Standardized Morphology Analysis of Cellulose Nanocrystals via a Semi-Automated Image Processing Approach
Author(s)
Yucel, Sezen
Advisor(s)
Moon, Robert J.
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Abstract
This thesis addresses the challenges in the investigation of cellulose nanocrystals (CNC) particle size measurements using transmission electron microscopy (TEM) and atomic force microscopy (AFM) image analysis. Standardizing particle size measurements an important step in the design and optimization of the processes employed in the manufacture and utilization of CNCs. Current protocols used in the analyses of CNC particle morphology for TEM and AFM images are largely manual and time-consuming, and often produce inconsistent results between different researchers.
Chapter 1 introduces a new semi-automated image analysis framework that can reliably and quickly detect and classify CNCs from TEM and AFM images, measure their dimensions and each particle’s detailed shape information, and provide additional information about different CNC configurations within the images. Chapter 2 explains the development of this framework, named as CNC-SMART (CNC – Standardized Morphology Analysis for Research and Technology), which utilizes different automated and semi-automated image processing workflows. The viability of this framework is demonstrated in this work using exemplar images obtained for a National Research Council Canada certified reference material, CNCD-1. The results obtained from the SMART approach presented in this work are compared critically against the results obtained from the conventional manual approaches. These comparisons revealed a good agreement between the manual and SMART approaches and proved that CNC-SMART can expeditiously process high-throughput image data using these workflows while being minimally impacted by human error and variability.
Chapter 3 and Chapter 4 are two different demonstrations of CNC-SMART which can be considered case studies in which the SMART approach was adapted and improved for further applications. Case studies are an extension of an inter-laboratory comparison (ILC) research on CNC particle size measurements performed by ten participating research laboratories using TEM and AFM imaging. Collaborating with different researchers and using different image datasets with varying image properties such as noise and contrast helped refine the SMART approach to be a more versatile system with more capabilities that were not primarily considered during the initial development phase.
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Date
2022-05-23
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Text
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Dissertation