Molecular dynamics simulations of energetic Ar cluster bombardment of Ag(111)

Large-scale molecular dynamics computer simulations are used to investigate the dynamics of material ejection during high-energy Ar_{n} cluster bombardment of Ag(111) at normal incidence. The silver sample containing 7 million atoms is bombarded with Ar_{n} projectiles (n=45-30000) with kinetic energy spanning from a few keV up to 1 MeV. Such a wide range of projectile parameters allows probing processes taking place during low-density collision cascade as well as during high-density events characteristic of micrometeorite bombardment in space. The material modifications and total sputtering yield of ejected particles are investigated. While at low-energy impacts, ejection of individual silver atoms is the main emission channel, the ejection of large clusters from the corona of the created crater dominates for the high-energy impacts

Sputtering of benzene sample by large Ne, Ar and Kr clusters : molecular dynamics computer simulations

Molecular dynamics simulations are employed to probe the role of an impact angle on emission efficiency of organic molecules sputtered from benzene crystal bombarded by 15 keV $Ne_{2953}$, $Ar_{2953}$, and $Kr_{2953}$ clusters. It is found that both the cluster type and the angle of incidence have significant effect on the emission efficiency. The shape of the impact angle dependence does not resemble the dependence characteristic for medium size clusters ($C_{60}, Ar_{366}$), where sputtering yield only moderately increases with the impact angle, has a shallow maximum around 40° and then decreases. On the contrary, for the large projectiles ($Ne_{2953}, Ar_{2953}$, and $Kr_{2953}$) the emission efficiency steeply increases with the impact angle, has a pronounced maximum around 55° followed by rapid signal decay. It has been found that the sputtering yield is the most sensitive to the impact angle change for Kr cluster projectiles, while change of the impact angle of Ne projectile has the smallest effect on the efficiency of material ejection

Non-Standard Errors

In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: Non-standard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for better reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants

How do food sources drive meiofauna community structure in soft bottom coastal food webs?

International audienceMeiofauna have a strong role in the functioning of coastal ecosystems but how their food sources affect their community structure remains unclear, likely due to the influence of abiotic parameters and the small size of these organisms. The meiofauna and their potential food sources were sampled in several intertidal habitats (i.e., mudflat, seagrass bed, sandflat) of the Marennes-Oléron Bay, France, and the Sylt-Rømø Bight, Germany, to assess the relationships between habitat characteristics and meiofauna community structure. Biomass and quality (carbon/chlorophyll a ratios) of food sources were estimated. Meiofauna community structure based on density and biomass was determined, as well as nematode diversity and feeding types. Meiofauna density and biomass varied highly within habitats and within ecosystems, ranging from 1.7 × 10⁵ to 3.4 × 10⁶ ind. m⁻² and from 0.057 to 1.541 gC m⁻², respectively. Benthic microalgae and sediment organic matter are important drivers in these food webs as the density of two important trophic groups of nematodes, non-selective deposit feeders and epigrowth feeders, varied in accordance with these food sources. No clear relationship was observed between bacterial biomass and selective deposit feeders (i.e., bacterivores) probably due to the high production rate of bacteria. Complementary information about production rates of food source as well as data from trophic markers would provide complimentary information to better understand flows of organic matter in intertidal habitats, particularly for opportunistic species such as non-selective deposit feeders