Computational studies of magnetite Fe₃O₄ and related spinel-structured materials

This thesis presents the results of ab initio based simulation studies of magnetite (Fe₃O₄) and related FeM₂X₄ (thio)spinels with M = Cr, Mn, Fe, Co and Ni and X = O and S. Using density functional theory with long-range dispersion correction and on-site Coulomb interactions (DFT + U – D2), we have investigated a number of properties of these materials. Firstly, we present a study of the inversion degree and its relevance in the electronic structure and magnetic properties of the spin filter candidates FeM₂X₄, which are one of the key devices in spintronic applications. We also analyze the role played by the size of the ions and by the crystal field stabilization effects in determining the equilibrium inversion degree. Secondly, we present the calculations of the elastic constants and other macroscopic mechanical properties by applying elastic strains on the unit cell of Fe₃O₄, which is the main component in different types of catalysts used in myriad of industrial processes. Thirdly, we calculate the geometries and surface free energies of a number of Fe₃O₄ surfaces at different compositions, including the non-dipolar stoichiometric plane, and those with a deficiency or excess of oxygen atoms. We propose a morphology in thermodynamic equilibrium conditions for the nanocrystals of this compound. We also present the simulated scanning tunnelling microscopy images of the different terminations of the surfaces shown on the Fe₃O₄ morphology. Finally, we investigate the initial oxidation stages of the greigite (Fe₃S₄) (001) surface induced by water. Fe₃S₄ is a mineral widely identified in anoxic aquatic environments and certain soils, which can be oxidised by these environments producing and extremely acid solution of sulfur-rich wastewater called acid mine drainage (AMD). We propose a number of mechanisms involving one or two water molecules and one OH group to explain the replacement of one sulfur by one oxygen atom in this mineral. The findings presented in this thesis provides a theoretical insight into various bulk and surface properties of this group of compounds

Early Oxidation Processes on the Greigite Fe₃S⁴(001) Surface by Water: A Density Functional Theory Study

Greigite (Fe3S4), the sulfide counterpart of the spinel-structured oxide material magnetite (Fe3O4), is a mineral widely identified in anoxic aquatic environments and certain soils, which can be oxidized, thereby producing extremely acid solutions of sulfur-rich wastewaters, so-called acid mine drainage (AMD) or acid rock drainage (ARD). Here we report a computational study of the partial replacement of sulfur (forming H2S) by oxygen (from H2O) in the Fe3S4(001) surface, derived from density functional theory calculations with on-site Coulomb approach and long-range dispersion corrections (DFT+U–D2). We have proposed three pathways for the oxidation of the surface as a function of H2O coverage and pH. Different pathways give different intermediates, some of which are followed by a solid-state diffusion of the O atom. Low levels of H2O coverage, and especially basic conditions, seem to be essential, leading to the most favorable energetic landscape for the oxidation of the Fe3S4(001) surface. We have derived the thermodynamic and kinetic profile for each mechanism and plotted the concentration of H2S and protons in aqueous solution and thermodynamic equilibrium with the stoichiometric and partially oxidized Fe3S4(001) surface as a function of the temperature. Changes in the calculated vibrational frequencies of the adsorbed intermediates are used as a means to characterize their transformation. We have taken into account statistical entropies for H2S and H2O and other experimental parameters, showing that this mineral may well be among those responsible for the generation of AMD

Digital Image Quality Prediction System

[Abstract] “A picture is worth a thousand words.” Based on this well-known adage, we can say that images are important in our society, and increasingly so. Currently, the Internet is the main channel of socialization and marketing, where we seek to communicate in the most efficient way possible. People receive a large amount of information daily and that is where the need to attract attention with quality content and good presentation arises. Social networks, for example, are becoming more visual every day. Only on Facebook can you see that the success of a publication increases up to 180% if it is accompanied by an image. That is why it is not surprising that platforms such as Pinterest and Instagram have grown so much, and have positioned themselves thanks to their power to communicate with images. In a world where more and more relationships and transactions are made through computer applications, many decisions are made based on the quality, aesthetic value or impact of digital images. In the present work, a quality prediction system for digital images was developed, trained from the quality perception of a group of humans.Xunta de Galicia; ED431G 2019/01Xunta de Galicia; ED431D 201716Xunta de Galicia; ED431C 20184

