiments is discussed in terms of density changes.