Quantum Monte Carlo study of the H- impurity in small helium clusters

We report ground state energies and structural properties for small helium clusters (4He) containing an H- impurity computed by means of variational and diffusion Monte Carlo methods. Except for 4He_2H- that has a noticeable contribution from collinear geometries where the H- impurity lies between the two 4He atoms, our results show that our 4He_NH- clusters have a compact 4He_N subsystem that binds the H- impurity on its surface. The results for $N\geq 3$ can be interpreted invoking the different features of the minima of the He-He and He-H- interaction potentials.Comment: 12 pages, 7 Ps figure

Hydrophobic aggregation and collective absorption of dioxin into lipid membranes: insights from atomistic simulations

Dioxins are a highly toxic class of chlorinated aromatic chemicals. They have been extensively studied, but several molecular-level details of their action are still missing. Here we present molecular dynamics simulations of their absorption and diffusion through cell membranes. We show that, due to their hydrophobic character, dioxins can quickly penetrate into a lipid membrane, both as single molecules and as aggregates. We find clear evidence for their ability to accumulate in cell membranes. Our free energy calculations indicate that subsequent transport into the cell is unlikely to be a simple diffusive process

Positron and positronium chemistry by quantum Monte Carlo. VI. The ground state of LiPs, NaPs, e(+)Be, and e(+)Mg

The ground states of the positronic complexes LiPs, NaPs, e(+)Be, e(+)Mg, and of the parent ordinary-matter systems have been simulated by means of the all-electron fixed-node diffusion Monte Carlo (DMC) method. Positron affinities and positronium binding energies are computed by direct difference between the DMC energy results. LiPs was recomputed in order to test the possibility of approximating the electron-positron Coulomb potential with a model one that does not diverge for r=0, finding accurate agreement with previous DMC results. As to e(+)Be, the effect due to the near degeneracy of the 1s(2)2s(2) and 1s(2)2p(2) configurations in Be is found to be relevant also for the positron affinity, and is discussed on the basis of the change in the ionization potential and the dipole polarizability. The DMC estimate of the positron affinity of Mg, a quantity still under debate, is 0.0168(14) hartree, in close agreement with the value 0.015 612 hartree computed by Mitroy and Ryzhihk [J. Phys. B. 34, 2001 (2001)] using explicitly correlated Gaussians. (C) 2002 American Institute of Physics

Computing accurate forces in quantum Monte Carlo using Pulay's corrections and energy minimization

3In order to overcome the difficulty of optimizing molecular geometry using quantum Monte Carlo methods, we introduce various approximations to the exact force expectation value. We follow Pulay's suggestion [Mol. Phys. 17, 153 (1969)] to correct the Hellmann-Feynman estimator by introducing the contributions due to the changes in the wave function with respect to the nuclear positions. When used in conjunction with energy-optimized explicitly correlated trial wave functions for H-2 and LiH, these approximations appear to yield accurate forces using both the variational and diffusion Monte Carlo methods. Also, the accuracy of the second-order estimate of the Hellmann-Feynman force estimator was investigated employing our energy-optimized trial wave functions, and an erratic behavior was uncovered for some of the studied bond lengths. The additional computational cost required to compute the corrections to the Hellmann-Feynman estimator was found to be only a small fraction of the cost for a simple mean energy calculation. The same approach could be exploited also in computing the derivative of other energy-dependent quantum-mechanical observables. (C) 2003 American Institute of Physics.openM. Casalegno;M. Mella;A. M. RappeM., Casalegno; Mella, Massimo; A. M., Rapp

Ytterbium disilicate-based glass-ceramic as joining material for ceramic matrix composites

A key aspect of ceramic matrix composites integration is related to a reliable joining technique. An ytterbium disilicate based glass-ceramic material is processed by reactive viscous flow sintering between a barium aluminium borosilicate glass and ytterbium oxide and it is used to join SiC/SiC and C/SiC composites. The joining temperature and the in situ formation of the Yb2Si2O7 is optimised at 1200°C without pressure, on the basis of the sintering and crystallisation mechanisms. The mechanical characterization of SiC/SiC and C/SiC joined with the ytterbium disilicate-based glass-ceramic, tested by single-lap offset at RT, exhibits an apparent shear strength of 35 MPa, similar to their interlaminar shear strength. The proposed system displays self-healing behaviour at 1000 °C and 1150 °C, as demonstrated by the partial and complete sealing of induced cracks by Vickers indentation on its surface at different loads, thus suggesting that it can effectively be used as promising joining material for CMCs

The pitfalls of inferring virus-virus interactions from co-detection prevalence data: application to influenza and SARS-CoV-2

There is growing experimental evidence that many respiratory viruses—including influenza and SARS-CoV-2—can interact, such that their epidemiological dynamics may not be independent. To assess these interactions, standard statistical tests of independence suggest that the prevalence ratio—defined as the ratio of co-infection prevalence to the product of single-infection prevalences—should equal unity for non-interacting pathogens. As a result, earlier epidemiological studies aimed to estimate the prevalence ratio from co-detection prevalence data, under the assumption that deviations from unity implied interaction. To examine the validity of this assumption, we designed a simulation study that built on a broadly applicable epidemiological model of co-circulation of two emerging or seasonal respiratory viruses. By focusing on the pair influenza–SARS-CoV-2, we first demonstrate that the prevalence ratio systematically underestimates the strength of interaction, and can even misclassify antagonistic or synergistic interactions that persist after clearance of infection. In a global sensitivity analysis, we further identify properties of viral infection—such as a high reproduction number or a short infectious period—that blur the interaction inferred from the prevalence ratio. Altogether, our results suggest that ecological or epidemiological studies based on co-detection prevalence data provide a poor guide to assess interactions among respiratory viruses

Estimating the impact of influenza on the epidemiological dynamics of SARS-CoV-2

As in past pandemics, co-circulating pathogens may play a role in the epidemiology of coronavirus disease 2019 (COVID-19), caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In particular, experimental evidence indicates that influenza infection can up-regulate the expression of ACE2—the receptor of SARS-CoV-2 in human cells—and facilitate SARS-CoV-2 infection. Here we hypothesized that influenza impacted the epidemiology of SARS-CoV-2 during the early 2020 epidemic of COVID-19 in Europe. To test this hypothesis, we developed a population-based model of SARS-CoV-2 transmission and of COVID-19 mortality, which simultaneously incorporated the impact of non-pharmaceutical control measures and of influenza on the epidemiological dynamics of SARS-CoV-2. Using statistical inference methods based on iterated filtering, we confronted this model with mortality incidence data in four European countries (Belgium, Italy, Norway, and Spain) to systematically test a range of assumptions about the impact of influenza. We found consistent evidence for a 1.8–3.4-fold (uncertainty range across countries: 1.1 to 5.0) average population-level increase in SARS-CoV-2 transmission associated with influenza during the period of co-circulation. These estimates remained robust to a variety of alternative assumptions regarding the epidemiological traits of SARS-CoV-2 and the modeled impact of control measures. Although further confirmatory evidence is required, our results suggest that influenza could facilitate the spread and hamper effective control of SARS-CoV-2. More generally, they highlight the possible role of co-circulating pathogens in the epidemiology of COVID-19