Separating Geometric and Diffusive Contributions to the Surface Nucleation of Dislocations in Nanoparticles.

While metal nanoparticles are widely used, their small size makes them mechanically unstable. Extensive prior research has demonstrated that nanoparticles with sizes in the range of 10-50 nm fail by the surface nucleation of dislocations, which is a thermally activated process. Two different contributions have been suggested to cause the weakening of smaller particles: first, geometric effects such as increased surface curvature reduce the barrier for dislocation nucleation; second, surface diffusion happens faster on smaller particles, thus accelerating the formation of surface kinks which nucleate dislocations. These two factors are difficult to disentangle. Here we use in situ compression testing inside a transmission electron microscope to measure the strength and deformation behavior of platinum particles in three groups: 12 nm bare particles, 16 nm bare particles, and 12 nm silica-coated particles. Thermodynamics calculations show that, if surface diffusion were the dominant factor, the last two groups would show equal strengthening. Our experimental results refute this, instead demonstrating a 100% increase in mean yield strength with increased particle size and no statistically significant increase in strength due to the addition of a coating. A separate analysis of stable plastic flow corroborates the findings, showing an order-of-magnitude increase in the rate of dislocation nucleation with a change in particle size and no change with coating. Taken together, these results demonstrate that surface diffusion plays a far smaller role in the failure of nanoparticles by dislocations as compared to geometric factors that reduce the energy barrier for dislocation nucleation.

Size-Dependent Role of Surfaces in the Deformation of Platinum Nanoparticles.

The mechanical behavior of nanostructures is known to transition from a Hall-Petch-like "smaller-is-stronger" trend, explained by dislocation starvation, to an inverse Hall-Petch "smaller-is-weaker" trend, typically attributed to the effect of surface diffusion. Yet recent work on platinum nanowires demonstrated the persistence of the smaller-is-stronger behavior down to few-nanometer diameters. Here, we used in situ nanomechanical testing inside of a transmission electron microscope (TEM) to study the strength and deformation mechanisms of platinum nanoparticles, revealing the prominent and size-dependent role of surfaces. For larger particles with diameters from 41 nm down to approximately 9 nm, deformation was predominantly displacive yet still showed the smaller-is-weaker trend, suggesting a key role of surface curvature on dislocation nucleation. For particles below 9 nm, the weakening saturated to a constant value and particles deformed homogeneously, with shape recovery after load removal. Our high-resolution TEM videos revealed the role of surface atom migration in shape change during and after loading. During compression, the deformation was accommodated by atomic motion from lower-energy facets to higher-energy facets, which may indicate that it was governed by a confined-geometry equilibration; when the compression was removed, atom migration was reversed, and the original stress-free equilibrium shape was recovered.

Size-dependent shape distributions of platinum nanoparticles.

While it is well established that nanoparticle shape can depend on equilibrium thermodynamics or growth kinetics, recent computational work has suggested the importance of thermal energy in controlling the distribution of shapes in populations of nanoparticles. Here, we used transmission electron microscopy to characterize the shapes of bare platinum nanoparticles and observed a strong dependence of shape distribution on particle size. Specifically, the smallest nanoparticles (<2.5 nm) had a truncated octahedral shape, bound by 〈111〉 and 〈100〉 facets, as predicted by lowest-energy thermodynamics. However, as particle size increased, the higher-energy 〈110〉 facets became increasingly common, leading to a large population of non-equilibrium truncated cuboctahedra. The observed trends were explained by combining atomistic simulations (both molecular dynamics and an empirical square-root bond-cutting model) with Boltzmann statistics. Overall, this study demonstrates experimentally how thermal energy leads to shape variation in populations of metal nanoparticles, and reveals the dependence of shape distributions on particle size. The prevalence of non-equilibrium facets has implications for metal nanoparticles applications from catalysis to solar energy.

Surface Area and Local Curvature: Why Roughness Improves the Bioactivity of Neural Implants.

While roughening the surface of neural implants has been shown to significantly improve their performance, the mechanism for this improvement is not understood, preventing systematic optimization of surfaces. Specifically, prior work has shown that the cellular response to a surface can be significantly enhanced by coating the implant surface with inorganic nanoparticles and neuroadhesion protein L1, and this improvement occurs even when the surface chemistry is identical between the nanoparticle-coated and uncoated electrodes, suggesting the critical importance of surface topography. Here, we use transmission electron microscopy to characterize the topography of bare and nanoparticle-coated implants across 7 orders of magnitude in size, from the device scale to the atomic scale. The results reveal multiscale roughness, which cannot be adequately described using conventional roughness parameters. Indeed, the topography is nearly identical between the two samples at the smallest scales and also at the largest scales but vastly different in the intermediate scales, especially in the range of 5-100 nm. Using a multiscale topography analysis, we show that the coating causes a 76% increase in the available surface area for contact and an order-of-magnitude increase in local surface curvature at characteristic sizes corresponding to specific biological structures. These are correlated with a 75% increase in bound proteins on the surface and a 134% increase in neurite outgrowth. The present investigation presents a framework for analyzing the scale-dependent topography of medical device-relevant surfaces, and suggests the most critical size scales that determine the biological response to implanted materials.