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In this work, industrial waste hexafluorosilicic acid (H2SiF6 or FSA) has been proven to be a low-cost alternative to silicate esters for the synthesis of high-quality MCM-41 (high surface area, hi...

Iron oxides/oxyhydroxides, namely maghemite, iron oxide-silica composite, akaganeite, and ferrihydrite, are studied for As

International audience; The synthesis, structural, photophysical characterization and theoretical studies on homo/heteroleptic neutral 2D layered coordination polymers (CPs), obtained by combining the erbium(III) ion with chlorocyananilates (ClCNAn) and/or tetrafluoroterephthalates (F4BDC) linkers, are herein reported. The structure of the heteroleptic Er III-based CP, formulated as [Er2(ClCNAn)2(F4BDC)(DMSO)6]n (1) is also reported. 1 crystallizes in the triclinic P-1 space group and the structure consists of neutral 2D layers formed by Er III ions linked through the two linkers oriented in such a way that the neighboring 2D layers are eclipsed along the a axis, leading to parallelogram-like cavities. Photophysical measurements highlight the prominent role of chlorocyananilate linkers as optical antennas toward lanthanide ions, while wave-function theory analysis supports the experimental findings providing evidence for the effect of ligand substitution on the luminescence properties of homo/heteroleptic 2D CPs.

Arsenic pollution in ground and drinking water is a major problem worldwide due to the natural abundance of arsenic by dissolution from ground sediment or mining activities from anthropogenic activities. To overcome this issue, iron oxides as low-cost and non-toxic materials, have been widely studied as efficient adsorbents for arsenic removal, including when dispersed within porous silica supports. In this study, two head-to-head comparisons were developed to highlight the As(V)-adsorptive ability of meso- and macrostructured silica-based adsorbents. First, the role of the textural properties of a meso-(SBA15) and macrostructured (MOSF) silica support in affecting the structural-morphological features and the adsorption capacity of the active phase (Fe2O3) have been studied. Secondly, a comparison of the arsenic removal ability of inorganic (Fe2O3) and organic (amino groups) active phases was carried out on SBA15. Finally, since silica supports are commonly proposed for both environmental and biomedical applications as active phase carriers, we have investigated secondary silicon and iron pollution. The batch tests at different pH revealed better performance from both Fe2O3-composites at pH 3. The values of qm of 7.9 mg g−1 (53 mg gact−1) and 5.5 mg g−1 (37 mg gact−1) were obtained for SBA15 and MOSF, respectively (gact stands for mass of the active phase). The results suggest that mesostructured materials are more suitable for dispersing active phases as adsorbents for water treatment, due to the obtainment of very small Fe2O3 NPs (about 5 nm). Besides studying the influence of the pore size of SBA15 and MOSF on the adsorption process, the impact of the functionalization was analyzed on SBA15 as the most promising sample for As(V)-removal. The amino-functionalized SBA15 adsorbent (3-aminopropyltriethoxysilane, APTES) exhibited a qm of 12.4 mg g−1 and faster kinetics. Furthermore, issues associated with the release of iron and silicon during the sorption process, causing secondary pollution, were evaluated and critically discussed.

Nanostructured spinel ferrites with formula M2+Fe2O4 (where M2+ ═ Fe, Co, Mn, Ni, Zn, etc.) represent a class of magnetic materials widely employed in different research fields, due to the possibility of finely tuning the magnetic properties by changing the chemical composition, size, shape, capping agents, etc. Herein, a review of the most common chemical synthesis in liquid media, distinguishing among aqueous and non-aqueous routes, is presented. The experimental procedure together with the mechanism, advantages and disadvantages, and examples are illustrated for each synthetic strategy.

An oleate-based solvothermal approach has been employed to produce pure CoFe₂O₄ and MnFe₂O₄ and mixed Co-Mn ferrites having manganese content in the range 0.13-0.65 and crystallite size of about 8-9 nm. The structural and magnetic properties, studied by powder X-ray diffraction and room temperature 57Fe Mossbauer spectroscopy, have allowed to ascertain the formation of a unique spinel phase in which cobalt and manganese are present and to get insights on the cation distribution and the correlated magnetic properties.

