Nanostructured spinel cobalt ferrites: Fe and Co chemical state, cation distribution and size effects by X-ray photoelectron spectroscopy

Nanostructured spinel cobalt ferrite samples having crystallite size ranging between 5.6 and 14.1 nm were characterized by X-ray photoelectron spectroscopy and X-ray induced Auger electron spectroscopy in order to determine the chemical state of the elements, the iron/cobalt ratio and the cation distribution within tetrahedral and octahedral sites. The presence of size-dependent trends in the binding energy of the main photoelectron peaks and in the kinetic energy of the X-ray induced O KLL signal was also investigated. The results showed that iron is present as FeIII and cobalt is present as CoII. The iron/cobalt ratio determined by XPS ranges between 1.8 and 1.9 and it is in very good agreement, within experimental uncertainty, with the expected 2 : 1 ratio. The percentage of Fe in octahedral sites ranges between 62% and 64% for all samples. The kinetic energy of the O KLL signals increases with crystallite size. These results are explained in terms of changes in the ionicity of the metal–oxygen bonds. The results of this investigation highlight how the XPS technique represents a powerful tool to investigate the composition, the chemical state and inversion degree of cobalt spinel ferrites, contributing to the comprehension of their properties

Mesostructured γ-Al2O3-Based Bifunctional Catalysts for Direct Synthesis of Dimethyl Ether from CO2

In this work, we propose two bifunctional nanocomposite catalysts based on acidic mesostructured γ-Al2O3 and a Cu/ZnO/ZrO2 redox phase. γ-Al2O3 was synthesized by an Evaporation-Induced Self-Assembly (EISA) method using two different templating agents (block copolymers Pluronic P123 and F127) and subsequently functionalized with the redox phase using an impregnation method modified with a self-combustion reaction. These nanocomposite catalysts and their corresponding mesostructured supports were characterized in terms of structural, textural, and morphological features as well as their acidic properties. The bifunctional catalysts were tested for the CO2-to-DME process, and their performances were compared with a physical mixture consisting of the most promising support as a dehydration catalyst together with the most common Cu-based commercial redox catalyst (CZA). The results highlight that the most appropriate Pluronic for the synthesis of γ-Al2O3 is P123; the use of this templating agent allows us to obtain a mesostructure with a smaller pore size and a higher number of acid sites. Furthermore, the corresponding composite catalyst shows a better dispersion of the redox phase and, consequently, a higher CO2 conversion. However, the incorporation of the redox phase into the porous structure of the acidic support (chemical mixing), favoring an intimate contact between the two phases, has detrimental effects on the dehydration performances due to the coverage of the acid sites with the redox nanophase. On the other hand, the strategy involving the physical mixing of the two phases, distinctly preserving the two catalytic functions, assures better performances.MIUR—National Program PON Ricerca e InnovazioneUniversity of CagliariFondazione di Sardegna (FdS)Regional Government of Sardinia ASSET projectPeer Reviewe

On the design of mesostructured acidic catalysts for the one-pot dimethyl ether production from CO2

Dimethyl ether (DME) production from hydrogenation of CO2 based on two-function (redox and acidic) catalysts is receiving increasing attention due to the high demand for alternative and green fuels. In this work, we propose different mesostructured acidic metal oxides as methanol dehydration catalysts to be used as physical mixtures in combination with a commercial Cu-based redox catalyst (CZA) for the CO2-to-DME one-pot production. Al-MCM41, TiO2 and TiO2-ZrO2 mixed oxides, obtained through Sol-Gel methods, either in a conventional or Evaporation-Induced Self-Assembly approach were selected as mesostructured acidic systems and compared with a commercial zeolite (ferrierite). The regular mesoporous structure should render the active sites of the acidic catalyst easily accessible for CO2 and H2 and allow a homogeneous dispersion of the redox phase inside the mesopores in view of a possible development of bifunctional catalysts (redox + acidic). With the aim of understanding how the textural and acidic properties can be correlated with the performances and eventually design efficient dehydration catalysts, a careful study on the acidic sites was performed by both adsorption microcalorimetry with ammonia and FTIR-monitored adsorption of pyridine. The results of the performances highlighted a higher activity toward methanol dehydration for catalysts featured by Bronsted sites (zeolite and Al-MCM-41); as for catalysts with Lewis sites only (TiO2, Ti0.77Zr0.23O2) better performances were shown in case of systems presenting sites of moderate strength (Ti0.77Zr0.23O2). In the light of the above, Al-MCM-41 and TiO2ZrO2 demonstrated to be the most promising mesostructured dehydration catalysts in terms of selectivity to DME

Exploring the Role of Killer Cell Immunoglobulin-Like Receptors and Their HLA Class I Ligands in Autoimmune Hepatitis

