Enhanced Morphological Characterization of Cellulose Nano/Microfibers through Image Skeleton Analysis

Area of Science:

• Materials Science
• Biomaterials Engineering
• Nanotechnology

Background:

• Cellulose nano and microfibers (CMF/CNFs) are crucial biomaterials with diverse applications.
• Controlling CMF/CNF morphology during industrial production is essential for product quality and performance.
• Existing characterization methods may lack the detail or scalability needed for real-time industrial monitoring.

Purpose of the Study:

• To introduce a novel, image analysis-based approach for the morphological characterization of CMF/CNF suspensions.
• To enable detailed quantification of CMF/CNF networks and fibrillation modes.
• To provide a scalable tool for monitoring and controlling CMF/CNF quality in industrial settings.

Main Methods:

• Analysis of eroded microscopy images of CMF/CNF suspensions.
• Skeleton analysis of microscopy images to extract morphological information.
• Complementary estimation of aspect ratio from gel point data.

Main Results:

• The method successfully characterized CMF/CNF morphology from various raw materials and processing conditions.
• Quantification of specific morphological changes: fiber peeling (mechanical), fiber shortening (enzymatic), and CMF/CNF entanglement (TEMPO-oxidation).
• Demonstrated the ability to discern fibrillation modes linked to different extraction conditions.

Conclusions:

• The proposed image analysis method offers a robust and detailed approach to CMF/CNF morphological characterization.
• This technique is readily implementable at an industrial scale for quality control and process optimization.
• The findings facilitate better understanding and control over CMF/CNF production, leading to improved material quality and homogeneity.