A Raman study on Zinc-substituted Cobalt ferrites, with different Zn(II) contents in each sample of formula: CoFe₂O₄ (1), Zn0.30Co0.70Fe2.00O₄ (2), Zn0.46Co0.54Fe2.02O₄ (3), Zn0.53Co0.47Fe2.02O₄ (4) is reported. These samples show the same crystallite size (∼6 nm), particle size (∼7 nm) and particle size distribution (∼20%) and they have been synthesized through heating up surfactant-assisted thermal decomposition of metalorganic precursors. The effect of Zn(II) substitution in the cationic distribution is investigated by using the known metal-oxygen vibrational modes in tetrahedral and octahedral sites. The presence of Zn(II) metal ion is determined through the band at 150 cm-1 (T2g(1) phonon mode), which is not present in the pure Co-ferrite, a blue-shift of the Eg vibrational mode depending on Zn(II)/Co(II) cationic distribution and a shoulder at ∼250 cm-1, which appears when zinc enters in the structure, and a broadening and a red-shift in the A1g phonon mode is observed in Raman spectra of 2-4 samples. Interestingly the latter represents a potential key probe to monitor the Zn(II) presence in Zn-substituted Co-ferrites.

Achieving metal-organic frameworks (MOFs) in the form of nanoparticles (NanoMOFs) represents a recent challenge due to the possibility to combine the intrinsic porosity of these materials with the nanometric dimension, a fundamental requirement for strategic biomedical applications. In this outlook we envision the current/future opportunities of the NanoMOFs in the field of biomedicine, with particular emphasis on (i) biocompatible MOFs composition; (ii) MOFs miniaturization and (iii) nanoMOFs applications.

In this work we study stationary linear time-series models, and construct and analyse “score-matching” estimators based on the Hyvarinen scoring rule. We consider two scenarios: a single series of increasing length, and an increasing number of independent series of fixed length. In the latter case there are two variants, one based on the full data, and another based on a sufficient statistic. We study the empirical performance of these estimators in three special cases, autoregressive (AR), moving average (MA) and fractionally differenced white noise (ARFIMA) models, and make comparisons with full and pairwise likelihood estimators. The results are somewhat model-dependent, with the new estimators doing well for MA and ARFIMA models, but less so for AR models.

Bayesian regression models have been widely studied and adopted in the statistical literature. Many studies consider the development of reliable priors to select the relevant variables and derive accurate posterior predictive distributions. Moreover in the context of small high-dimensional data, where the number of observations is very small with respect to the number of predictors, sparsity is assumed and many parameters can be set to values close to zero without affecting the fit of the model. Aim of this work is to develop a comparative analysis to empirically evaluate the performances of several Bayesian regression approaches in these contexts. In this study we assume that the predictors can be expressed only as binary variables coding the presence or the absence of a particular characteristic of the system. This binary structure is often present in many real studies, in particular in laboratory experimentation and in very high-dimension genome wide association studies.

One of the main problems that the drug discovery research field confronts is to identify small molecules, modulators of protein function, which are likely to be therapeutically useful. Common practices rely on the screening of vast libraries of small molecules (often 1-2 million molecules) in order to identify a molecule, known as a lead molecule, which specifically inhibits or activates the protein function. To search for the lead molecule, we investigate the molecular structure, which generally consists of an extremely large number of fragments. Presence or absence of particular fragments, or groups of fragments, can strongly affect molecular properties. We study the relationship between molecular properties and its fragment composition by building a regression model, in which predictors, represented by binary variables indicating the presence or absence of fragments, are grouped in subsets and a bi-level penalization term is introduced for the high dimensionality of the problem. We evaluate the performance of this model in two simulation studies, comparing different penalization terms and different clustering techniques to derive the best predictor subsets structure. Both studies are characterized by small sets of data relative to the number of predictors under consideration. From the results of these simulation studies, we show that our approach can generate models able to identify key features and provide accurate predictions. The good performance of these models is then exhibited with real data about the MMP-12 enzyme.

