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Characterization of 3D Ultrastructure of Plant Biomass and Development of a Transport-Reaction Model for the Pretreatment Process.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Characterization of 3D Ultrastructure of Plant Biomass and Development of a Transport-Reaction Model for the Pretreatment Process./
作者:	Ramanna, Sahana.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2021,
面頁冊數:	183 p.
附註:	Source: Dissertations Abstracts International, Volume: 83-02, Section: B.
Contained By:	Dissertations Abstracts International83-02B.
標題:	Chemical engineering. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28497559
ISBN:	9798534688542

Characterization of 3D Ultrastructure of Plant Biomass and Development of a Transport-Reaction Model for the Pretreatment Process.
Ramanna, Sahana.

Characterization of 3D Ultrastructure of Plant Biomass and Development of a Transport-Reaction Model for the Pretreatment Process. - Ann Arbor : ProQuest Dissertations & Theses, 2021 - 183 p.

Source: Dissertations Abstracts International, Volume: 83-02, Section: B.

Thesis (Ph.D.)--University of Minnesota, 2021.

This item must not be sold to any third party vendors.

The complex network of fibers and pore spaces in porous materials such as paper, wood etc., affect their structure, physical properties, and transport characteristics. In the case of wood or plant biomass, the system consists of cellulose fibers enclosed in a matrix of lignin and cellulose with some void spaces enclosed. Biomass is renewable and can be converted to a wide variety of bio-based products including biofuels, biochemicals, bioplastics, paper, wood plastic composites etc. The 3D internal structure of biomass can be related to their material properties. The biomass ultrastructure and how they change during various treatments may play a critical role in influencing the biomass conversion processes. Hence, it is essential to have an overall understanding of the 3D ultrastructure of plant cell walls and its relationship to the properties and how their change influences biomass conversion processes. The first step in biomass conversion processes is the pretreatment which is crucial in terms of the changes it brings to the cell wall architecture which in turn influences the reaction path forward. During this step, degradation of one or more of the cell wall components occur thereby, potentially altering the cell wall architecture. This is achieved with the help of several reagents such as alkali, acid, hot water, ammonia, enzymes, etc. and paves way for further treatment and conversion processes.While most of the previous work in this regard focuses mainly on 2D structure characterization using techniques such as optical and scanning electron microscopy, Fourier transform infra-red spectroscopy, atomic force microscopy, etc., it is vital that 3D structure characterization techniques are employed to fully explore the ultrastructure in a non-intrusive manner. This is possible with the advent of techniques such as Computed Tomography (CT) using either X-rays or Transmission Electron Microscopy (TEM). The current work uses TEM-CT to visualize the structural evolution of plant biomass and determine changes in properties such as porosity, pore size distribution and surface area, due to pretreatment. The cell wall structure was disrupted during pretreatment which resulted in a more porous structure and greater surface area which made it suitable for further hydrolysis. Additionally, topochemical distribution obtained from Raman spectroscopy was correlated with the TEM-CT structural evolution data in order to provide a complete understanding of the pretreatment process. In this context, a 3D transport-reaction model was then developed based on stochastic principles and reaction kinetics for lignin dissolution during pretreatment.The simultaneous transport-reaction occurring within the biomass cell wall structure is modeled using a hybrid random walk process. In our model, the structure and topochemical distribution of the untreated biomass sample obtained using Confocal Laser Scanning Raman Microscopy was used as the initial biomass sample. The diffusion and reaction model, using the actual biomass structure, begins in the cell wall lumen where the reagent particles diffuse through the lumen and other enclosed pore spaces based on a hybrid random walk. Diffusion continues in the pore phase until the fiber phase is encountered, upon which either reaction or further diffusion occurs based on the reaction probability. The reaction probability is determined from the Thiele modulus which encompasses both diffusive and reactive behavior of the system. The changes in lignin concentration in the cell wall is determined by local pseudo first order kinetics where the rate of reaction depends on the lignin concentration. The reagent used for pretreatment is assumed to be available in abundance compared to the lignin in the cell wall. The extent of conversion and thereby the efficiency of the pretreatment process is determined by the rate of transport of the reagents both in the pore and fiber phases, reaction probability, local kinetics, and ratio of diffusivity between the pore and fiber phases. Both the spatial and bulk concentration profiles of lignin as a function of reaction time were determined from the diffusion-reaction simulation. It was shown that the effective rate constant Keff considering both transport and reaction during biomass conversion is a function of biomass composition and, in some cases, also the reaction time. This is in correspondence with prior work reported in the biomass conversion literature. In addition, an overall transport rate co-efficient KT considering only the bulk and internal diffusion of the reagent in the cell wall system during pretreatment was determined based on walker's survival time.The transport and reaction model results for different biomass species and pretreatment processes were compared with experimental data and appropriate local transport and reaction rate constants were determined. The relative effects of diffusion and reaction during biomass conversion for a given biomass species was then studied using various Thiele moduli over an appropriate range. Interestingly, it was found that diffusive transport, in general, played a critical role in the overall biomass dissolution. However, the relative effect of diffusion was found to be more significant at a lower Thiele modulus than at a higher Thiele modulus for the same local rate constant. The critical Thiele modulus may also depend on the biomass species and the biomass treatment conditions. These results indicate that approaches to opening the cell wall prior to any chemical/biochemical treatment, thus increasing their diffusive transport characteristics, may help with improving the efficiency of biomass pretreatment processes and, hence, further conversion. The results from the transport and reaction model may provide additional insights on the relative benefits of thermal, mechanical, and chemical pretreatment processes prior to further biomass conversion. This may help to select appropriate pretreatment processes for effective biomass conversion. The 3D structure visualization, characterization and the transport-reaction model using actual biomass structure developed here can help provide fundamental insights into the structure-property relationships during biomass pretreatment as well gain additional insight in developing improved biomass conversion strategies.

