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URC - Enhancing Performance and Sustainability in Engineering Plastics by Using Natural Fillers
Objective and Background
Optical Image of Coconut Shell CompositeShort-fiber-reinforced thermoplastic composites enjoy widespread industrial application due to the ease in fabricating complex morphologies and being able to control bulk material properties by the manufacturing process. Properties of the thermoplastics are dependent on the fiber orientation and resulting micro-structure within the polymer matrix which is determined by the manufacturing process. Computer simulation techniques, such as those from the related NSF funded project NSF MPM #720399, have made it possible to perform accurate simulations of the injection molding process and thus predict these properties.

The goal of this project is to image layer-by-layer the cut cross section of processed thermoplastic composites reinforced with natural and synthetic fillers to obtain the orientations and position vectors of a distribution of fibers within a polymeric matrix. Preliminary images taken with the SEM are comprised of polypropylene and coconut fibers as the natural filler (shown below left). The SEM afforded higher contrast images than the optical microscopy images (image above right). This contrast becomes even more significant for fiberglass reinforced polypropylene and noted in the figure below on the right.
SEM Image of Coconut Shell Composite
SEM Image of Fiberglass Composite
Optical Image of Coconut Shell Composite Processed in MATLABUsing the SEM image from the coconut Fibers, we created an image analysis software suite of files using MATLAB to automatically capture each fiber with minimal manual inputs. Images show that the techniques need improvement, however, we have shown that the fibers can be imaged using various microscopy techniques.

Improvements in the experimental method for this research will be in the areas of sample preparation techniques and pursuing alternative microscopy methods.

We thank Baylor University’s URC program for their financial support of this work.
Preliminary Results
  • Developed image analysis model to determine fiber/particle outputs from image(s)
  • Able to obtain values for fiber area, orientation, length of major/minor axis length, ellipticalness, etc.
  • Confirmed aspect ratio results with previously established results.
  • Developed SEM techniques to image both natural and fiberglass reinforced polypropylene composites.
Baylor University School of Engineering and Computer Science Department of Mechanical Engineering Sic'Em - Scientific Innovations in Composites and Engineering Materials