Particles adsorbed at various non-aqueous liquid-liquid interfaces

Particles adsorbed at liquid interfaces are commonly used to stabilise water-oil Pickering emulsions and water-air foams. The fundamental understanding of the physics of particles adsorbed at water-air and water-oil interfaces is improving significantly due to novel techniques that enable the measurement of the contact angle of individual particles at a given interface. The case of non-aqueous interfaces and emulsions is less studied in the literature. Non-aqueous liquid-liquid interfaces in which water is replaced by other polar solvents have properties similar to those of water-oil interfaces. Nanocomposites of non-aqueous immiscible polymer blends containing inorganic particles at the interface are of great interest industrially and consequently more work has been devoted to them. By contrast, the behaviour of particles adsorbed at oil-oil interfaces in which both oils are immiscible and of low dielectric constant (ε < 3) is scarcely studied. Hydrophobic particles are required to stabilise these oil-oil emulsions due to their irreversible adsorption, high interfacial activity and elastic shell behaviour

On the Study of Fitness Landscapes and the Max-Cut Problem

The goal of this thesis is to study the complexity of NP-Hard problems, using the Max-Cut and the Max-k-Cut problems, and the study of fitness landscapes. The Max-Cut and Max-k-Cut problems are well studied NP-hard problems specially since the approximation algorithm of Goemans and Williamson (1995) which introduced the use of SDP to solve relaxed problems. In order to prove the existence of a performance guarantee, the rounding step from the SDP solution to a Max-Cut solution is simple and randomized. For the Max-k-Cut problem, there exist several approximation algorithms but many of them have been proved to be equivalent. Similarly as in Max-Cut, these approximation algorithms use a simple randomized rounding to be able to get a performance guarantee. Ignoring for now the performance guarantee, one could ask if there is a rounding process that takes into account the structure of the relaxed solution since it is the result of an optimization problem. In this thesis we answered this question positively by using clustering as a rounding method. In order to compare the performance of both algorithms, a series of experiments were performed using the so-called G-set benchmark for the Max-Cut problem and using the Random Graph Benchmark of Goemans1995 for the Max-k-Cut problem. With this new rounding, larger cut values are found both for the Max-Cut and the Max-k-Cut problems, and always above the value of the performance guarantee of the approximation algorithm. This suggests that taking into account the structure of the problem to design algorithms can lead to better results, possibly at the cost of a worse performance guarantee. An example for the vertex k-center problem can be seen in Garcia-Diaz et al. (2017), where a 3-approximation algorithm performs better than a 2-approximation algorithm despite having a worse performance guarantee. Landscapes over discrete configurations spaces are an important model in evolutionary and structural biology, as well as many other areas of science, from the physics of disordered systems to operations research. A landscape is a function defined on a very large discrete set V that carries an additional metric or at least topological structure into the real numbers R. We will consider landscapes defined on the vertex set of undirected graphs. Thus let G=G(V,E) be an undirected graph and f an arbitrary real-valued function taking values from V . We will refer to the triple (V,E,f) as a landscape over G. We say two configurations x,y in V are neutral if f(x)=f(y). We colloquially refer to a landscape as 'neutral'' if a substantial fraction of adjacent pairs of configurations are neutral. A flat landscape is one where f is constant. The opposite of flatness is ruggedness and it is defined as the number of local optima or by means of pair correlation functions. These two key features of a landscape, ruggedness and neutrality, appear to be two sides of the same coin. Ruggedness can be measured either by correlation properties, which are sensitive to monotonic transformation of the landscape, and by combinatorial properties such as the lengths of downhill paths and the number of local optima, which are invariant under monotonic transformations. The connection between the two views has remained largely unexplored and poorly understood. For this thesis, a survey on fitness landscapes is presented, together with the first steps in the direction to find this connection together with a relation between the covariance matrix of a random landscape model and its ruggedness

Tuning the bulk behavior and 2D interfacial self-assembly of microgels by Keggin-type polyoxometalate ionic specificity

Finding new ways to tune the behavior of thermoresponsive microgels in bulk and confined at 2D liquid interfaces is key to achieve a deeper understanding and control of these smart materials. We studied the interaction of positively charged pNIPAM microgels with the Keggin-type polyoxometalate $Na_{3}PW_{12}O_{40}$ (POM). In bulk, we observed charge inversions below and above the volume phase transition temperature (VPTT) at significantly low POM concentrations as $5\cdot10^{-5}$ M. In the presence of POM, the microgels exhibited a deswelling-swelling-deswelling behaviour below the VPTT, and a two-step further deswelling above the VPTT. When microgels were confined at 2D water/air interfaces, adding $10^{-5}$ M of POM below the VPTT was equivalent to heat above the VPTT and compress the monolayer from $5$ to 20\,\text{mN m^{-1}}. Above the VPTT, the diameter at the interface did not change while the portion immersed in the subphase further deswelled, in agreement with the behavior in bulk. Adding more POM did not change the diameter at the interface nor the height of the microgels, showing a saturation effect in 2D. The restructuring of the pNIPAM polymeric network by the POM was characterized by EDS mapping and XPS. The microgel monolayers with POM improved their resistance to plasma etching, which could be useful for soft colloidal lithography

Microgels Adsorbed at Liquid-Liquid Interfaces: A Joint Numerical and Experimental Study

