LYOCELL AND COTTON FIBERS AS REINFORCEMENTS FOR A THERMOSET POLYMER

Cellulose fibers obtained from the textile industry (lyocell) were investigated as a potential reinforcement for thermoset phenolic matrices, to improve their mechanical properties. Textile cotton fibers were also considered. The fibers were characterized in terms of their chemical composition and analyzed using TGA, SEM, and X-ray. The thermoset (non-reinforced) and composites (phenolic matrices reinforced with randomly dispersed fibers) were characterized using TG, DSC, SEM, DMTA, the Izod impact strength test, and water absorption capacity analysis. The composites that were reinforced with lyocell fibers exhibited impact strengths of nearly 240 Jm(-1), whereas those reinforced with cotton fibers exhibited impact strengths of up to 773 Jm(-1). In addition to the aspect ratio, the higher crystallinity of cotton fibers compared to lyocell likely plays a role in the impact strength of the composite reinforced by the fibers. The SEM images showed that the porosity of the textile fibers allowed good bulk diffusion of the phenolic resin, which, in turn, led to both good adhesion of fiber to matrix and fewer microvoids at the interface.

Mapping and Quantification of the Cotton Chain in Brazil

The CHAINPlan method developed by Neves (2007) is a practical tool which can be used to construct strategic plans for production chains. A preliminary step in this process includes mapping and quantifying the production chain. We present the results of applying the method to one of the most important agribusiness chains in Brazil-the cotton sector. The Gross Domestic Product for the cotton sector in the 2010-2011 crop year was estimated at nearly $19.2 billion. We show the interconnections between the links in the chain and its ability to generate revenues, taxes and jobs.

Processing of high resolution magic angle spinning spectra of breast cancer cells by the filter diagonalization method

Proton nuclear magnetic resonance (H-1 NMR) spectroscopy for detection of biochemical changes in biological samples is a successful technique. However, the achieved NMR resolution is not sufficiently high when the analysis is performed with intact cells. To improve spectral resolution, high resolution magic angle spinning (HR-MAS) is used and the broad signals are separated by a T-2 filter based on the CPMG pulse sequence. Additionally, HR-MAS experiments with a T-2 filter are preceded by a water suppression procedure. The goal of this work is to demonstrate that the experimental procedures of water suppression and T-2 or diffusing filters are unnecessary steps when the filter diagonalization method (FDM) is used to process the time domain HR-MAS signals. Manipulation of the FDM results, represented as a tabular list of peak positions, widths, amplitudes and phases, allows the removal of water signals without the disturbing overlapping or nearby signals. Additionally, the FDM can also be used for phase correction and noise suppression, and to discriminate between sharp and broad lines. Results demonstrate the applicability of the FDM post-acquisition processing to obtain high quality HR-MAS spectra of heterogeneous biological materials.

Multi-Walled Carbon Nanotubes and Poly(lactic acid) Nanocomposite Fibrous Membranes Prepared by Solution Blow Spinning

Nanocomposite fibers based on multi-walled carbon nanotubes (MWCNT) and poly(lactic acid) (PLA) were prepared by solution blow spinning (SBS). Fiber morphology was characterized by scanning electron microscopy (SEM) and optical microscopy (OM). Electrical, thermal, surface and crystalline properties of the spun fibers were evaluated, respectively, by conductivity measurements (4-point probe), thermogravimetric analyses (TGA), differential scanning calorimetry (DSC), contact angle and X-ray diffraction (XRD). OM analysis of the spun mats showed a poor dispersion of MWCNT in the matrix, however dispersion in solution was increased during spinning where droplets of PLA in solution loaded with MWCNT were pulled by the pressure drop at the nozzle, producing PLA fibers filled with MWCNT. Good electrical conductivity and hydrophobicity can be achieved at low carbon nanotube contents. When only 1 wt% MWCNT was added to low-crystalline PLA, surface conductivity of the composites increased from 5 x 10(-8) to 0.46 S/cm. Addition of MWCNT can slightly influence the degree of crystallinity of PLA fibers as studied by XRD and DSC. Thermogravimetric analyses showed that MWCNT loading can decrease the onset degradation temperature of the composites which was attributed to the catalytic effect of metallic residues in MWCNT. Moreover, it was demonstrated that hydrophilicity slightly increased with an increase in MWCNT content. These results show that solution blow spinning can also be used to produce nanocomposite fibers with many potential applications such as in sensors and biosensors.

Processes Mapping in Cotton Culture to Traceability Creation

Traceability is a concept that arose from the need for monitoring of production processes, this concept is usually used in sectors related to food production or activities involving some kind of direct risk to people. Agribusiness in the cotton industry does not have a comprehensive infrastructure for all stages of the processes involved in production. Map and define the data to enable traceability of products is synonymous to delegate responsibilities for all involved in the production, the collection of aggregate data on cotton production is done in stages and specific pre-defined since the choice of the variety through the processing, the scope of this article specifically addresses the production of lint cotton. The paper presents a proposal based on service oriented architecture (SOA) for data integration processes in the cotton industry, this proposal provide support for the implementation of platform independent solutions.

Ontology for Data Representation in the Production of Cotton Fiber in Brazil

An important feature in computer systems developed for the agricultural sector is to satisfy the heterogeneity of data generated in different processes. Most problems related with this heterogeneity arise from the lack of standard for different computing solutions proposed. An efficient solution for that is to create a single standard for data exchange. The study on the actual process involved in cotton production was based on a research developed by the Brazilian Agricultural Research Corporation (EMBRAPA) that reports all phases as a result of the compilation of several theoretical and practical researches related to cotton crop. The proposition of a standard starts with the identification of the most important classes of data involved in the process, and includes an ontology that is the systematization of concepts related to the production of cotton fiber and results in a set of classes, relations, functions and instances. The results are used as a reference for the development of computational tools, transforming implicit knowledge into applications that support the knowledge described. This research is based on data from the Midwest of Brazil. The choice of the cotton process as a study case comes from the fact that Brazil is one of the major players and there are several improvements required for system integration in this segment.