Potentially toxic elements speciation in bottom ashes from a municipal solid waste incinerator: A combined SEM-EDS, µ-XRF and µ-XANES study

Bottom Ashes from Municipal Solid Waste Incinerators and Waste to Energy plants represent an interesting source of secondary raw materials for many applications, like urban mining and inclusion in concrete, and road pavement. However, Bottom Ashes may contain potentially toxic elements, whose actual toxicity depends essentially on their oxidation state and mineralogical environment. For this reason, a representative sample of bottom ashes from Parma Waste to Energy plant has been selected to investigate the chemical speciation of Cr, Ni, Pb, Co, Zn and Cu by means of complementary techniques: Scanning Electron Microscopy with Energy Dispersive X-Ray Spectroscopy (SEM-EDS), micro X-Ray Fluorescence (µ-XRF) mapping and X-Ray Absorption Near Edge Structure (XANES) measurements by synchrotron radiation. This multi-technique approach allowed to obtain a general image of the mineralogical and chemical environment in which these elements are found. SEM-EDS analyses show the presence of Zn and Pb both in minerals and in glass matrix. Cr has been detected in the form of oxide and in spinel structure (chromite) whereas Co and Cu are found as alloy or metal inclusions. µ-XRF mapping reveals that Cu, Ni and Cr are generally associated to Na, K and Si suggesting their presence in glass matrix. XANES investigations exhibit that Cu has a variable oxidation state that suggesting its presence in the form of oxide, hydroxide, acetate and metal. Zn is mainly found as +II and in a number of different phases (including Zn-carbonates, in agreement with SEM-EDS data). Cr has been found only as +III, with XANES features resembling those of chromite, whereas as +VI was never identified. Ni and Co were found either as metal form and oxides. Pb spectra show a good match with oxides

Spritz: a server for the prediction of intrinsically disordered regions in protein sequences using kernel machines

Intrinsically disordered proteins have long stretches of their polypeptide chain, which do not adopt a single native structure composed of stable secondary and tertiary structure in the absence of binding partners. The prediction of intrinsically disordered regions in proteins from sequence is increasingly becoming of interest, as the presence of many such regions in the complete genome sequences are discovered and important functional roles are associated with them. We have developed a machine learning approach based on two support vector machines (SVM) to discriminate disordered regions from sequence. The SVM are trained and benchmarked on two sets, representing long and short disordered regions. A preliminary version of Spritz was shown to perform consistently well at the recent biannual CASP-6 experiment [Critical Assessment of Techniques for Protein Structure Prediction (CASP), 2004]. The fully developed Spritz method is freely available as a web server at and

Large scale synthesis of copper nickel alloy nanoparticles with reduced compressibility using arc thermal plasma process

Among the various methods employed in the synthesis of nanostructures, those involving high operating temperature and sharp thermal gradients often lead to the establishment of new exotic properties. Herein, we report on the formation of Cu-Ni metallic alloy nanoparticles with greatly enhanced stiffness achieved through direct-current transferred arc-thermal plasma assisted vapour-phase condensation. High pressure synchrotron X-ray powder diffraction (XRPD) at ambient temperature as well as XRPD in the temperature range 180 to 920 K, show that the thermal arc-plasma route resulted in alloy nanoparticles with much enhanced bulk modulus compared to their bulk counterparts. Such a behaviour may find an explanation in the sudden quenching assisted by the retention of a large amount of local strain due to alloying, combined with the perfect miscibility of the elemental components during the thermal plasma synthesis process

The Missing Piece: The Structure of the Ti3C2TxMXene and Its Behavior as Negative Electrode in Sodium Ion Batteries

The most common MXene composition Ti3C2Tx (T = F, O) shows outstanding stability as anode for sodium ion batteries (100% of capacity retention after 530 cycles with charge efficiency >99.7%). However, the reversibility of the intercalation/deintercalation process is strongly affected by the synthesis parameters determining, in turn, significant differences in the material structure. This study proposes a new approach to identify the crystal features influencing the performances, using a structural model built with a multitechnique approach that allows exploring the short-range order of the lamella. The model is then used to determine the long-range order by inserting defective elements into the structure. With this strategy it is possible to fit the MXene diffraction patterns, obtain the structural parameters including the stoichiometric composition of the terminations (neutron data), and quantify the structural disorder which can be used to discriminate the phases with the best electrochemical properties

