Assessment of Mechanical Property Variation of As-Processed Bast Fibers
Hemp, flax, and kenaf are bast fibers with promising material characteristics to sustainably displace synthetic fibers used in composites; however, their use in composite applications is hindered by high material property variability. More widespread adoption and application, as well as improved qua...
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Veröffentlicht in: | Sustainability 2019-05, Vol.11 (9), p.2655 |
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Sprache: | eng |
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Zusammenfassung: | Hemp, flax, and kenaf are bast fibers with promising material characteristics to sustainably displace synthetic fibers used in composites; however, their use in composite applications is hindered by high material property variability. More widespread adoption and application, as well as improved quality methods, of fibers is contingent on the reduction of this variability. Efforts made herein to assess variability in as-processed fibers and methods were found to identify key sources of variability by investigating four areas: cross-sectional area approximation, physical defects, color and stem diameter, and fiber composition. Using fiber gage lengths closer to those found in composites, different geometric approximations of cross-sectional areas resulted in mean elliptical approximation showing the lowest variability across all fiber types. Next, by removing fibers exhibiting physical defects, maximum variation in tested flax fibers was reduced from 66% to 49% for ultimate tensile strength and 74% to 36% for elastic modulus. Additionally, fibers of darker color were found to have lower mechanical property variation than lighter or spotted fibers, and those coming from smaller stem diameters were found to be stronger than fibers from large stem diameters. Finally, contrary to previous findings with other lignocellulosics, clear trends between the lignin content in a fiber and its mechanical properties were not readily evident. Overall, these factors combined to significantly reduce mechanical property variation, while identifying the underlying contributing parameters. |
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ISSN: | 2071-1050 2071-1050 |
DOI: | 10.3390/su11092655 |