Dewatering of Cellulose Nanomaterials using Ultrasound
Loading...
Author(s)
Ringania, Udita
Advisor(s)
Editor(s)
Collections
Supplementary to:
Permanent Link
Abstract
This dissertation aims to develop a sustainable dewatering technology that can dramatically lower the energy consumption in pulp and paper industries. Using ultrasound technology, the study offers an energy-efficient and sustainable technique for dewatering Cellulose Nanomaterials (CNMs), a highly valuable cellulosic materials used in various industries. Given their unique properties and renewable nature, CNMs offer potential for achieving a sustainable economy. However, the high energy requirements associated with their dewatering and drying acts as a bottleneck in their widescale application.
The research is segmented into three key objectives: First, the dissertation aims to design an energy-efficient, scalable, low-cost platform for dewatering Cellulose Nanofibers (CNFs) and examines the effects of system parameters on dewatering efficiency. Second, the research investigates how the fines percentage in cellulose nanofibrils affects the ultrasonic dewatering process. Lastly, it seeks to automate the image analysis process for highly branched fibrils, enabling faster and easier characterisation.
Overall, the goal is to provide a sustainable solution to dewatering challenges in pulp and paper industries, reducing both energy consumption and cost, while also addressing key issues such as agglomeration.
Guide to dissertation:
In Chapter 1, I outline the dissertation’s motivation and research aims. I familiarize the reader with CNMs, explaining their conventional drying and dewatering techniques, and shedding light on the challenges intrinsic to these methods.
In Chapter 2, I introduce an innovative ultrasonic dewatering process for CNFs which is validation through proof-of-concept experiments using a static dewatering setup. I also present a design for a continuous dewatering platform and evaluates its efficiency by considering parameters such as the number and configuration of transducers, the CNF flow rate on the transducers, and mesh pore size. I assess the redispersibility of dewatered samples and benchmarks it against CNFs dewatered using other methods. I conclude the chapter by providing an energy estimation and comparison.
In Chapter 3, I further examine the influence of material parameters — specifically, the percentage of fines in the CNFs sample — on ultrasonic dewatering efficiency. I explore possible water removal mechanism, guided by observed dewatering curves for varying fines percentages. Finally, I evaluate the dependence of suspension stability of the redispersed samples on fines percentage, final dewatered CNFs weight, and redispersion time.
My experiences with CNFs in previous chapters highlighted the challenges associated with characterizing these highly branched fibrils, which span a broad dimension range. In Chapter 4, I discuss an automated image analysis method, developed to ease the characterization of these highly branched fibrils through application of machine learning algorithms.
Finally, in Chapter 5, I conclude the dissertation, offering recommendations for sustainable implementation of the technology. Here, I also describe few other methods that can be followed up for future work.
Sponsor
Date
2023-07-30
Extent
Resource Type
Text
Resource Subtype
Dissertation