Abstract
Chrome tanning is the most common method used to produce leather, but its environmental and health impacts have necessitated the search for alternatives that have proved to be challenging. The circular economy, which uses biomasses to reduce and recover waste, is seen as a potential solution. In Morocco, fruit waste produced by juice processing industries is an untapped source of tannins that could replace chrome tanning in a more sustainable manner. In this study, a new eco-friendly tanning method based on vegetable biomass has been developed to reduce chromium-related environmental pollution and enhance leather performance. Tanning activities of extracts from six Moroccan pomegranate rind (PR) varieties were investigated, by studying their crosslinking with the insoluble collagen (IC) extracted from a sheep hide, under industrial tanning conditions. Herein, molecular distribution of crosslinkers extracts were carried out using gel exclusion chromatography to follow polymerization degree and crosslinking kinetics during tanning process. Between linear and logarithmic profiles, tannins and phenolics behave differently during the crosslinking depending on their molecular weight. Fourier Transform Infrared Spectroscopy exhibits the existence of inter and intramolecular interaction between IC functional groups and extract. X-Ray Diffraction analysis shows the influence of crosslinkers extracts into the triple helix structure of collagen. Scanning Electron Microscopy observations shows the fibrial size variations of crosslinked collagenous structure by varying the extract variety. Differential Scanning Calorimetry and thermogravimetric measurements revealed that the thermal stabilities were affected by the extracts varieties origins. Theoretical studies using Gaussian was used as a complementally tool to compare the reactivity and the stability of the major molecules that contributes in the crosslinking process. Principal Component Analysis (PCA) was used to examine correlations between the crosslinked IC and PR extracts' analyzed properties. The data set's dimension was reduced to two components via PCA, which accounted for 69.79% of the observed variability.
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