Hexavalent chromium release over time from a pyrolyzed Cr-bearing tannery sludge

Pyrolysis in an inert atmosphere is a widely applied route to convert tannery wastes into reusable materials. In the present study, the Cr(III) conversion into the toxic hexavalent form in the pyrolyzed tannery waste referred to as KEU was investigated. Ageing experiments and leaching tests demonstrated that the Cr(III)–Cr(VI) inter-conversion occurs in the presence of air at ambient temperature, enhanced by wet environmental conditions. Microstructural analysis revealed that the Cr-primary mineral assemblage formed during pyrolysis (Cr-bearing srebrodolskite and Cr-magnetite spinel) destabilized upon spray water cooling in the last stage of the process. In the evolution from the higher to the lower temperature mineralogy, Cr is incorporated into newly formed CrOOH flakes which likely react in air forming extractable Cr(VI) species. This property transforms KEU from an inert waste to a hazardous material when exposed to ordinary ambient conditions

Accurate prediction of protein secondary structure and solvent accessibility by consensus combiners of sequence and structure information

Background : Structural properties of proteins such as secondary structure and solvent accessibility contribute to three-dimensional structure prediction, not only in the ab initio case but also when homology information to known structures is available. Structural properties are also routinely used in protein analysis even when homology is available, largely because homology modelling is lower throughput than, say, secondary structure prediction. Nonetheless, predictors of secondary structure and solvent accessibility are virtually always ab initio. Results: Here we develop high-throughput machine learning systems for the prediction of protein secondary structure and solvent accessibility that exploit homology to proteins of known structure, where available, in the form of simple structural frequency profiles extracted from sets of PDB templates. We compare these systems to their state-of-the-art ab initio counterparts, and with a number of baselines in which secondary structures and solvent accessibilities are extracted directly from the templates. We show that structural information from templates greatly improves secondary structure and solvent accessibility prediction quality, and that, on average, the systems significantly enrich the information contained in the templates. For sequence similarity exceeding 30%, secondary structure prediction quality is approximately 90%, close to its theoretical maximum, and 2-class solvent accessibility roughly 85%. Gains are robust with respect to template selection noise, and significant for marginal sequence similarity and for short alignments, supporting the claim that these improved predictions may prove beneficial beyond the case in which clear homology is available. Conclusion: The predictive system are publicly available at the address http://distill.ucd.ieScience Foundation IrelandIrish Research Council for Science, Engineering and TechnologyHealth Research BoardUCD President's Award 2004au, da, ke, ab, sp - kpw30/11/1

Revealing the Formation Mechanism and Optimizing the Synthesis Conditions of Layered Double Hydroxides for the Oxygen Evolution Reaction

Layered double hydroxides (LDHs), whose formation is strongly related to OH− concentration, have attracted significant interest in various fields. However, the effect of the real-time change of OH− concentration on LDHs’ formation has not been fully explored due to the unsuitability of the existing synthesis methods for in situ characterization. Here, the deliberately designed combination of NH3 gas diffusion and in situ pH measurement provides a solution to the above problem. The obtained results revealed the formation mechanism and also guided us to synthesize a library of LDHs with the desired attributes in water at room temperature without using any additives. After evaluating their oxygen evolution reaction performance, we found that FeNi-LDH with a Fe/Ni ratio of 25/75 exhibits one of the best performances so far reported

CSpritz: accurate prediction of protein disorder segments with annotation for homology, secondary structure and linear motifs

CSpritz is a web server for the prediction of intrinsic protein disorder. It is a combination of previous Spritz with two novel orthogonal systems developed by our group (Punch and ESpritz). Punch is based on sequence and structural templates trained with support vector machines. ESpritz is an efficient single sequence method based on bidirectional recursive neural networks. Spritz was extended to filter predictions based on structural homologues. After extensive testing, predictions are combined by averaging their probabilities. The CSpritz website can elaborate single or multiple predictions for either short or long disorder. The server provides a global output page, for download and simultaneous statistics of all predictions. Links are provided to each individual protein where the amino acid sequence and disorder prediction are displayed along with statistics for the individual protein. As a novel feature, CSpritz provides information about structural homologues as well as secondary structure and short functional linear motifs in each disordered segment. Benchmarking was performed on the very recent CASP9 data, where CSpritz would have ranked consistently well with a Sw measure of 49.27 and AUC of 0.828. The server, together with help and methods pages including examples, are freely available at URL: http://protein.bio.unipd.it/cspritz/