Construction and mechanistic insights of a novel ZnO functionalized rGO composite for efficient adsorption and reduction of Cr(VI).

A series of ZnO decorated reduced graphene oxide (rGO) (ZnrGOx) with different doping ratios were synthesized by the alkaline hydrothermal method using graphene oxide (GO) and Zn(NO3)2·6H2O as precursors, and subsequently used for the adsorption study of Cr(VI) in water. The morphology, crystalline phase structure, and surface elemental properties of ZnrGOx composites were revealed by XRD, SEM, BET, FT-IR, and XPS characterizations. The results showed that ZnO nanoparticles can be clearly seen on the surface of layered rGO. Meanwhile, as the doping rate increased, the C = C double bonds were broken and more carboxylic acid groups formed in ZnrGOx. In addition, the ZnrGO0.1 composite had the most excellent adsorption performance and good stability, and reusability. The adsorption removal rate of Cr(VI) can reach 99%, and the maximum adsorption amount of Cr(VI) was 68.9655 mg/g in 3 h. The isothermal and kinetic model simulations showed that Cr(VI) adsorption on ZnrGO0.1 composite is a chemical adsorption process, spontaneous and endothermic. Based on the concentrations of different valence states of Cr in the solid and liquid phases, 40% of Cr(VI) was reduced to Cr(III) on the surface of ZnrGO0.1 composite. Moreover, the adsorption-reduction mechanisms of Cr(VI) on ZnrGO0.1 composite were further elucidated. The ZnrGO0.1 composite manifested great potential as an efficient adsorbent for Cr(VI) removal.

Multistability in neural systems with random cross-connections.

Neural circuits with multiple discrete attractor states could support a variety of cognitive tasks according to both empirical data and model simulations. We assess the conditions for such multistability in neural systems using a firing rate model framework, in which clusters of similarly responsive neurons are represented as single units, which interact with each other through independent random connections. We explore the range of conditions in which multistability arises via recurrent input from other units while individual units, typically with some degree of self-excitation, lack sufficient self-excitation to become bistable on their own. We find many cases of multistability-defined as the system possessing more than one stable fixed point-in which stable states arise via a network effect, allowing subsets of units to maintain each others' activity because their net input to each other when active is sufficiently positive. In terms of the strength of within-unit self-excitation and standard deviation of random cross-connections, the region of multistability depends on the response function of units. Indeed, multistability can arise with zero self-excitation, purely through zero-mean random cross-connections, if the response function rises supralinearly at low inputs from a value near zero at zero input. We simulate and analyze finite systems, showing that the probability of multistability can peak at intermediate system size, and connect with other literature analyzing similar systems in the infinite-size limit. We find regions of multistability with a bimodal distribution for the number of active units in a stable state. Finally, we find evidence for a log-normal distribution of sizes of attractor basins, which produces Zipf's Law when enumerating the proportion of trials within which random initial conditions lead to a particular stable state of the system.

Multistability in neural systems with random cross-connections.

Neural circuits with multiple discrete attractor states could support a variety of cognitive tasks according to both empirical data and model simulations. We assess the conditions for such multistability in neural systems, using a firing-rate model framework, in which clusters of neurons with net self-excitation are represented as units, which interact with each other through random connections. We focus on conditions in which individual units lack sufficient self-excitation to become bistable on their own. Rather, multistability can arise via recurrent input from other units as a network effect for subsets of units, whose net input to each other when active is sufficiently positive to maintain such activity. In terms of the strength of within-unit self-excitation and standard-deviation of random cross-connections, the region of multistability depends on the firing-rate curve of units. Indeed, bistability can arise with zero self-excitation, purely through zero-mean random cross-connections, if the firing-rate curve rises supralinearly at low inputs from a value near zero at zero input. We simulate and analyze finite systems, showing that the probability of multistability can peak at intermediate system size, and connect with other literature analyzing similar systems in the infinite-size limit. We find regions of multistability with a bimodal distribution for the number of active units in a stable state. Finally, we find evidence for a log-normal distribution of sizes of attractor basins, which can appear as Zipf's Law when sampled as the proportion of trials within which random initial conditions lead to a particular stable state of the system.

Catalytic ozonation oxidation of ketoprofen by peanut shell-based biochar: effects of the pyrolysis temperatures.

A series of peanut shell (HS)-based biochar were prepared at different pyrolysis temperatures and subsequently used as the effective ozonation catalysts for ketoprofen (KET) degradation in aqueous solution. The physicochemical properties and morphology of the obtained biochar were analysed by ICP, TG, XRD, FT-IR, SEM, TEM, BET and etc. characterizations. The results demonstrated that the pyrolysis temperature played an important role on the structure and morphology of HS-based biochar. As the pyrolysis temperature increased, the cellulose and hemicellulose of HS gradually decomposed, resulting in the loss of biochar mass, improvement of the surface roughness, the increase of specific surface area, and the formation of new functional groups. The HS-based biochar pyrolyzed at 600°C (HS600) achieved the fast KET degradation rate with the pseudo-first-order rate constant of 0.922 min-1 and the low adsorption rate of 1.3% in O3/HS600 process. Meanwhile, the effects of the HS600 dosage, initial KET concentration, temperature, water matrix, and solution pH on KET degradation were systematically evaluated. Besides, the HS600 displayed great stability and reusability towards KET degradation during multiple cycling experiments. Moreover, the single oxygen, superoxide radical and hydroxyl radical were involved in O3/HS600 process and the mechanisms for the improvement of KET degradation were also elucidated. It could be speculated that the enhancement of the catalytic ozonation by HS-based biochar was probably attributed to the increased active sites and the intense chemical bonds, and delocalized π electron.