Framework of fully integrated hybrid systems

The final publication is available at Springer via http://dx.doi.org/10.1007/s00521-011-0672-9A framework of fully integrated hybrid systems (HSs) is proposed for the development and management of HS which involve databases, advanced user interfaces, symbolic systems, and artificial neural networks. This framework provides a common input–output interface among those HS modules developed on the framework, with a completely two-directional flow control and a highly parallel processing. This integration framework facilitates the incorporation of heterogeneous modules, together with their subsequent management and updating

A computational study of the interaction of organic surfactants with goethite α-FeO(OH) surfaces

We have studied the adsorption of three organic molecules onto different surfaces of goethite α−FeO(OH) using atomistic simulation techniques. New interatomic potentials for the interaction between goethite and the organic molecules were developed. In the majority of cases the organic molecules were found capable of forming a coordinate bond via their carbonyl oxygen atom with a surface iron ion. In addition, weaker hydrogen-bonds were formed between the organic molecules and the surfaces. The largest adsorption energies were obtained for the modes of adsorption where the organic molecules bridged or spanned the periodic grooves or dips present on the goethite surfaces, thus forming several interactions between the molecule and the surface. Among all adsorbates studied, the hydroxamic acid molecule in the eclipsed conformation releases the largest adsorption energy when it interacts with goethite surfaces, followed by the staggered conformations of hydroxyethanal and methanoic acid molecules. The adsorption energies are in the range of −60.0 to −186.4 kJ∙mol−1. Due to the surface structure, as well as the flexibility and size of hydroxamic acid and hydroxyethanal, in most cases these adsorbate molecules lose their planarity with respect to the structure of the isolated molecules. We found that the replacement of pre-adsorbed water by the organic adsorbates is an exothermic process on all the goethite surfaces studied. The removal by sorption onto iron particles of humic and fulvic acids, the major substituents of natural organic matter (NOM) that pollutes aquifers and soils, is corroborated by our calculations of the adsorption of surfactants with the same functional groups to the surfaces of oxidised iron particles

Visual complexity modelling based on image features fusion of multiple kernels

[Abstract] Humans’ perception of visual complexity is often regarded as one of the key principles of aesthetic order, and is intimately related to the physiological, neurological and, possibly, psychological characteristics of the human mind. For these reasons, creating accurate computational models of visual complexity is a demanding task. Building upon on previous work in the field (Forsythe et al., 2011; Machado et al., 2015) we explore the use of Machine Learning techniques to create computational models of visual complexity. For that purpose, we use a dataset composed of 800 visual stimuli divided into five categories, describing each stimulus by 329 features based on edge detection, compression error and Zipf’s law. In an initial stage, a comparative analysis of representative state-of-the-art Machine Learning approaches is performed. Subsequently, we conduct an exhaustive outlier analysis. We analyze the impact of removing the extreme outliers, concluding that Feature Selection Multiple Kernel Learning obtains the best results, yielding an average correlation to humans’ perception of complexity of 0.71 with only twenty-two features. These results outperform the current state-of-the-art, showing the potential of this technique for regression.Xunta de Galicia; GRC2014/049Portuguese Foundation for Science and Technology; SBIRC; PTDC/EIA EIA/115667/2009Xunta de Galicia; Ref. XUGA-PGIDIT-10TIC105008-PRMinisterio de Ciencia y Tecnología; TIN2008-06562/TINMinisterio de Ecnomía y Competitividad; FJCI-2015-2607

A DFT+U study of the oxidation of cobalt nanoparticles: Implications for biomedical applications

