Fluorescent labeling and image analysis of cellulosic fillers in biocomposites: Effect of added compatibilizer and correlation with physical properties
Source abstract
Abstract
Abstract The performance of cellulosic filler/polyolefin biocomposites is affected by the filler dispersion (aggregation and spatial arrangement) in the matrix. However, this mechanistic factor is generally inferred from the physical properties of the final bulk material because of the limitations of analytical techniques. Herein, we propose a simple method to quantitatively evaluate the dispersion of filler particles. To accomplish this, the cellulose component in injection-molded specimens of microcrystalline cellulose (MCC)/maleic anhydride-modified polypropylene (MAPP)/polypropylene (PP) composites was selectively fluorescently labeled with calcofluor white, and the dispersion state of tens of thousands of MCC particles observed by fluorescence microscopy was analyzed. The close-range aggregation behavior of the MCC particles can be evaluated by the area of the fluorescent particles (A), and the normality (randomness) of the spatial arrangement can be classified by the skewness of the distribution of the distances between the centroids of the particles (s). As a result, with an increase in the degree of acid modification of the added MAPP, aggregation of MCC was suppressed and the spatial arrangement became random. Both A and s were not associated with the modulus or fracture strain of the injection-molded specimens, but they were correlated with the tensile and bending strengths and water absorption behavior. This visualization method was also applied to a composite containing nanofibrillated cellulose filler (citric acid-modified cellulose nanofiber).
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Natural Fiber Reinforced Composites · Advanced Cellulose Research Studies · biodegradable polymer synthesis and properties
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (27)
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