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Register a new userStatistical characterization of the yield stress of nanoparticles
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Atomistic simulations are performed to study the statistical mechanical property of gold nanoparticles. It is demonstrated that the yielding behavior of gold nanoparticles is governed by dislocation nucleation around surface steps. Since the nucleation of dislocations is an activated process with the aid of thermal fluctuation, the yield stress at a specific temperature should exhibit a statistical distribution rather than a definite constant value. Molecular dynamics simulations reveal that the yield stress follows a Gaussian distribution at a specific temperature. As the temperature increases, the mean value of yield stress decreases while the width of distribution becomes larger. Based on numerical analysis, the dependence of the mean yield stress on temperature can be well described by a parabolic function. Present study illuminates the statistical features of the yielding behavior of nanostructured elements.
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The results of density functional theory calculations and measurements using X-ray photoelectron spectroscopy of Co-nanoparticles dispersed on graphene/Cu are presented. It is found that for low cobalt thickness (0.02 nm - 0.06 nm) the Co forms islands distributed non-homogeneously which are strongly oxidized under exposure to air to form cobalt oxides. At greater thicknesses up to 2 nm the upper Co-layers are similarly oxidized whereas the lower layers contacting the graphene remain metallic. The measurements indicate a Co2+ oxidation state with no evidence of a 3+ state appearing at any Co thickness, consistent with CoO and Co[OH]2. The results show that thicker Co (2nm) coverage induces the formation of a protective oxide layer while providing the magnetic properties of Co nanoparticles.
Normal stresses in complex fluids lead to new flow phenomena because they can be comparable to or even larger than the shear stress itself. In addition, they are of paramount importance for formulating and testing constitutive equations for predicting non-viscometric flow behavior. Very little attention has so far been paid to the normal stresses of yield stress fluids, mainly because they are very difficult to measure. We report the first systematic study of the first and second normal stress differences, N1 (>0) and N2 (<0), in both continuous and oscillatory shear of three model yield stress fluids. We show that both normal stress differences are quadratic functions of the shear stress both above and below the shear yield stress, leading to the existence of a yield normal stress.
We report a novel synthesis for near monodisperse, sub-10-nm Bi2Te3 nanoparticles. At first, a new reduction route to bismuth nanoparticles is described which are applied as starting materials in the formation of rhombohedral Bi2Te3 nanoparticles. After ligand removal by a novel hydrazine hydrate etching procedure, the nanoparticle powder is spark plasma sintered to a pellet with preserved crystal grain sizes. Unlike previous works on the properties of Bi2Te3 nanoparticles, the full thermoelectric characterization of such sintered pellets shows a highly reduced thermal conductivity and the same electric conductivity as bulk n-type Bi2Te3.
Soft glassy materials such as mayonnaise, wet clays, or dense microgels display under external shear a solid-to-liquid transition. Such a shear-induced transition is often associated with a non-monotonic stress response, in the form of a stress maximum referred to as stress overshoot. This ubiquitous phenomenon is characterized by the coordinates of the maximum in terms of stress $sigma_text{M}$ and strain $gamma_text{M}$ that both increase as weak power laws of the applied shear rate. Here we rationalize such power-law scalings using a continuum model that predicts two different regimes in the limit of low and high applied shear rates. The corresponding exponents are directly linked to the steady-state rheology and are both associated with the nucleation and growth dynamics of a fluidized region. Our work offers a consistent framework for predicting the transient response of soft glassy materials upon start-up of shear from the local flow behavior to the global rheological observables.
Using a simple mathematical model, we demonstrate that statistical kinetics of phase-transforming nanoparticles in porous electrodes results in macroscopic non-monotonic transient currents, which could be misinterpreted as the nucleation and growth mechanism by the Kolmogorov-Johnson-Mehl-Avrami (KJMA) theory. Our model decouples the roles of nucleation and surface reaction in the electrochemically driven phase-transformation process by a special activation rate and the mean particle-filling speed of active nanoparticles, which can be extracted from the responses of porous electrodes to identify the dynamics in single composing nanoparticles.
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