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The subject of the presented research focuses on a comparative assessment of three types of polymer fillers used to modify highly crystalline poly(lactic acid) PLA intended for the FDM technique. The aim of the presented work was to determine the performance of the developed materials. The key aspect of the work was the use of polymer fillers of three different types. Nano-sized montmorillonite (MMT), biobased biocarbon (BC) and mineral talc. The several types of composites were prepared using extrusion technique. The maximum content for BC and talc filler was limited to 20 wt%, while for MMT it was 5 wt%. Prepared samples were subjected to detailed material analysis including mechanical tests (tensile, flexural, Charpy), thermal analysis (DSC, DMTA), HDT/Vicat tests and structure analysis. The results of the test confirmed that even relatively small amount of nano-type filler can be more efficient than micrometric particles. The used type of matrix was highly crystalline PLA, which resulted in a significant nucleation effect of the crystalline structure. However, thermomechanical tests revealed no improvement in thermal resistance. Microscopic survey confirmed that for MMT and talc filler the structure anisotropy was leading to more favorable properties, especially when compared to structures based on spherical BC particles.

BackgroundConstraint-based approaches facilitate the prediction of cellular metabolic capabilities, based, in turn on predictions of the repertoire of enzymes encoded in the genome. Recently, genome annotations have been used to reconstruct genome scale metabolic reaction networks for numerous species, including Homo sapiens, which allow simulations that provide valuable insights into topics, including predictions of gene essentiality of pathogens, interpretation of genetic polymorphism in metabolic disease syndromes and suggestions for novel approaches to microbial metabolic engineering. These constraint-based simulations are being integrated with the functional genomics portals, an activity that requires efficient implementation of the constraint-based simulations in the web-based environment.ResultsHere, we present Acorn, an open source (GNU GPL) grid computing system for constraint-based simulations of genome scale metabolic reaction networks within an interactive web environment. The grid-based architecture allows efficient execution of computationally intensive, iterative protocols such as Flux Variability Analysis, which can be readily scaled up as the numbers of models (and users) increase. The web interface uses AJAX, which facilitates efficient model browsing and other search functions, and intuitive implementation of appropriate simulation conditions. Research groups can install Acorn locally and create user accounts. Users can also import models in the familiar SBML format and link reaction formulas to major functional genomics portals of choice. Selected models and simulation results can be shared between different users and made publically available. Users can construct pathway map layouts and import them into the server using a desktop editor integrated within the system. Pathway maps are then used to visualise numerical results within the web environment. To illustrate these features we have deployed Acorn and created a web server allowing constraint based simulations of the genome scale metabolic reaction networks of E. coli, S. cerevisiae and M. tuberculosis.ConclusionsAcorn is a free software package, which can be installed by research groups to create a web based environment for computer simulations of genome scale metabolic reaction networks. It facilitates shared access to models and creation of publicly available constraint based modelling resources.

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