Efficiency of shear-induced agglomeration of particulate suspensions subjected to bridging flocculation

This study examines the problem of shear-induced agglomeration of particles such as fillers and pigments in polymer solutions, where polymer molecules adsorb on the surface of particles and form a bridge between them causing agglomeration. The rate of agglomeration is usually obtained by multiplying the rate of collision of particles by the collision efficiency. In a laminar flow field, the collision frequency is readily given by Smoluchowski\u27s expression. If agglomeration takes place by coagulation, the collision efficiency is well studied and the influences of hydrodynamic and colloidal forces are well understood. In case of polymer bridging, the collision efficiency is determined by probabilistic models based on fractional surface coverage of particles by the adsorbing polymer, neglecting the influence of hydrodynamic forces. A new model is required to determine the collision efficiency in case of shear-induced agglomeration of non-colloidal size particles by polymer bridging.;In this work, a new model is developed in terms of dimensionless groups and the fractional surface coverage. The dimensionless groups represent the relative magnitudes of the colloidal, hydrodynamic and steric forces. An expression for the optimum surface coverage needed to achieve the maximum collision efficiency is also obtained. In particular, a model is presented for the case where surface of the particles is completely covered by a polymer layer.;To validate this model, experimental collision efficiencies at various agglomeration conditions are determined by shearing a model suspension in a cone-and-plate device. The model suspension consisted of 4.9 mum diameter spherical hollow glass beads dispersed in an aqueous glycerin solution; polyethylene oxide was used as the flocculant. Using experimental collision efficiencies and non-linear regression analysis, the parameters in the collision efficiency model were determined.;It was found that increasing the shear rate decreases the collision efficiency and it can be expressed as a power law. Increasing the molecular weight and concentration of flocculant also gives higher collision efficiency. Agglomerate growth and the equilibrium agglomerate size were also monitored under different flocculation conditions. It was found that the size to which agglomerates grow depends on the shear rate and this can be expressed as a power law as df,95% ∝ g&d2;-0.258 . In addition, agglomerate breakage studies show that the agglomerate breakage occurs by floc rupture mechanism rather than by the surface erosion of primary particles

Trade-Offs between Fairness, Interpretability, and Privacy in Machine Learning

Algorithms have increasingly been deployed to make consequential decisions, and there have been many ethical questions raised about how these algorithms function. Three ethical considerations we look at in this work are fairness, interpretability, and privacy. These concerns have received a lot of attention in the research community recently, but have primarily been studied in isolation. In this work, we look at cases where we want to satisfy multiple of these properties simultaneously, and analyse how they interact. The underlying message of this work is that these requirements come at a cost, and it is necessary to make trade-offs between them. We have two theoretical results to demonstrate this. The first main result shows that there is a tension between the requirements of fairness and interpretability of classifiers. More specifically, we consider a formal framework to build simple classifiers as a means to attain interpretability, and show that each simple classifier is strictly improvable, in the sense that every simple classifier can be replaced by a more complex classifier that strictly improves both fairness and accuracy. The second main result considers the issue of compatibility between fairness and differential privacy of learning algorithms. In particular, we prove an impossibility theorem which shows that even in simple binary classification settings, one cannot design an accurate learning algorithm that is both ε-differentially private and fair (even approximately, according to any reasonable notion of fairness)

Legislative Compliance Assessment: Framework, Model and GDPR Instantiation

Legislative compliance assessment tools are commonly used by companies to help them to understand their legal obligations. One of the primary limitations of existing tools is that they tend to consider each regulation in isolation. In this paper, we propose a flexible and modular compliance assessment framework that can support multiple legislations. Additionally, we describe our extension of the Open Digital Rights Language (ODRL) so that it can be used not only to represent digital rights but also legislative obligations, and discuss how the proposed model is used to develop a flexible compliance system, where changes to the obligations are automatically reflected in the compliance assessment tool. Finally, we demonstrate the effectiveness of the proposed approach through the development of a General Data Protection Regulatory model and compliance assessment too

Barrier Properties of Graphene-Based Polymer Nanocomposites

Exfoliated graphite nanoplatelets (herein called graphene) are nanometer-thin platelets that are being extensively researched for their high stiffness, thermal conductivity, mass transfer barrier properties, and electrical conductivity towards developing a wide range of applications such as polymer nanocomposites (PNCs). These graphene-based PNCs (GPNCs) are expected to have better properties as compared to PNCs made using carbon nanotubes or nano-layered silicates. Graphene platelets are generally hydrophilic in nature hence difficult to disperse in polymers. In the work described here, surface treatment of graphene using 3-aminopropyltrimethoxysilane (APTMS), as shown by energy dispersive x-ray spectroscopy (EDS), results in more hydrophobic graphene which shows better dispersion. Scanning electron microscopy (SEM) and transmission electron microscopy (TEM) images illustrate the effect of surface treatment on the dispersion of graphene into polyvinyl acetate (PVAc). Barrier properties of treated and untreated graphene in PVAc were measured by sorption tests of GPNCs in water at various filler concentrations and different platelet diameters which show that the graphene platelets form an excellent barrier against diffusion

Stronger Generalization Guarantees for Robot Learning by Combining Generative Models and Real-World Data

We are motivated by the problem of learning policies for robotic systems with rich sensory inputs (e.g., vision) in a manner that allows us to guarantee generalization to environments unseen during training. We provide a framework for providing such generalization guarantees by leveraging a finite dataset of real-world environments in combination with a (potentially inaccurate) generative model of environments. The key idea behind our approach is to utilize the generative model in order to implicitly specify a prior over policies. This prior is updated using the real-world dataset of environments by minimizing an upper bound on the expected cost across novel environments derived via Probably Approximately Correct (PAC)-Bayes generalization theory. We demonstrate our approach on two simulated systems with nonlinear/hybrid dynamics and rich sensing modalities: (i) quadrotor navigation with an onboard vision sensor, and (ii) grasping objects using a depth sensor. Comparisons with prior work demonstrate the ability of our approach to obtain stronger generalization guarantees by utilizing generative models. We also present hardware experiments for validating our bounds for the grasping task

Incineration of Nanoclay Composites Leads to Byproducts with Reduced Cellular Reactivity

Addition of nanoclays into a polymer matrix leads to nanocomposites with enhanced properties to be used in plastics for food packaging applications. Because of the plastics’ high stored energy value, such nanocomposites make good candidates for disposal via municipal solid waste plants. However, upon disposal, increased concerns related to nanocomposites’ byproducts potential toxicity arise, especially considering that such byproducts could escape disposal filters to cause inhalation hazards. Herein, we investigated the effects that byproducts of a polymer polylactic acid-based nanocomposite containing a functionalized montmorillonite nanoclay (Cloisite 30B) could pose to human lung epithelial cells, used as a model for inhalation exposure. Analysis showed that the byproducts induced toxic responses, including reductions in cellular viability, changes in cellular morphology, and cytoskeletal alterations, however only at high doses of exposure. The degree of dispersion of nanoclays in the polymer matrixappeared to influence the material characteristics, degradation, and ultimately toxicity. With toxicity of the byproduct occurring at high doses, safety protocols should be considered, along with deleterious effects investigations to thus help aid in safer, yet still effective products and disposal strategies