Background Natural killer cells are involved in the complex mechanisms underlying autoimmune diseases but few studies have investigated their role in autoimmune hepatitis. Killer immunoglobulin-like receptors are key regulators of natural killer cell-mediated immune responses. Methods and Findings KIR gene frequencies, KIR haplotypes, KIR ligands and combinations of KIRs and their HLA Class I ligands were investigated in 114 patients diagnosed with type 1 autoimmune hepatitis and compared with a group of 221 healthy controls. HLA Class I and Class II antigen frequencies were compared to those of 551 healthy unrelated families representative of the Sardinian population. In our cohort, type 1 autoimmune hepatitis was strongly associated with the HLA-B18, Cw5, DR3 haplotype. The KIR2DS1 activating KIR gene and the high affinity HLA-C2 ligands were significantly higher in patients compared to controls. Patients also had a reduced frequency of HLA-Bw4 ligands for KIR3DL1 and HLA-C1 ligands for KIR2DL3. Age at onset was significantly associated with the KIR2DS1 activating gene but not with HLA-C1 or HLA-C2 ligand groups. Conclusions The activating KIR gene KIR2DS1 resulted to have an important predictive potential for early onset of type 1 autoimmune hepatitis. Additionally, the low frequency of the KIR-ligand combinations KIR3DL1/HLA-Bw4 and KIR2DL3/HLA-C1 coupled to the high frequency of the HLA-C2 high affinity ligands for KIR2DS1 could contribute to unwanted NK cell autoreactivity in AIH-1

Pair-sharing analysis of object-oriented programs

Abstract Pair-sharing analysis of object-oriented programs determines those pairs of program variables bound at run-time to overlapping data structures. This information is useful for program parallelisation and analysis. We follow a similar construction for logic programming and formalise the property, or abstract domain, Sh of pair-sharing. We prove that Sh induces a Galois insertion w.r.t. the concrete domain of program states. We define a compositional abstract semantics for the static analysis over Sh, and prove it correct.

Hard-Soft Core-Shell Architecture Formation from Cubic Cobalt Ferrite Nanoparticles.

Cubic bi-magnetic hard-soft core-shell nanoarchitectures were prepared starting from cobalt ferrite nanoparticles, prevalently with cubic shape, as seeds to grow a manganese ferrite shell. The combined use of direct (nanoscale chemical mapping via STEM-EDX) and indirect (DC magnetometry) tools was adopted to verify the formation of the heterostructures at the nanoscale and bulk level, respectively. The results showed the obtainment of core-shell NPs (CoFe2O4@MnFe2O4) with a thin shell (heterogenous nucleation). In addition, manganese ferrite was found to homogeneously nucleate to form a secondary nanoparticle population (homogenous nucleation). This study shed light on the competitive formation mechanism of homogenous and heterogenous nucleation, suggesting the existence of a critical size, beyond which, phase separation occurs and seeds are no longer available in the reaction medium for heterogenous nucleation. These findings may allow one to tailor the synthesis process in order to achieve better control of the materials' features affecting the magnetic behaviour, and consequently, the performances as heat mediators or components for data storage devices

As^{(III, V)} Uptake from Nanostructured Iron Oxides and Oxyhydroxides: The Complex Interplay between Sorbent Surface Chemistry and Arsenic Equilibria

Iron oxides/oxyhydroxides, namely maghemite, iron oxide-silica composite, akaganeite, and ferrihydrite, are studied for AsV and AsIII removal from water in the pH range 2–8. All sorbents were characterized for their structural, morphological, textural, and surface charge properties. The same experimental conditions for the batch tests permitted a direct comparison among the sorbents, particularly between the oxyhydroxides, known to be among the most promising As-removers but hardly compared in the literature. The tests revealed akaganeite to perform better in the whole pH range for AsV (max 89 mg g−1 at pH0 3) but to be also efficient toward AsIII (max 91 mg g−1 at pH0 3–8), for which the best sorbent was ferrihydrite (max 144 mg g−1 at pH0 8). Moreover, the study of the sorbents’ surface chemistry under contact with arsenic and arsenic-free solutions allowed the understanding of its role in the arsenic uptake through electrophoretic light scattering and pH measurements. Indeed, the sorbent’s ability to modify the starting pH was a crucial step in determining the removal of performances. The AsV initial concentration, contact time, ionic strength, and presence of competitors were also studied for akaganeite, the most promising remover, at pH0 3 and 8 to deepen the uptake mechanism

Checking Array Bounds by Abstract Interpretation and Symbolic Expressions

Array access out of bounds is a typical programming error. From the \u201970s, static analysis has been used to identify where such errors actually occur at runtime, through abstract interpretation into linear constraints. However, feasibility and scalability to modern object-oriented code has not been established yet. This article builds on previous work on linear constraints and shows that the result does not scale, when polyhedra implement the linear constraints, while the more abstract zones scale to the analysis of medium-size applications. Moreover, this article formalises the inclusion of symbolic expressions in the constraints and shows that this improves its precision. Expressions are automatically selected on-demand. The resulting analysis applies to code with dynamic memory allocation and arrays held in expressions. It is sound, also in the presence of arbitrary side-effects. It is fully defined in the abstract interpretation framework and does not use any code instrumentation. Its proof of correctness, its implementation inside the commercial Julia analyzer and experiments on third-party code complete the work