The effect of the annealing temperature Tann on the magnetic properties of cobalt ferrite nanoparticles embedded in an amorphous silica matrix (CoFe2O4/SiO2), synthesized by a sol-gel auto-combustion method, was investigated by magnetization and AC susceptibility measurements. For samples with 15% w/w nanoparticle concentration, the particle size increases from ~2.5 to ~7 nm, increasing Tann from 700 to 900 &deg, C. The effective magnetic anisotropy constant (Keff) increases with decreasing Tann, due to the increase in the surface contribution. For a 5% w/w sample annealed at 900 &deg, C, Keff is much larger (1.7 &times, 106 J/m3) than that of the 15% w/w sample (7.5 &times, 105 J/m3) annealed at 700 &deg, C and showing comparable particle size. This indicates that the effect of the annealing temperature on the anisotropy is not only the control of the particle size but also on the core structure (i.e., cation distribution between the two spinel sublattices and degree of spin canting), strongly affecting the magnetocrystalline anisotropy. The results provide evidence that the magnetic anisotropy comes from a complex balance between core and surface contributions that can be controlled by thermal treatments.

Artificial nano-heterostructures (NHs) with controlled morphology, obtained by combining two or more components in several possible architectures, make them suitable for a wide range of applications. Here, we propose an oleate-based solvothermal approach to design silver-spinel ferrite flower-like NHs. Small oleate-coated silver nanoparticles were used as seeds for the growth of magnetic spinel ferrite (cobalt ferrite and spinel iron oxide) nanodomains on their surface. With the aim of producing homogeneous flower-like heterostructures, a careful study of the effect of the concentration of precursors, the reaction temperature, the presence of water, and the chemical nature of the spinel ferrite was carried out. The magnetic and optical properties of the NHs were also investigated. A heterogeneous growth of the spinel ferrite phase on the silver nanoparticles, through a possible defect-assisted mechanism, was suggested in the light of the high concentration of stacking faults (intrinsic and twins) in the silver seeds, revealed by Rietveld refinement of powder X-ray diffraction patterns and High-Resolution electron microscopy.

Building clusters for pattern recognition and analysis of geographical areas can be a useful way to provide relevant information for economic and social decisions. In this paper, we introduce a novel spatial clustering technique, called Bootstrap ClustGeo (BCG), which is a hierarchical approach, based on bootstrap techniques with spatial constraints. We evaluate the performance of the proposed approach BCG through some real case studies and simulations studies with different complexity, by computing Clustering Validation Measures (CVM) and then we compare the approach with the recently proposed ClustGeo (CG). These analyses exhibit the accuracy of BCG, also with respect to CG, in the presented applications, and highlight the great potentiality of this new clustering technique to provide meaningful information for spatial analysis.

International audience; Nanosheets of two mixed linker (anilate/carboxylate)/YbIII-based two-dimensional (2D) layered coordination polymers (CPs) are herein reported. Bulky sized CPs, formulated as [Yb4(ClCNAn)5(DOBDC)1(DMSO)10]n·(DMSO)2 (1) and [Yb2(ClCNAn)2(F4BDC)(DMSO)6]n (2), are formed by two-dimensional neutral polymeric networks based on YbIII ions, heterosubstituted ClCNAn2– anilate, and dicarboxylate linkers (DOBDC2– in 1; F4BDC2– in 2): in 1, neighbor layers are eclipsed and form six-membered rings showing either hexagonal cavities, formed by ClCNAn2– and YbIII ions or rectangular cavities formed by ClCNAn2–, DOBDC2–, and YbIII while distorted square-like cavities formed by ClCNAn2–, F4BDC2–, and YbIII are obtained in 2. The 1 and 2 nanosheets, that is, 1-NS and 2-NS, are produced by exfoliation of bulk CPs by the well-known top-down approach and characterized by atomic force microscopy and high resolution transmission electron microscopy. The 1-NS and 2-NS show thickness in the range of 1–5 nm, whereas the lateral dimensions are in the micrometer scale and the presence of well-defined lattice fringes, key evidence of their robustness. Remarkably the powder X-ray diffraction (PXRD) patterns highlight that the crystallinity is retained at the nanoscale level. Nanosheets photophysics are investigated by an innovative Multiprobe Approach where lifetime, photoluminescence (PL) and integrated PL are simultaneously measured in order to study how these parameters can be affected by the presence of the different ligands. These advanced photophysical studies pave the way to challenging luminescent sensing applications and to contribute to the ongoing research on fabricating robust and crystalline hybrid (organic/inorganic) lanthanide sheetlike 2D nanomaterials.