Nanomaterials – magnetic nanoparticles in particular have been shown to have significant potential in cancer theranostics, where iron oxides are commonly the materials of choice. While biocompatibility presents an advantage, the low magnetisation is a barrier to their widespread use. As a result, highly magnetic cobalt nanoparticles are attracting increasing attention as a promising alternative. Precise control of the physiochemical properties of such magnetic systems used in biomedicine is crucial, however, it is difficult to test their behaviour in vivo. In the present work, density functional theory calculations with the Dudarev approach (DFT+U) have been used to model the adsorption of oxygen on low Miller index surfaces of the hexagonal phase of cobalt. In vivo conditions of temperature and oxygen partial pressure in the blood have been considered, and the effects of oxidation on the overall properties of cobalt nanoparticles are described. It is shown that oxygen adsorbs spontaneously on all surfaces with the formation of non-magnetic cobalt tetroxide, Co3O4, at body temperature, confirming that, despite their promising magnetic properties, bare cobalt nanoparticles would not be suitable for biomedical applications. Surface modifications could be designed to preserve their favourable characteristics for future utilisation

Africa-UK Partnership for the Computer-aided Development of Sustainable Catalysts

No Abstract

A DFT study of the structures, stabilities and redox behaviour of the major surfaces of magnetite Fe3O4

The renewed interest in magnetite (Fe3O4) as a major phase in different types of catalysts has led us to study the oxidation–reduction behaviour of its most prominent surfaces. We have employed computer modelling techniques based on the density functional theory to calculate the geometries and surface free energies of a number of surfaces at different compositions, including the stoichiometric plane, and those with a deficiency or excess of oxygen atoms. The most stable surfaces are the (001) and (111), leading to a cubic Fe3O4 crystal morphology with truncated corners under equilibrium conditions. The scanning tunnelling microscopy images of the different terminations of the (001) and (111) stoichiometric surfaces were calculated and compared with previous reports. Under reducing conditions, the creation of oxygen vacancies in the surface leads to the formation of reduced Fe species in the surface in the vicinity of the vacant oxygen. The (001) surface is slightly more prone to reduction than the (111), due to the higher stabilisation upon relaxation of the atoms around the oxygen vacancy, but molecular oxygen adsorbs preferentially at the (111) surface. In both oxidized surfaces, the oxygen atoms are located on bridge positions between two surface iron atoms, from which they attract electron density. The oxidised state is thermodynamically favourable with respect to the stoichiometric surfaces under ambient conditions, although not under the conditions when bulk Fe3O4 is thermodynamically stable with respect to Fe2O3. This finding is important in the interpretation of the catalytic properties of Fe3O4 due to the presence of oxidised species under experimental conditions

Comparison of Outlier-Tolerant Models for Measuring Visual Complexity

[Abstract] Providing the visual complexity of an image in terms of impact or aesthetic preference can be of great applicability in areas such as psychology or marketing. To this end, certain areas such as Computer Vision have focused on identifying features and computational models that allow for satisfactory results. This paper studies the application of recent ML models using input images evaluated by humans and characterized by features related to visual complexity. According to the experiments carried out, it was confirmed that one of these methods, Correlation by Genetic Search (CGS), based on the search for minimum sets of features that maximize the correlation of the model with respect to the input data, predicted human ratings of image visual complexity better than any other model referenced to date in terms of correlation, RMSE or minimum number of features required by the model. In addition, the variability of these terms were studied eliminating images considered as outliers in previous studies, observing the robustness of the method when selecting the most important variables to make the prediction.The Carlos III Health Institute from the Spanish National plan for Scientific and Technical Research and Innovation 2013-2016 and the European Regional Development Funds (FEDER) “A way to build Europe” support this work through the “Colaborative Project in Genomic Data Integration (CICLOGEN)” Pl17/01826. This work has also been supported by the General Directorate of Culture, Education and University Management of Xunta de Galicia (Ref. ED431G/01, ED431D 2017/16), the “Galician Network for Colorectal Cancer Research” (Ref. ED431D 2017/23) and Competitive Reference Groups (Ref. ED431C 2018/49). On the other hand, the unique installation BIOCAI (UNLC08-1E-002, UNLC13-13-3503) was funded by the Spanish Ministry of Economy and Competitiveness and the European Regional Development Funds (FEDER)Xunta de Galicia; ED431G/01Xunta de Galicia; ED431D 2017/16Xunta de Galicia; ED431D 2017/23Xunta de Galicia; ED431C 2018/4