Interference Effects in Nanocrystalline Systems
- 527 Downloads
Interference (cross-correlation) effects are present in the X-ray powder diffraction pattern of a polycrystalline aggregate. In an experimental diffraction pattern, the information is highly overlapped and can be confused with other effects. In this article, it is shown that the analysis of the patterns calculated from a cluster equilibrated via molecular dynamics simulation allows those effects to be separated. Extra intensity is observed, because of the presence of the grain boundaries contribution which is unexpectedly not that of an amorphous phase.
Recent studies have shown how interference effects can be observed in the diffraction from polycrystalline systems when scattering domains are sufficiently small and textured.[1, 2, 3, 4, 5] Besides loose nanocrystalline powders, where the above conditions can arise from special growth or coalescence phenomena,[6,7] these effects are important also in polycrystalline aggregates as they can influence the overall properties of the system.
Models have been proposed to describe the special condition when the diffracted intensity distributions from small and closely oriented domains overlap in Reciprocal Space (RS), thus affecting the observed powder patterns in different ways.[1, 2, 3, 4, 5] This is especially visible for low Miller indices peak profiles, corresponding RS points of which are closer to the origin. Further insights have been provided by a few recent studies, where interference effects among the nanosized metallic domains were simulated using atomistic models and the Debye scattering equation (DSE)[8,9] to generate the corresponding powder patterns.[10,11]
In all of these cases, however, interference was related to the size and orientation of the domains without the consideration of the role of grain boundaries, which indeed contribute a considerable fraction to nano-scale materials (see, e.g., References 12 through 14). Models and simulations so far have treated nanocrystals as small (perfect) single crystals, without accounting for the boundary region and of the natural tendency of the system to achieve a minimum of energy. In the current study, we provide a preliminary understanding of the possible effects of the grain boundary (GB) on the diffraction patterns from systems made of small crystalline domains. In particular, it is shown that the signal from the GB region can be partly coherent with the bulk of the neighboring crystalline domains.
2 Generation of the Nano-Polycrystalline Model
Once stationary conditions were reached, a sequence of 100 independent frames was collected each 1 ps. The position of each atom (labeled with the grain ID) was averaged over the collected dataset in order to remove any dynamic (thermal) component. A powder diffraction pattern was computed via DSE for each of those averaged datasets; the PowDOG code running on a cluster of NVIDIA GPUs was employed. Because of the averaging, these diffraction patterns contain only information on size and static displacements: local distortion, non-crystalline features, and defects contributions to line profile broadening can therefore be more easily separated.
3 Results and Discussion
To study the interference effects, we can use a plot of the difference between those contributions, i.e., between the pattern of the cluster and the sum of the patterns of the contributing grains (interference effects plot, IEP). As shown in this and in the following figures, the effect is clearly visible and is peaked around the Bragg positions.
The IEPs in the lower part of Figure 3 show that interference effects are quite small for (i), in agreement with the recent study by Gelisio and Scardi. Quite surprisingly, the interference component increases with energy minimization (ii) and even further after MD equilibration (iii). As already pointed out, the latter step mostly rearranges atoms in the GB region, with negligible grain rotations; it is therefore clear that the main contribution to interference comes from the GB.
The first group (a) gives powder patterns typical of fcc structures, with a progressive broadening of the Bragg’s peaks caused by the decrease in grain size, from CL1 to CL3. The pattern produced by GB atoms (b) gives a main diffuse scattering component with a Bragg’s component which is only visible for low Miller indices; the latter effect is due to the high disorder in the GB that enhances line broadening with the scattering vector until it cannot be distinguished from the diffuse scattering component. For increasing layer removal, the Bragg’s component sharpens, as it includes more correlations between distant atom couples. The last group (c) shows that the correlation between GB atoms and grain cores also consists of a diffuse scattering component, but the Bragg’s signal is stronger than that in (b).
An experimental validation of the arguments presented here is difficult to obtain in practice, as it is impossible to separate in this easy way the constituents of a diffraction pattern. The results are therefore tightly bound to the performance of the MD (thus to the choice of microstructure and potentials) and to its appropriateness in representing the microstructure of the cluster analyzed here. MD is known to provide a realistic representation of a material when limited to equilibration effects like those shown here. The use of a particular MD model does not change the fact that GBs are clearly different than the cores: it is therefore likely that interference effects due to the presence of the GB are present in a real microstructure as well.
Molecular dynamics applied to a nano-polycrystalline cluster allowed the various contributions to the diffraction pattern (static, thermal, defects, grain boundaries, etc.) to be singled out. In particular, it was shown in this study that the diffraction pattern of a cluster is not the mere sum of the contributions from all grains, but additionally diffuse and broadening effects are present. These effects are due to the interference of the grains in the cluster, and in particular they are mainly caused by the particular structure of grain boundaries.
The authors wish to thank Mr Luca Gelisio for his useful discussions and providing support with the PowDOG software.
- 11.L. Gelisio and P. Scardi: J. Nanosci. Nanotechnol., 2012, vol. 12, in press.Google Scholar
- 17.J.K. Mackenzie: Biometrika, 1958, vol. 45, pp. 229–240.Google Scholar
- 21.A. Leonardi, K.R. Beyerlein, T. Xu, M. Li, M. Leoni, and P. Scardi, Z. Kristall. Proc., 2011, vol. 1, pp. 37–42.Google Scholar