In this work, the effect of the M41S support pore structure (hexagonal or cubic) and of the wall thickness of the silica mesochannels has been evaluated aimed at achieving more and more efficient and regenerable iron oxide-based sorbents for H2S removal at midtemperature. With this purpose, we set up a simple Pluronic-free synthetic strategy capable of producing silica supports with hexagonal (MCM-41) or cubic (MCM-48) pore structure with different wall thicknesses that have been used to fabricate the corresponding sorbents made up of iron oxide nanoparticles homogeneously dispersed into the mesochannels. The combined use of 57Fe-Mossbauer Spectroscopy and DC magnetometry has allowed for ascertaining the presence of maghemite in the form of ultrasmall nanoparticles in both composites and gives new insights on the influence of the different silica matrices on the active phase features. The performances of the sorbents have been evaluated at midtemperature (300 °C) through three repeated sulfidation and reg...

During the 2nd millennium BC anthropomorphic menhirs belonging to a 3rd millennium BC sanctuary were reused as building material in the Arasseda Nuraghe (Sardinia, Italy). To analyse the Arasseda menhirs and the local Monte Ironi geological samples (presenting similar visual features), chemical (pXRF, ICP-OES, ICP-MS), mineralogical-chemical (PXRD) and physical (Mohs hardness) measurements were performed. Through the experimental data, the menhirs source provenance and the technological properties (workability, durability) of the raw material chosen for sculptural purposes during Copper Age were investigated. To the authors’ knowledge this is the first archaeometric study on the Arasseda menhirs (the third on Sardinian menhirs) and one between the few recently developed on European megaliths.

An easy, low-cost, repeatable seed-mediated growth approach in solvothermal condition has been proposed to synthesize bimagnetic spinel ferrite core-shell heterostructures in the 10-20 nm particle size range. Cobalt ferrite and manganese ferrite nanoparticles (CoFe2O4 and MnFe2O4) have been coated with isostructural spinel ferrites like maghemite/magnetite, MnFe2O4, and CoFe2O4 with similar cell parameters to create different heterostructures. The conventional study of the structure, morphology, and composition has been combined with advanced techniques in order to achieve details on the interface at the nanoscale level. Clear evidence of the heterostructure formation have been obtained (i) indirectly by comparing the 57Fe Mossbauer spectra of the core-shell samples and an ad hoc mechanical mixture and (ii) directly by mapping the nanoparticles' chemical composition by electron energy loss spectroscopy (EELS) and energy-dispersive X-ray spectroscopy (EDX) in the scanning transmission electron microscopy mode (STEM). In addition, chemical-sensitive electron tomography in STEM-EDX mode has been applied in order to obtain detailed 3D images with a sub-nanometer spatial resolution.