ISBN: 9798534688542Subjects--Topical Terms:

560457
Chemical engineering.
Subjects--Index Terms:

3D Characterization

Characterization of 3D Ultrastructure of Plant Biomass and Development of a Transport-Reaction Model for the Pretreatment Process.
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245 1 0 $a Characterization of 3D Ultrastructure of Plant Biomass and Development of a Transport-Reaction Model for the Pretreatment Process.
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300 $a 183 p.
500 $a Source: Dissertations Abstracts International, Volume: 83-02, Section: B.
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502 $a Thesis (Ph.D.)--University of Minnesota, 2021.
506 $a This item must not be sold to any third party vendors.
520 $a The complex network of fibers and pore spaces in porous materials such as paper, wood etc., affect their structure, physical properties, and transport characteristics. In the case of wood or plant biomass, the system consists of cellulose fibers enclosed in a matrix of lignin and cellulose with some void spaces enclosed. Biomass is renewable and can be converted to a wide variety of bio-based products including biofuels, biochemicals, bioplastics, paper, wood plastic composites etc. The 3D internal structure of biomass can be related to their material properties. The biomass ultrastructure and how they change during various treatments may play a critical role in influencing the biomass conversion processes. Hence, it is essential to have an overall understanding of the 3D ultrastructure of plant cell walls and its relationship to the properties and how their change influences biomass conversion processes. The first step in biomass conversion processes is the pretreatment which is crucial in terms of the changes it brings to the cell wall architecture which in turn influences the reaction path forward. During this step, degradation of one or more of the cell wall components occur thereby, potentially altering the cell wall architecture. This is achieved with the help of several reagents such as alkali, acid, hot water, ammonia, enzymes, etc. and paves way for further treatment and conversion processes.While most of the previous work in this regard focuses mainly on 2D structure characterization using techniques such as optical and scanning electron microscopy, Fourier transform infra-red spectroscopy, atomic force microscopy, etc., it is vital that 3D structure characterization techniques are employed to fully explore the ultrastructure in a non-intrusive manner. This is possible with the advent of techniques such as Computed Tomography (CT) using either X-rays or Transmission Electron Microscopy (TEM). The current work uses TEM-CT to visualize the structural evolution of plant biomass and determine changes in properties such as porosity, pore size distribution and surface area, due to pretreatment. The cell wall structure was disrupted during pretreatment which resulted in a more porous structure and greater surface area which made it suitable for further hydrolysis. Additionally, topochemical distribution obtained from Raman spectroscopy was correlated with the TEM-CT structural evolution data in order to provide a complete understanding of the pretreatment process. In this context, a 3D transport-reaction model was then developed based on stochastic principles and reaction kinetics for lignin dissolution during pretreatment.The simultaneous transport-reaction occurring within the biomass cell wall structure is modeled using a hybrid random walk process. In our model, the structure and topochemical distribution of the untreated biomass sample obtained using Confocal Laser Scanning Raman Microscopy was used as the initial biomass sample. The diffusion and reaction model, using the actual biomass structure, begins in the cell wall lumen where the reagent particles diffuse through the lumen and other enclosed pore spaces based on a hybrid random walk. Diffusion continues in the pore phase until the fiber phase is encountered, upon which either reaction or further diffusion occurs based on the reaction probability. The reaction probability is determined from the Thiele modulus which encompasses both diffusive and reactive behavior of the system. The changes in lignin concentration in the cell wall is determined by local pseudo first order kinetics where the rate of reaction depends on the lignin concentration. The reagent used for pretreatment is assumed to be available in abundance compared to the lignin in the cell wall. The extent of conversion and thereby the efficiency of the pretreatment process is determined by the rate of transport of the reagents both in the pore and fiber phases, reaction probability, local kinetics, and ratio of diffusivity between the pore and fiber phases. Both the spatial and bulk concentration profiles of lignin as a function of reaction time were determined from the diffusion-reaction simulation. It was shown that the effective rate constant Keff considering both transport and reaction during biomass conversion is a function of biomass composition and, in some cases, also the reaction time. This is in correspondence with prior work reported in the biomass conversion literature. In addition, an overall transport rate co-efficient KT considering only the bulk and internal diffusion of the reagent in the cell wall system during pretreatment was determined based on walker's survival time.The transport and reaction model results for different biomass species and pretreatment processes were compared with experimental data and appropriate local transport and reaction rate constants were determined. The relative effects of diffusion and reaction during biomass conversion for a given biomass species was then studied using various Thiele moduli over an appropriate range. Interestingly, it was found that diffusive transport, in general, played a critical role in the overall biomass dissolution. However, the relative effect of diffusion was found to be more significant at a lower Thiele modulus than at a higher Thiele modulus for the same local rate constant. The critical Thiele modulus may also depend on the biomass species and the biomass treatment conditions. These results indicate that approaches to opening the cell wall prior to any chemical/biochemical treatment, thus increasing their diffusive transport characteristics, may help with improving the efficiency of biomass pretreatment processes and, hence, further conversion. The results from the transport and reaction model may provide additional insights on the relative benefits of thermal, mechanical, and chemical pretreatment processes prior to further biomass conversion. This may help to select appropriate pretreatment processes for effective biomass conversion. The 3D structure visualization, characterization and the transport-reaction model using actual biomass structure developed here can help provide fundamental insights into the structure-property relationships during biomass pretreatment as well gain additional insight in developing improved biomass conversion strategies.
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