Raman fingerprints of ultrasmall nanodiamonds produced from adamantane

The synthesis of ultrasmall (2-5 nm) nanodiamonds purely from adamantane at pressure of 12 GPa is reported. Their structural features have been studied by Raman spectroscopy. The unusual vibration band containing a number of pronounced maxima at about 1147, 1245, 1344, and 1456 cm-1 was detected in Raman spectra. The band is confidently identified with the bending vibrational modes of CHx groups terminating the nanodiamonds surface. Excessively intense mode at 1344 cm-1 is explained by its coupling with the 1328 cm-1 diamond phonons. The Raman band found is proposed to be used for express recognition of ultrasmall nanodiamonds produced from adamantane and other hydrocarbons with a high hydrogen content. Moreover, polarized CH bonds on a diamond surface are sensitive to environmental conditions. This opens up opportunities for using the diamond produced from adamantane as ultrasmall nanosensors in biology, chemistry, and medicineComment: 12 pages, 6 figure

High pressure metallization and amorphization of the molecular crystal Sn(IBr){sub 2}

An insulator-to-metal transition concurring with amorphization is found in the cubic (Pa{bar 3}) molecular crystal Sn(IBr){sub 2} at P {approx} 20 GPa. Measurements were carried out with diamond-anvil cells at pressures up to {approximately}30 GPa using resistance measurements, X-ray diffraction (XRD), and {sup 119}Sn Moessbauer spectroscopy (MS). With increasing pressure a new crystalline phase is observed in the 10--23 GPa range; at P {approx} 16 GPa a gradual onset of structural disorder is first observed, and full amorphization takes place at P {ge} 21 GPa. Both electronic properties as measured by R(P,T) and MS data are consistent with a gradual growth of disordered (SnI{sub 2}Br{sub 2}){sub n} polymeric chains, formed by intermolecular I{single_bond}I bonding allowing for electronic delocalization to occur. Upon decompression both XRD and {sup 119}Sn MS show a significant pressure hysteresis

Urine disinfection and in situ pathogen killing using a Microbial Fuel Cell cascade system

© 2017 Ieropoulos et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Microbial Fuel Cells (MFCs) are emerging as an effective means of treating different types of waste including urine and wastewater. However, the fate of pathogens in an MFC-based system remains unknown, and in this study we investigated the effect of introducing the enteric pathogen Salmonella enterica serovar enteritidis in an MFC cascade system. The MFCs continuously fed with urine showed high disinfecting potential. As part of two independent trials, during which the bioluminescent S. enteritidis strain was introduced into the MFC cascade, the number of viable counts and the level of bioluminescence were reduced by up to 4.43-0.04 and 4.21-0.01 log-fold, respectively. The killing efficacy observed for the MFCs operating under closed-circuit conditions, were higher by 1.69 and 1.72 log-fold reduction than for the open circuit MFCs, in both independent trials. The results indicated that the bactericidal properties of a well performing anode were dependent on power performance and the oxidation-reduction potential recorded for the MFCs. This is the first time that the fate of pathogenic bacteria has been investigated in continuously operating MFC systems

High-throughput comparison, functional annotation, and metabolic modeling of plant genomes using the PlantSEED resource

The increasing number of sequenced plant genomes is placing new demands on the methods applied to analyze, annotate, and model these genomes. Today's annotation pipelines result in inconsistent gene assignments that complicate comparative analyses and prevent efficient construction of metabolic models. To overcome these problems, we have developed the PlantSEED, an integrated, metabolism-centric database to support subsystems-based annotation and metabolic model reconstruction for plant genomes. PlantSEED combines SEED subsystems technology, first developed for microbial genomes, with refined protein families and biochemical data to assign fully consistent functional annotations to orthologous genes, particularly those encoding primary metabolic pathways. Seamless integration with its parent, the prokaryotic SEED database, makes PlantSEED a unique environment for cross-kingdom comparative analysis of plant and bacterial genomes. The consistent annotations imposed by PlantSEED permit rapid reconstruction and modeling of primary metabolism for all plant genomes in the database. This feature opens the unique possibility of model-based assessment of the completeness and accuracy of gene annotation and thus allows computational identification of genes and pathways that are restricted to certain genomes or need better curation. We demonstrate the PlantSEED system by producing consistent annotations for 10 reference genomes. We also produce a functioning metabolic model for each genome, gapfilling to identify missing annotations and proposing gene candidates for missing annotations. Models are built around an extended biomass composition representing the most comprehensive published to date. To our knowledge, our models are the first to be published for seven of the genomes analyzed

The Dynamical Cluster Approximation: Non-Local Dynamics of Correlated Electron Systems

We recently introduced the dynamical cluster approximation(DCA), a new technique that includes short-ranged dynamical correlations in addition to the local dynamics of the dynamical mean field approximation while preserving causality. The technique is based on an iterative self-consistency scheme on a finite size periodic cluster. The dynamical mean field approximation (exact result) is obtained by taking the cluster to a single site (the thermodynamic limit). Here, we provide details of our method, explicitly show that it is causal, systematic, $\Phi$-derivable, and that it becomes conserving as the cluster size increases. We demonstrate the DCA by applying it to a Quantum Monte Carlo and Exact Enumeration study of the two-dimensional Falicov-Kimball model. The resulting spectral functions preserve causality, and the spectra and the CDW transition temperature converge quickly and systematically to the thermodynamic limit as the cluster size increases.Comment: 19 pages, 13 postscript figures, revte

Charge-transfer metal-insulator transitions in the spin-one-half Falicov-Kimball model

The spin-one-half Falicov-Kimball model is solved exactly on an infinite-coordination-number Bethe lattice in the thermodynamic limit. This model is a paradigm for a charge-transfer metal-insulator transition where the occupancy of localized and delocalized electronic orbitals rapidly changes at the metal-insulator transition (rather than the character of the electronic states changing from insulating to metallic as in a Mott-Hubbard transition). The exact solution displays both continuous and discontinuous (first-order) transitions.Comment: 22 pages including 4 figures(eps), RevTe