Polylactide (PLA)—Halloysite Nanocomposites: Production, Morphology and Key-Properties

To evaluate the potential of halloysite nanotubes (HNT) as nanofiller for polylactide (PLA), various nanocomposites have been successfully produced by melt-blending the polyester matrix with HNT (HNT(QM)). HNT were also surface treated by silanization reaction with 3-(Trimethoxysilyl) propyl methacrylate (TMSPM). The morphology, thermal, tensile and impact strength properties of the nanocomposites containing 3?C12?% HNT were evaluated and compared to those of pristine (unfilled) PLA. The nanocomposites were characterized by higher rigidity (with Young??s modulus increasing with HNT loading), higher tensile strength (about 70?MPa at 6?% HNT(QM)), whereas the elongation at break and impact strength did not decrease. As demonstrated under dynamic solicitation (DMA), melt-blending PLA with HNT led to enhancement of storage modulus (E??) and offers the possibility to use PLA in applications requiring higher temperatures of utilization. However, with few exceptions, TGA and DSC measurements did not reveal important changes of thermal parameters. The surface silanization treatment proved to improve the quality of the nanofiller dispersion even at higher loading. As a result, good thermal stability associated to high tensile strength, and noticeable increases in impact properties were recorded. Furthermore, enhanced nucleating ability and crystallization kinetics of the PLA matrix were revealed as specific characteristics.     

Cadmium speciation and accumulation in periphyton in a small stream with dynamic concentration variations

Accumulation of cadmium in periphyton was investigated under field conditions while Cd concentration and speciation were dynamically varying in a small stream during rain events. Speciation in water was determined in situ by diffusion gradient in thin-films (DGT) and by modeling of complexation with fulvic acids. During the rain events, dissolved Cd concentrations increased from 0.17 nM to 0.27-0.36 nM, and 70-97% were DGT-labile. Cd content in periphyton closely followed Cd concentrations in water, despite higher concentrations of Zn and Mn, and may be controlled by either free or DGT-labile Cd concentrations. Decrease of Cd content in periphyton after the rain events was slower than the decrease of Cd concentration in water. Concentrations of Zn, Mn, Cu, Pb and Fe in periphyton also followed the dynamic variations of metal concentrations in water. Repeated exposure of periphyton to elevated dissolved Cd may lead to Cd accumulation.     

An adaptive reduction algorithm for efficient chemical calculations in global atmospheric chemistry models

We present a computationally efficient adaptive method for calculating the time evolution of the concentrations of chemical species in global 3-D models of atmospheric chemistry. Our strategy consists of partitioning the computational domain into fast and slow regions for each chemical species at every time step. In each grid box, we group the fast species and solve for their concentration in a coupled fashion. Concentrations of the slow species are calculated using a simple semi-implicit formula. Separation of species between fast and slow is done on the fly based on their local production and loss rates. This allows for example to exclude short-lived volatile organic compounds (VOCs) and their oxidation products from chemical calculations in the remote troposphere where their concentrations are negligible, letting the simulation determine the exclusion domain and allowing species to drop out individually from the coupled chemical calculation as their production/loss rates decline. We applied our method to a 1-year simulation of global tropospheric ozone-NO_x-VOC-aerosol chemistry using the GEOS-Chem model. Results show a 50% improvement in computational performance for the chemical solver, with no significant added error.     

Individual-based modelling of carbon and nitrogen dynamics in soils: Parameterization and sensitivity analysis of microbial components

The fate of soil carbon and nitrogen compounds in soils in response to climate change is currently the object of significant research. In particular, there is much interest in the development of a new generation of micro-scale models of soil ecosystems processes. Crucial to the elaboration of such models is the ability to describe the growth and metabolism of small numbers of individual microorganisms, distributed in a highly heterogeneous environment. In this context, the key objective of the research described in this article was to further develop an individual-based soil organic matter model, INDISIM-SOM, first proposed a few years ago, and to assess its performance with a broader experimental data set than previously considered. INDISIM-SOM models the dynamics and evolution of carbon and nitrogen associated with organic matter in soils. The model involves a number of state variables and parameters related to soil organic matter and microbial activity, including growth and decay of microbial biomass, temporal evolutions of easily hydrolysable N, mineral N in ammonium and nitrate, CO₂ and O₂. The present article concentrates on the biotic components of the model. Simulation results demonstrate that the model can be calibrated to provide good fit to experimental data from laboratory incubation experiments performed on three different types of Mediterranean soils. In addition, analysis of the sensitivity toward its biotic parameters shows that the model is far more sensitive to some parameters, i.e., the microbial maintenance energy and the probability of random microbial death, than to others. These results suggest that, in the future, research should focus on securing better measurements of these parameters, on environmental determinants of the switch from active to dormant states, and on the causes of random cell death in soil ecosystems.