Surface Modification of Polyethylene with Multi-End-Functional Polyethylene Additives

We have prepared and characterized a series of multifluorocarbon end-functional polyethylene additives, which when blended with polyethylene matrices increase surface hydrophobicity and lipophobicity. Water contact angles of >112° were observed on spin-cast blended film surfaces containing less than 1% fluorocarbon in the bulk, compared to 98° in the absence of any additive. Crystallinity in these films gives rise to surface roughness that is an order of magnitude greater than is typical for amorphous spin-cast films but is too little to give rise to superhydrophobicity. X-ray photoelectron spectroscopy (XPS) confirms the enrichment of the multifluorocarbon additives at the air surface by up to 80 times the bulk concentration. Ion beam analysis was used to quantify the surface excess of the additives as a function of composition, functionality, and molecular weight of either blend component. In some cases, an excess of the additives was also found at the substrate interface, indicating phase separation into self-stratified layers. The combination of neutron reflectometry and ion beam analysis allowed the surface excess to be quantified above and below the melting point of the blended films. In these films, where the melting temperatures of the additive and matrix components are relatively similar (within 15 °C), the surface excess is almost independent of whether the blended film is semicrystalline or molten, suggesting that the additive undergoes cocrystallization with the matrix when the blended films are allowed to cool below the melting point

Measurement Of The Σ̄- Lifetime And Direct Comparison With The Σ+ Lifetime

We have measured the lifetime of the Σ̄- using the Fermilab Proton Center 375 GeV/c charged hyperon beam. We obtained (80.43±0.80±0.14) ps. We also measured the lifetime of the Σ+, obtaining (80.38 ±0.40±0.14) ps, in agreement with the Particle Data Group value. A direct comparison between the two lifetimes from the ratio of the decay curves gives a fractional lifetime difference of Δτ/τ=(-0.06±1.12)%, consistent with equal lifetimes for baryon and antibaryon as required by CPT invariance. ©1999 The American Physical Society.61314Foucher, M., (1992) Phys. Rev. Lett., 68, p. 3004Timm, S., (1995) Phys. Rev. D, 51, p. 4638Dubbs, T., (1994) Phys. Rev. Lett., 72, p. 808Caso, C., (1998) Eur. Phys. J. C, 3, p. 690(1993) GEANT 3.21 CERN Program Library W5103, , CERNKuropatkin, N., private communicationLangland, J.L., (1995) Hyperon and Antihyperon Production in P-Cu Interactions, , Ph.D. thesis, University of IowaMorelos, A., (1993) Phys. Rev. Lett., 71, p. 341

TRY plant trait database – enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives