Dissecting giant hailstones: A glimpse into the troposphere with its diverse bacterial communities and fibrous microplastics

The formation of giant hailstones is a rare weather event that has devastating consequences in inhabited areas. This hazard has been occurring more frequently and with greater size of hailstones in recent years, and thus needs to be better understood. While the generally accepted mechanism is thought to be a process similar to the formation of smaller hailstones but with exceptional duration and stronger updrafts, recent evidence suggests that biotic and abiotic factors also influence the growth of these unusually large ice chunks. In this study, we improved these findings by determining the distribution of a wide variety of these factors throughout the hail volume and expanding the search to include new particles that are common in the environment and are of anthropogenic origin. We melted the concentric layers of several giant hailstones that fell to the ground over a small region in Slovenia in 2019. The samples, up to 13 cm in diameter, were analyzed for biotic and abiotic constituents that could have influenced their formation. Using 16S rRNA-based metagenomics approaches, we identified a highly diverse bacterial community, and by using scanning electron microscopy and Raman spectroscopy, we found natural and synthetic fibers concentrated in the cores of the giant hailstones. For the first time, we were able to detect the existence of microplastic fibers in giant hailstones and determine the changes in the distribution of sand within the volume of the samples. Our results suggest that changes in the composition of hail layers and their great diversity are important factors that should be considered in research. It also appears that anthropogenic microfiber pollutants were a significant factor in the formation of the giant hailstones analyzed in this study.

Characterization of Polyamide 6/Multilayer Graphene Nanoplatelet Composite Textile Filaments Obtained Via In Situ Polymerization and Melt Spinning

Studies of the production of fiber-forming polyamide 6 (PA6)/graphene composite material and melt-spun textile fibers are scarce, but research to date reveals that achieving the high dispersion state of graphene is the main challenge to nanocomposite production. Considering the significant progress made in the industrial mass production of graphene nanoplatelets (GnPs), this study explored the feasibility of production of PA6/GnPs composite fibers using the commercially available few-layer GnPs. To this aim, the GnPs were pre-dispersed in molten ε-caprolactam at concentrations equal to 1 and 2 wt %, and incorporated into the PA6 matrix by the in situ water-catalyzed ring-opening polymerization of ε-caprolactam, which was followed by melt spinning. The results showed that the incorporated GnPs did not markedly influence the melting temperature of PA6 but affected the crystallization temperature, fiber bulk structure, crystallinity, and mechanical properties. Furthermore, GnPs increased the PA6 complex viscosity, which resulted in the need to adjust the parameters of melt spinning to enable continuous filament production. Although the incorporation of GnPs did not provide a reinforcing effect of PA6 fibers and reduced fiber tensile properties, the thermal stability of the PA6 fiber increased. The increased melt viscosity and graphene anti-dripping properties postponed melt dripping in the vertical flame spread test, which consequently prolonged burning within the samples.

A Unique Interactive Nanostructure Knitting based Passive Sampler Adsorbent for Monitoring of Hg2+ in Water

This work reports the development of ultralight interwoven ultrathin graphitic carbon nitride (g-CN) nanosheets for use as a potential adsorbent in a passive sampler (PAS) designed to bind Hg²⁺ ions. The g-CN nanosheets were prepared from bulk g-CN synthesised via a modified high-temperature short-time (HTST) polycondensation process. The crystal structure, surface functional groups, and morphology of the g-CN nanosheets were characterised using a battery of instruments. The results confirmed that the as-synthesized product is composed of few-layered nanosheets. The adsorption efficiency of g-CN for binding Hg²⁺ (100 ng mL⁻¹) in sea, river, rain, and Milli-Q quality water was 89%, 93%, 97%, and 100%, respectively, at natural pH. Interference studies found that the cations tested (Co²⁺, Ca²⁺, Zn²⁺, Fe²⁺, Mn²⁺, Ni²⁺, Bi³⁺, Na⁺, and K⁺) had no significant effect on the adsorption efficiency of Hg²⁺. Different parameters were optimised to improve the performance of g-CN such as pH, contact time, and amount of adsorbent. Optimum conditions were pH 7, 120 min incubation time and 10 mg of nanosheets. The yield of nanosheets was 72.5%, which is higher compared to other polycondensation processes using different monomers. The g-CN sheets could also be regenerated up to eight times with only a 20% loss in binding efficiency. Overall, nano-knitted g-CN is a promising low-cost green adsorbent for use in passive samplers or as a transducing material in sensor applications.