Microscopic mechanisms of cooperative communications within single nanocatalysts

Catalysis is a method of accelerating chemical reactions that is critically important for fundamental research as well as for industrial applications. It has been recently discovered that catalytic reactions on metal nanoparticles exhibit cooperative effects. The mechanism of these observations, however, remains not well understood. In this work, we present a theoretical investigation on possible microscopic origin of cooperative communications in nanocatalysts. In our approach, the main role is played by positively charged holes on metal surfaces. A corresponding discrete-state stochastic model for the dynamics of holes is developed and explicitly solved. It is shown that the observed spatial correlation lengths are given by the average distances migrated by the holes before they disappear, while the temporal memory is determined by their lifetimes. Our theoretical approach is able to explain the universality of cooperative communications as well as the effect of external electric fields. Theoretical predictions are in agreement with experimental observations. The proposed theoretical framework quantitatively clarifies some important aspects of the microscopic mechanisms of heterogeneous catalysis.

Towards a Quantitative Cartography of the Grain Boundary Energy Landscape: Paths and Correlations

We apply a newly developed Voronoi fundamental zone (VFZ) framework to gain insights about grain boundary (GB) structure-property relationships in the five degree-of-freedom (5DOF) space of cubic GBs. We analyze the shape and size of a 5DOF fundamental zone (FZ), molecular statics energy uncertainty, property similarity of GBs that are crystallographically \close" (i.e. correlations), and energy pathways through 5DOF space. Considered together, these insights are important for managing tradeoffs between accuracy, complexity, and design considerations for electron backscatter diffraction/serial sectioning, high-energy diffraction microscopy, molecular statics, and density-functional theory. In terms of the shape and size of a 5DOF FZ, we discover that a FZ is smaller than expected at only ∼65° in the largest principal component. Thus, a 10° difference between two GBs, which may have previously been considered small, is actually quite large. We represent a GB by five transformed Cartesian coordinates equipped with a Euclidean distance metric. Using this representation, we find that the FZ has a low aspect-ratio shape (i.e. width, length, height, etc. are similar) which is important for 5DOF numerical differentiation. Semivariogram and numerical optimization methods reveal that grain boundary energy (GBE) in Ni and Fe are globally correlated within ∼6° to 8° in the grain boundary octonion (GBO) sense (multiply by 2 to convert to misorientation angle). For local correlation lengths of high-symmetry GBs of interest, we notice significant variation relative to global correlation lengths and an inverse relationship with the Brandon criterion. We suggest that property data with no more than ± ∼3 % error and point sets with GBs that are no more than ∼3−4° apart should be used and then paired with high-fidelity interpolation strategies. Finally, in terms of dynamic material behavior, geodesic paths through 5DOF space for Ni suggest that, under appropriate conditions, a certain low-energy Σ7 GB may transform into the frequently observed Σ3 coherent-twin GB which may be interesting to verify by experiment or simulation.

Microstructural and Energy-Dispersive X-ray Analyses on Argon Ion Implantations in Tantalum Thin Films for Microelectronic Substrates

In the present study, the microstructural and statistical properties of unimplanted in comparison to argon ion-implanted tantalum-based thin film surface structures are investigated for potential application in microelectronic thin film substrates. In the study, the argon ions were implanted at the energy of 30 keV and the doses of 1×1017, 3×1017, and 7×1017 (ion/cm2) at an ambient temperature. Two primary goals have been pursued in this study. First, by using atomic force microscopy (AFM) analysis, the roughness of samples, before and after implantation, has been studied. The corrosion apparatus wear has been used to compare resistance against tantalum corrosion for all samples. The results show an increase in resistance against tantalum corrosion after the argon ion implantation process. After the corrosion test, scanning electron microscopy (SEM) analysis was applied to study the sample morphology. The elemental composition of the samples was characterized by using energy-dispersive X-ray (EDX) analysis. Second, the statisticalcharacteristics of both unimplanted and implanted samples, using the monofractal analysis with correlation function and correlation length of samples, were studied. The results show, however, that all samples are correlated and that the variation of ion doses has a negligible impact on the values of correlation lengths. Moreover, the study of height distribution and higher-order moments show the deviation from Gaussian distribution. The calculations of the roughness exponent and fractal dimension indicates that the implanted samples are the self-affine fractal surfaces.

Concentration Dependent Single Chain Properties of Poly(Sodium 4-Styrenesulfonate) Subjected to Aromatic Interactions with Chlorpheniramine Maleate Studied by Diafiltration and Synchrotron-SAXS

The polyelectrolyte poly(sodium 4-styrenesulfonate) undergoes aromatic–aromatic interaction with the drug chlorpheniramine, which acts as an aromatic counterion. In this work, we show that an increase in the concentration in the dilute and semidilute regimes of a complex polyelectrolyte/drug 2:1 produces the increasing confinement of the drug in hydrophobic domains, with implications in single chain thermodynamic behavior. Diafiltration analysis at polymer concentrations between 0.5 and 2.5 mM show an increase in the fraction of the aromatic counterion irreversibly bound to the polyelectrolyte, as well as a decrease in the electrostatic reversible interaction forces with the remaining fraction of drug molecules as the total concentration of the system increases. Synchrotron-SAXS results performed in the semidilute regimes show a fractal chain conformation pattern with a fractal dimension of 1.7, similar to uncharged polymers. Interestingly, static and fractal correlation lengths increase with increasing complex concentration, due to the increase in the amount of the confined drug. Nanoprecipitates are found in the range of 30–40 mM, and macroprecipitates are found at a higher system concentration. A model of molecular complexation between the two species is proposed as the total concentration increases, which involves ion pair formation and aggregation, producing increasingly confined aromatic counterions in hydrophobic domains, as well as a decreasing number of charged polymer segments at the hydrophobic/hydrophilic interphase. All of these features are of pivotal importance to the general knowledge of polyelectrolytes, with implications both in fundamental knowledge and potential technological applications considering aromatic-aromatic binding between aromatic polyelectrolytes and aromatic counterions, such as in the production of pharmaceutical formulations.

MODELING AND CALIBRATION OF UNCERTAINTY IN MATERIAL PROPERTIES OF ADDITIVELY MANUFACTURED COMPOSITES

Simulations quantifying the uncertainty in structural response and damage evolution require accurate representation of the randomness of the underlying material stiffness and strength behaviors. In this paper, the mean and variance descriptions of variability of strength and stiffness of additively manufactured composite specimens are augmented with random field correlation descriptors that represent the process dependence on the property heterogeneity through microstructure variations. Two correlation lengths and a rotation parameter are introduced into randomized stiffness and strength distribution fields to capture the local heterogeneities in the microstructure of Additively Manufactured (AM) composites. We formulated a simulation and Artificial Intelligence (AI)-based technique to calibrate the correlation length and rotation parameter measures from relatively few samples of experimentally obtained strain field observations using Digital Image Correlation (DIC). The neural networks used for calibrating the correlation lengths of Karhunen-Loève Expansion (KL expansion) from the DIC images are trained using simulated stiffness and strength fields that have known correlation coefficients. A virtual DIC filter is used to add the noise and artifacts from typical DIC analysis to the simulated strain fields. A Deep Neural Network (DNN), whose architecture is optimized using Efficient Neural Architecture Search (ENAS), is trained on 150,000 simulated DIC images. The trained DNN is then used for calibration of KL expansion correlation lengths for additively manufactured composite specimens. The AM composites are loaded in tension and DIC images of the strain fields are generated and presented to the DNNs, which produce the correlation coefficients for the random fields as outputs. Compared to classical optimization methods to calibrate model parameters iteratively, neural networks, once trained, efficiently and quickly predict parameters without the need for a robust simulator and optimization methods.

Tungsten Based Spectrally Selective Absorbers with Anisotropic Rough Surface Texture

Spectrally selective absorbers have received considerable interest due to their applications in thermophotovoltaic devices and as solar absorbers. Due to extreme operating conditions in these applications, such as high temperatures, thermo-mechanically stable and broadband spectrally selective absorbers are of interest. This paper demonstrates anisotropic random rough surfaces that provide broadband spectrally selective absorption for the thermo-mechanically stable Tungsten surfaces. Anisotropic random rough surface has different correlation lengths in the x- and y-directions, which means their topography parameters have directional dependence. In particular, we demonstrate that spectral absorptance of Tungsten random rough surfaces at visible (VIS) and near-infrared (NIR) spectral regions are sensitive to correlation length and RMS height variations. Our results indicate that by optimizing random rough surface parameters, absorption values exceeding 95% can be obtained. Moreover, our results indicate that anisotropic random rough surfaces broaden the bandwidth of the high absorption region. It is shown that in VIS and NIR regions, the absorption enhancements of up to 47% and 52% are achieved for the isotropic and anisotropic rough surfaces, respectively.

Reconstruction of the magnetic connection from Mercury to the solar corona, during events in the solar proton fluxes observed by MESSENGER

<p>We present a study conducted on a number of selected events characterised by a significant increase in the solar proton fluxes measured by FIPS-MESSENGER during the period 2011-2013. For each of them, the magnetic connection between Mercury and the solar corona (Source Surface Field @2.5 R<sub>S</sub>) has been reconstructed, in order to identify the possible source of the accelerated particles on the solar surface. The transport of the magnetic field lines in the heliosphere is here evaluated with a Monte Carlo code that computes a random displacement at each step of the integration along the Parker magnetic field model. Such displacement is proportional to a “local” diffusion coefficient, which is a function of the fluctuation level and magnetic turbulence correlation lengths. The simulation is tailored to the specific events by using the observed values of solar wind velocity and magnetic fluctuation levels.</p>

Condensate Formation in Collisionless Plasma

Particle condensates in general magnetic mirror geometries in high-temperature plasmas may be caused by a discrete resonance with thermal ion-acoustic background noise near mirror points. The resonance breaks the bounce symmetry, temporally locking the particles to the resonant wavelength. The relevant correlation lengths are the Debye length in the parallel direction and the ion gyroradius in the perpendicular direction.

Dislocation interactions in olivine control postseismic creep of the upper mantle

Changes in stress applied to mantle rocks, such as those imposed by earthquakes, commonly induce a period of transient creep, which is often modelled based on stress transfer among slip systems due to grain interactions. However, recent experiments have demonstrated that the accumulation of stresses among dislocations is the dominant cause of strain hardening in olivine at temperatures ≤600 °C, raising the question of whether the same process contributes to transient creep at higher temperatures. Here, we demonstrate that olivine samples deformed at 25 °C or 1150–1250 °C both preserve stress heterogeneities of ~1 GPa that are imparted by dislocations and have correlation lengths of ~1 μm. The similar stress distributions formed at these different temperatures indicate that accumulation of stresses among dislocations also provides a contribution to transient creep at high temperatures. The results motivate a new generation of models that capture these intragranular processes and may refine predictions of evolving mantle viscosity over the earthquake cycle.