Polymer nanocomposites : Insights on rheology, percolation and molecular mobility

The integration of carbon nanotubes (CNTs) into a polymer matrix strongly affects the rheological behavior that in turn may hamper the overall performance of the resulting composite. Research in this topic has focused on bulk rheological properties, while here we employ NMR diffusion experiments to explore the mobility (diffusivity) of epoxy molecules when loaded with CNTs. Rheology and light microscopy indicate percolation of CNT aggregates. Those aggregates cage a substantial amount of epoxy molecules while small angle X-ray scattering indicates some rearrangement of epoxy molecules in the vicinity of the nanotubes. NMR diffusion experiments distinguish between the slow diffusion of the caged molecules and that of the free ones, and relate the fraction of the former to the macroscopic system viscosity. The demonstrated surface-induced slowing-down of diffusion is attributed to strong intermolecular π-π interactions among the epoxy molecules, and between them and the CNT surface. These findings demonstrate the utility of NMR diffusion experiments as an additional method applied to nanocomposites. </p

M-CAMP™: A cloud-based web platform with a novel approach for species-level classification of 16S rRNA microbiome sequences

AbstractThe M-CAMP™ (Microbiome Computational Analysis for Multiomic Profiling) Cloud Platform was designed to provide users with an easy-to-use web interface to access best in class microbiome analysis tools. This interface allows bench scientists to conduct bioinformatic analysis on their samples and then download publication-ready graphics and reports. The core pipeline of the platform is the 16S-seq taxonomic classification algorithm which provides species-level classification of Illumina 16s sequencing. This algorithm uses a novel approach combining alignment and kmer based taxonomic classification methodologies to produce a highly accurate and comprehensive profile. Additionally, a comprehensive proprietary database combining reference sequences from multiple sources was curated and contains 18056 unique V3-V4 sequences covering 11527 species. The M-CAMP™ 16S taxonomic classification algorithm was validated on 52 sequencing samples from both public and in-house standard sample mixtures with known fractions. Compared to current popular public classification algorithms, our classification algorithm provides the most accurate species-level classification of 16S rRNA sequencing data.</jats:p