Advanced materials that can remain electrically conductive under substantial elastic stretch and bending have attracted extensive interest recently owing to their broad application potentials, particularly for flexible electronics. Here, we have developed a simple and inexpensive method to fabricate highly conductive and stretchable composites using bacterial cellulose (BC) pellicles as starting materials, which can be produced in large amounts on an industrial scale via a microbial fermentation process. The prepared pyrolyzed BC (p-BC)/polydimethylsiloxane (PDMS) composites exhibit a high electrical conductivity of 0.20-0.41 S cm À1 , which is much higher than conventional carbon nanotubes and graphene-based composites. More importantly, the p-BC/PDMS composites that combine high stretchability with high conductivity show great electromechanical stability. Even after 1000 stretching cycles at the maximum strain of 80%, the resistance of the composites increased by only B10%. The resistance increased slightly (B4%) after 5000 bending cycles with a maximum bending radius of 1.0 mm.
BackgroundMetagenomics can reveal the vast majority of microbes that have been missed by traditional cultivation-based methods. Due to its extremely wide range of application areas, fast metagenome sequencing simulation systems with high fidelity are in great demand to facilitate the development and comparison of metagenomics analysis tools.ResultsWe present here a customizable metagenome simulation system: NeSSM (Next-generation Sequencing Simulator for Metagenomics). Combining complete genomes currently available, a community composition table, and sequencing parameters, it can simulate metagenome sequencing better than existing systems. Sequencing error models based on the explicit distribution of errors at each base and sequencing coverage bias are incorporated in the simulation. In order to improve the fidelity of simulation, tools are provided by NeSSM to estimate the sequencing error models, sequencing coverage bias and the community composition directly from existing metagenome sequencing data. Currently, NeSSM supports single-end and pair-end sequencing for both 454 and Illumina platforms. In addition, a GPU (graphics processing units) version of NeSSM is also developed to accelerate the simulation. By comparing the simulated sequencing data from NeSSM with experimental metagenome sequencing data, we have demonstrated that NeSSM performs better in many aspects than existing popular metagenome simulators, such as MetaSim, GemSIM and Grinder. The GPU version of NeSSM is more than one-order of magnitude faster than MetaSim.ConclusionsNeSSM is a fast simulation system for high-throughput metagenome sequencing. It can be helpful to develop tools and evaluate strategies for metagenomics analysis and it’s freely available for academic users at http://cbb.sjtu.edu.cn/~ccwei/pub/software/NeSSM.php.
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