MCM-41 is proposed to build mesostructured Fe2O3-based sorbents as an alternative to other silica or alumina supports for mid-temperature H2S removal. MCM-41 was synthesized as micrometric (MCM41_M) and nanometric (MCM41_N) particles and impregnated through an efficient two-solvent (hexane–water) procedure to obtain the corresponding γ-Fe2O3@MCM-41 composites. The active phase is homogeneously dispersed within the 2 nm channels in the form of ultrasmall maghemite nanoparticles assuring a high active phase reactivity. The final micrometric (Fe_MCM41_M) and nanometric (Fe_MCM41_N) composites were tested as sorbents for hydrogen sulphide removal at 300 °C and the results were compared with a reference sorbent (commercial unsupported ZnO) and an analogous silica-based sorbent (Fe_SBA15). MCM-41 based sorbents, having the highest surface areas, showed superior performances that were retained after the first sulphidation cycle. Specifically, the micrometric sorbent (Fe_MCM41_M) showed a higher SRC value than the nanometric one (Fe_MCM41_N), due to the low stability of the nanosized particles over time caused by their high reactivity. Furthermore, the low regeneration temperature (300–350 °C), besides the high removal capacity, renders MCM41-based systems an alternative class of regenerable sorbents for thermally efficient cleaning up processes in Integrated Gasification Combined Cycles (IGCC) systems.

Obsidian is a natural volcanic glass in which nanocrystalline and microcrystalline phases can coexist with the glassy one. In this paper, magnetic properties of Monte Arci obsidians are investigated by an experimental approach commonly applied to synthetic nanostructured materials and rarely to natural ones, and correlated with the mineralogical composition and microstructure. Among the different crystalline phases, the iron-containing components are found to be responsible for a great variety of magnetic behaviors, including paramagnetism, antiferromagnetism, ferromagnetism, and superparamagnetism. The combined use of powder X-ray diffraction (PXRD), Fe-57 Mossbauer spectroscopy, DC magnetometry, and transmission electron microscopy (TEM/HRTEM) provides new insights in the Monte Arci obsidian: (i) the presence of magnetite nanoparticles spread into the glassy matrix; (ii) the presence of an antiferromagnetic phase responsible for a discontinuity at about 45 K; (iii) exchange bias phenomena, for the first time revealed in obsidians, due to the coupling between the nanostructured ferrimagnetic phase and the antiferromagnetic one; (iv) Goldanskii-Karyagin effect (GKE) associated with biotite.

The versatility of a promising and repeatable oleate-based solvothermal approach has been explored through the synthesis of MnFe₂O₄ and

Currently many research problems are addressed by analysing datasets characterized by a huge number of variables, with a relatively limited number of observations, especially when data are generated by experimentation. Most of the classical statistical procedures for regression analysis are often inadequate to deal with such datasets as they have been developed assuming that the number of observations is larger than the number of the variables. In this work, we propose a new penalization procedure for variable selection in regression models based on Bootstrap group Penalties (BgP). This new family of penalization methods extends the bootstrap version of the LASSO approach by taking into account the grouping structure that may be present or introduced in the model. We develop a simulation study to compare the performance of this new approach with respect several existing group penalization methods in terms of both prediction accuracy and variable selection quality. The results achieved in this study show that the new procedure outperforms the other penalties procedures considered.

Standard Bayesian analyses can be difficult to perform when the full likelihood, and consequently the full posterior distribution, is too complex and difficult to specify or if robustness with respect to data or to model misspecifications is required. In these situations, we suggest to resort to a posterior distribution for the parameter of interest based on proper scoring rules. Scoring rules are loss functions designed to measure the quality of a probability distribution for a random variable, given its observed value. Important examples are the Tsallis score and the Hyv\"arinen score, which allow us to deal with model misspecifications or with complex models. Also the full and the composite likelihoods are both special instances of scoring rules. The aim of this paper is twofold. Firstly, we discuss the use of scoring rules in the Bayes formula in order to compute a posterior distribution, named SR-posterior distribution, and we derive its asymptotic normality. Secondly, we propose a procedure for building default priors for the unknown parameter of interest that can be used to update the information provided by the scoring rule in the SR-posterior distribution. In particular, a reference prior is obtained by maximizing the average $\alpha-$divergence from the SR-posterior distribution. For $0 \leq |\alpha, Comment: 29 pages and 9 figures

In this paper we consider frequentist and Bayesian likelihood-based small-sample procedures to compute confidence intervals for Gini’s gamma index in the bivariate Gaussian copula model. We furthermore discuss how the method straightforwardly extends to any measure of concordance which is available in closed form, and to any type of copula for which the considered measure of concordance has a closed-form expression.