Kinks in experimental diffusion profiles of a dissolving semi-crystalline polymer explained by a concentration-dependent diffusion coefficient

Hermes, Helen E.; Sitta, Christoph E.; Schillinger, Burkhard; Löwen, Hartmut; Egelhaaf, Stefan U.

doi:10.1039/c5cp01082a

Cited by 12 publications

(14 citation statements)

References 25 publications

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“…This behavior, combined with the very steep initial concentration profile of the solvent (Figure 3a), indicates that the diffusion mechanism of [Bmim]Cl in cotton fiber at 80 °C is similar to Case II transport (Lustig et al, 1992), i.e., the solvent diffusion is rapid compared with the relaxation of glassy cellulose. Similar results have been obtained for the diffusion of methanol in glassy poly(methyl methacrylate) (Thomas and Windle, 1978) and in the decrystallization and dissolution of semicrystalline poly(vinyl alcohol) (Mallapragada and Peppas, 1997) and poly(ethylene oxide) (Hermes et al, 2015) in water.…”

Section: Mechanism Of Solvent Diffusion In Semicrystalline Cellulosesupporting

confidence: 83%

Assessment of solvents for cellulose dissolution

Ghasemi

Tsianou

Alexandridis

2017

Bioresource Technology

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A necessary step in the processing of biomass is the pretreatment and dissolution of cellulose. A good solvent for cellulose involves high diffusivity, aggressiveness in decrystallization, and capability of disassociating the cellulose chains. However, it is not clear which of these factors and under what conditions should be improved in order to obtain a more effective solvent. To this end, a newly-developed phenomenological model has been applied to assess the controlling mechanism of cellulose dissolution. Among the findings, the cellulose fibers remain crystalline almost to the end of the dissolution process for decrystallization-controlled kinetics. In such solvents, decreasing the fiber crystallinity, e.g., via pretreatment, would result in a considerable increase in the dissolution rate. Such insights improve the understanding of cellulose dissolution and facilitate the selection of more efficient solvents and processing conditions for biomass. Specific examples of solvents are provided where dissolution is limited due to decrystallization or disentanglement.

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Section: Mechanism Of Solvent Diffusion In Semicrystalline Cellulosesupporting

confidence: 83%

Assessment of solvents for cellulose dissolution

Ghasemi

Tsianou

Alexandridis

2017

Bioresource Technology

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“…They consist of a two-piece aluminum alloy body. In contrast to a previous cell consisting only of aluminum, 27 the present cell has quartz glass windows. One aluminum part has a spherical window (Hellma, 22 mm diameter, 1.25 mm thickness) glued to it.…”

Section: Sample Cellsmentioning

confidence: 87%

Neutron, fluorescence, and optical imaging: An in situ combination of complementary techniques

Wagner

Börgardts

Grünzweig

et al. 2015

Review of Scientific Instruments

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An apparatus which enables the simultaneous combination of three complementary imaging techniques, optical imaging, fluorescence imaging, and neutron radiography, is presented. While each individual technique can provide information on certain aspects of the sample and their time evolution, a combination of the three techniques in one setup provides a more complete and consistent data set. The setup can be used in transmission and reflection modes and thus with optically transparent as well as opaque samples. Its capabilities are illustrated with two examples. A polymer hydrogel represents a transparent sample and the diffusion of fluorescent particles into and through this polymer matrix is followed. In reflection mode, the absorption of solvent by a nile red-functionalized mesoporous silica powder and the corresponding change in fluorescent signal are studied.

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“…Water acts like a plasticizer and affects diffusion properties within the polymer. This plasticizer effect leads to nonlinear diffusion, and the diffusion coefficient D can show a dependency on concentration . The identification of the interface between swollen and unswollen regions, and its evolution with time, can help in the evaluation of nonlinear diffusion effects.…”

Section: Introductionmentioning

confidence: 99%

Mathematical Modeling and Experimental Study of Water Diffusion and Swelling in Polymer Films

Gagliardi

2019

Macro Theory & Simulations

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Equation (1) is also applied to solvent diffusion in polymers but more recent studies have demonstrated different diffusive behaviors for imbibition. Due to effects of polymer physical properties and polymer/solvent interactions, Alfrey and coworkers have proposed a semi-empirical classification based on polymer relaxation rates, [6] identifying the Fickian and the non-Fickian regimes. According to this model, the amount of solvent absorbed by a polymer membrane follows a power law and the power exponent is related to the transport mechanism.The transport mechanism is related to the bulk properties of the polymer, in particular the physical state. In the rubbery state, when the glass transition temperature T g is above the working temperature T w , molecules show high mobility and it facilitates solvent penetration across the polymer matrix. On the other hand, glassy polymers, with T g < T w , are more rigid and solvent absorption is less easy. [7] In some polymers, the glassy-to-rubbery transition is physically similar to that occurring in hydrated matrices. Water acts like a plasticizer and affects diffusion properties within the polymer. This plasticizer effect leads to nonlinear diffusion, and the diffusion coefficient D can show a dependency on concentration. [8] The identification of the interface between swollen and unswollen regions, and its evolution with time, can help in the evaluation of nonlinear diffusion effects. This internal boundary was experimentally tracked in gelatin beads, and its evolution with time significantly differed from that of the external bead boundary. [9] Mathematical models involving the movement of the internal boundary were developed in food science to study grain hydration [10] while in polymer membranes this study was simplified with a front-fixing transformation [11] and a comprehensive analysis of this aspect is still lacking.When soft materials imbibe a large amount of water their volume can increase. The swelling phenomenon is a kinetic process and it involves mass transport and mechanical properties. [12] In systems with variable volume, concentration profiles are described with the more advanced advection-diffusion model [13] that takes the moving front velocity v into accountNumerical models of swelling, in which the boundary of the domain needs to be calculated as part of the solution, are commonly called Stefan problems. The Stefan problem can describe Absorption Water diffusion and swelling of polymer films can be modeled by nonlinear diffusion equations with fixed or moving boundaries, investigating the Fick and the Stefan problems. To form a better view of the dynamics of the problems, this paper reports the mathematical modeling of water diffusion with linear and nonlinear diffusion coefficients by using the finite element method, and the description of boundary movements calculated with a fully implicit upwind scheme. Experimental results are used to support theoretical data. It is found that porosity strongly affects diffusion properties and proposed models de...

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Kinks in experimental diffusion profiles of a dissolving semi-crystalline polymer explained by a concentration-dependent diffusion coefficient

Cited by 12 publications

References 25 publications

Assessment of solvents for cellulose dissolution

Assessment of solvents for cellulose dissolution

Neutron, fluorescence, and optical imaging: An in situ combination of complementary techniques

Mathematical Modeling and Experimental Study of Water Diffusion and Swelling in Polymer Films

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