Finite-size effects for spiking neural networks with spatially dependent coupling.

We study finite-size fluctuations in a network of spiking deterministic neurons coupled with nonuniform synaptic coupling. We generalize a previously developed theory of finite-size effects for globally coupled neurons with a uniform coupling function. In the uniform coupling case, mean-field theory is well defined by averaging over the network as the number of neurons in the network goes to infinity. However, for nonuniform coupling it is no longer possible to average over the entire network if we are interested in fluctuations at a particular location within the network. We show that if the coupling function approaches a continuous function in the infinite system size limit, then an average over a local neighborhood can be defined such that mean-field theory is well defined for a spatially dependent field. We then use a path-integral formalism to derive a perturbation expansion in the inverse system size around the mean-field limit for the covariance of the input to a neuron (synaptic drive) and firing rate fluctuations due to dynamical deterministic finite-size effects.

Free energy contributions and structural characterization of stacking disordered ices.

Crystallization of ice from deeply supercooled water and amorphous ices - a process of fundamental importance in the atmosphere, interstellar space, and cryobiology - results in stacking disordered ices with a wide range of metastabilities with respect to hexagonal ice. The structural origin of this high variability, however, has not yet been elucidated. Here we use molecular dynamics simulations with the mW water model to characterize the structure of ice freshly grown from supercooled water at temperatures from 210 to 270 K, the thermodynamics of stacking faults, line defects, and interfaces, and to elucidate the interplay between kinetics and thermodynamics in determining the structure of ice. In agreement with experiments, the ice grown in the simulations is stacking disordered with a random distribution of cubic and hexagonal layers, and a cubicity that decreases with growth temperature. The former implies that the cubicity of ice is determined by processes at the ice/liquid interface, without memory of the structure of buried ice layers. The latter indicates that the probability of building a cubic layer at the interface decreases upon approaching the melting point of ice, which we attribute to a more efficient structural equilibration of ice at the liquid interface as the driving force for growth wanes. The free energy cost for creating a pair of cubic layers in ice is 8.0 J mol(-1) in experiments, and 9.7 ± 1.9 J mol(-1) for the mW water model. This not only validates the simulations, but also indicates that dispersion in cubicity is not sufficient to explain the large energetic variability of stacking disordered ices. We compute the free energy cost of stacking disorder, line defects, and interfaces in ice and conclude that a characterization of the density of these defects is required to predict the degree of metastability and vapor pressure of atmospheric ices.

B→πll Form Factors for New Physics Searches from Lattice QCD.

The rare decay B→πℓ^{+}ℓ^{-} arises from b→d flavor-changing neutral currents and could be sensitive to physics beyond the standard model. Here, we present the first ab initio QCD calculation of the B→π tensor form factor f_{T}. Together with the vector and scalar form factors f_{+} and f_{0} from our companion work [J. A. Bailey et al., Phys. Rev. D 92, 014024 (2015)], these parametrize the hadronic contribution to B→π semileptonic decays in any extension of the standard model. We obtain the total branching ratio BR(B^{+}→π^{+}µ^{+}µ^{-})=20.4(2.1)×10^{-9} in the standard model, which is the most precise theoretical determination to date, and agrees with the recent measurement from the LHCb experiment [R. Aaij et al., J. High Energy Phys. 12 (2012) 125].

Determination of |V(us)|| from a lattice QCD calculation of the K → πℓν semileptonic form factor with physical quark masses.

We calculate the kaon semileptonic form factor f+(0) from lattice QCD, working, for the first time, at the physical light-quark masses. We use gauge configurations generated by the MILC Collaboration with Nf = 2 + 1 + 1 flavors of sea quarks, which incorporate the effects of dynamical charm quarks as well as those of up, down, and strange. We employ data at three lattice spacings to extrapolate to the continuum limit. Our result, f+(0) = 0.9704(32), where the error is the total statistical plus systematic uncertainty added in quadrature, is the most precise determination to date. Combining our result with the latest experimental measurements of K semileptonic decays, one obtains the Cabibbo-Kobayashi-Maskawa matrix element |V(us)| = 0.22290(74)(52), where the first error is from f+(0) and the second one is from experiment. In the first-row test of Cabibbo-Kobayashi-Maskawa unitarity, the error stemming from |V(us)| is now comparable to that from |V(ud)|.

Refining new-physics searches in B→Dτν with lattice QCD.

The semileptonic decay channel B→Dτν is sensitive to the presence of a scalar current, such as that mediated by a charged-Higgs boson. Recently, the BABAR experiment reported the first observation of the exclusive semileptonic decay B→Dτ(-)ν, finding an approximately 2σ disagreement with the standard-model prediction for the ratio R(D)=BR(B→Dτν)/BR(B→Dℓν), where ℓ = e,µ. We compute this ratio of branching fractions using hadronic form factors computed in unquenched lattice QCD and obtain R(D)=0.316(12)(7), where the errors are statistical and total systematic, respectively. This result is the first standard-model calculation of R(D) from ab initio full QCD. Its error is smaller than that of previous estimates, primarily due to the reduced uncertainty in the scalar form factor f(0)(q(2)). Our determination of R(D) is approximately 1σ higher than previous estimates and, thus, reduces the tension with experiment. We also compute R(D) in models with electrically charged scalar exchange, such as the type-II two-Higgs-doublet model. Once again, our result is consistent with, but approximately 1σ higher than, previous estimates for phenomenologically relevant values of the scalar coupling in the type-II model. As a by-product of our calculation, we also present the standard-model prediction for the longitudinal-polarization ratio P(L)(D)=0.325(4)(3).