Soft particles display highly versatile properties with respect to hard colloids, even more so at fluid-fluid interfaces. In particular, microgels, consisting of a cross-linked polymer network, are able to deform and flatten upon adsorption at the interface due to the balance between surface tension and internal elasticity. Despite the existence of experimental results, a detailed theoretical understanding of this phenomenon is still lacking due to the absence of appropriate microscopic models. In this work, we propose an advanced modelling of microgels at a flat water/oil interface. The model builds on a realistic description of the internal polymeric architecture and single-particle properties of the microgel and is able to reproduce its experimentally observed shape at the interface. Complementing molecular dynamics simulations with in-situ cryo-electron microscopy experiments and atomic force microscopy imaging after Langmuir-Blodgett deposition, we compare the morphology of the microgels for different values of the cross-linking ratios. Our model allows for a systematic microscopic investigation of soft particles at fluid interfaces, which is essential to develop predictive power for the use of microgels in a broad range of applications, including the stabilization of smart emulsions and the versatile patterning of surfaces

Decision Making Intelligent Agent on SOX Compliance over the Goods Receipt Processs

The objective of this work is to define a decision support system over SOX (Sarbanes-Oxley Act) compatibility  of the Goods Receipt Process based on Artificial Intelligence and Theory of Argumentation knowledge and techniques measuring at the same time the quality of how things were done on this specific process of the analyzed business case. SOX Law in effect nowadays is worldwide facto standard for financial and economical operations of private sector with the main objective to protect investors of private sector and promote the financial health of private companies. In this framework we have developed a decision support intelligent expert model to help SOX control bodies, companies and auditors to support their SOX compliance decisions based on well founded bases like Artificial Intelligence and Theory of Argumentation. The model here presented incorporates several key concepts like pre-existing expert knowledge base, a formalized and structure way to evaluate an existing business case focusing on the Goods Receipt Process, a semi automated fuzzy dynamic knowledge learning protocol and an structure method to evolve based on the facts of the business case and suggest an specific decision about the SOX compatibility of the specific business case. Keywords: Multiagent Systems (MAS), Expert Systems (ES), Business Intelligence (BI), Decision Support Systems (DSS), Sarbanes-Oxley Act (SOX), Argumentation, Artificial Intelligence

Decision Making Intelligent Agent on SOX Compliance over the Imports Process

The objective of this work is to define a decision support system over SOX (Sarbanes-Oxley Act) compatibility  of the Imports Process based on Artificial Intelligence and Theory of Argumentation knowledge and techniques measuring at the same time the quality of how things were done on this specific process of the analyzed business case. SOX Law in effect nowadays is worldwide facto standard for financial and economical operations of private sector with the main objective to protect investors of private sector and promote the financial health of private companies. In this framework we have developed a decision support intelligent expert model to help SOX control bodies, companies and auditors to support their SOX compliance decisions based on well founded bases like Artificial Intelligence and Theory of Argumentation. The model here presented incorporates several key concepts like pre-existing expert knowledge base, a formalized and structure way to evaluate an existing business case focusing on the Imports Process, a semi automated fuzzy dynamic knowledge learning protocol and an structure method to evolve based on the facts of the business case and suggest an specific decision about the SOX compatibility of the specific business case. Keywords: Multiagent Systems (MAS), Expert Systems (ES), Business Intelligence (BI), Decision Support Systems (DSS), Sarbanes-Oxley Act (SOX), Argumentation, Artificial Intelligence

Self-Templating Assembly of Soft Microparticles into Complex Tessellations

Self-assembled monolayers of microparticles encoding Archimedean and non-regular tessellations promise unprecedented structure-property relationships for a wide spectrum of applications in fields ranging from optoelectronics to surface technology. Yet, despite numerous computational studies predicting the emergence of exotic structures from simple interparticle interactions, the experimental realization of non-hexagonal patterns remains challenging. Not only kinetic limitations often hinder structural relaxation, but also programming the inteparticle interactions during assembly, and hence the target structure, remains an elusive task. Here, we demonstrate how a single type of soft polymeric microparticle (microgels) can be assembled into a wide array of complex structures as a result of simple pairwise interactions. We first let microgels self-assemble at a water-oil interface into a hexagonally packed monolayer, which we then compress to varying degrees and deposit onto a solid substrate. By repeating this process twice, we find that the resultant structure is not the mere stacking of two hexagonal patterns. The first monolayer retains its hexagonal structure and acts as a template into which the particles of the second monolayer rearrange to occupy interstitial positions. The frustration between the two lattices generates new symmetries. By simply varying the packing fraction of the two monolayers, we obtain not only low-coordination structures such as rectangular and honeycomb lattices, but also rhomboidal, hexagonal, and herringbone superlattices which display non-regular tessellations. Molecular dynamics simulations show that these structures are thermodynamically stable and develop from short-ranged repulsive interactions, making them easy to predict, and thus opening new avenues to the rational design of complex patterns

Clustering Improves the Goemans–Williamson Approximation for the Max-Cut Problem

MAX−CUT is one of the well-studied NP-hard combinatorial optimization problems. It can be formulated as an Integer Quadratic Programming problem and admits a simple relaxation obtained by replacing the integer “spin” variables xi by unitary vectors v⃗ i. The Goemans–Williamson rounding algorithm assigns the solution vectors of the relaxed quadratic program to a corresponding integer spin depending on the sign of the scalar product v⃗ i⋅r⃗ with a random vector r⃗ . Here, we investigate whether better graph cuts can be obtained by instead using a more sophisticated clustering algorithm. We answer this question affirmatively. Different initializations of k-means and k-medoids clustering produce better cuts for the graph instances of the most well known benchmark for MAX−CUT. In particular, we found a strong correlation of cluster quality and cut weights during the evolution of the clustering algorithms. Finally, since in general the maximal cut weight of a graph is not known beforehand, we derived instance-specific lower bounds for the approximation ratio, which give information of how close a solution is to the global optima for a particular instance. For the graphs in our benchmark, the instance specific lower bounds significantly exceed the Goemans–Williamson guarantee