Shear Modulus Dependence of the Diffusion Coefficient of a Polymer Network

Fujiyabu, Takeshi; Yoshikawa, Yuki; Kim, Junhyuk; Sakumichi, Naoyuki; Chung, Ung‐il; Sakai, Takamasa

doi:10.1021/acs.macromol.9b01654

Cited by 12 publications

(37 citation statements)

References 36 publications

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“…Another diffusion may occur, called abnormal diffusion ( Goychuk, 2009 ; Yasuda et al, 2017 ), which is representative of viscoelastic diffusion (diffusion in relaxing media) that is affected by the mechanics of the system ( Caccavo et al, 2018 ). The diffusion coefficient in a semi-solid and the viscoelastic properties of medium are correlated ( Tanaka et al, 1973 ; Fujiyabu et al, 2019 ). For the brain viscoelastic medium with a linear elastic behavior, it is Young’s modulus E which is the most described.…”

Section: Discussionmentioning

confidence: 99%

A Minireview on Brain Models Simulating Geometrical, Physical, and Biochemical Properties of the Human Brain

Bouattour¹,

Sautou

Hmede

et al. 2022

Front. Bioeng. Biotechnol.

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There is a growing body of evidences that brain surrogates will be of great interest for researchers and physicians in the medical field. They are currently mainly used for education and training purposes or to verify the appropriate functionality of medical devices. Depending on the purpose, a variety of materials have been used with specific and accurate mechanical and biophysical properties, More recently they have been used to assess the biocompatibility of implantable devices, but they are still not validated to study the migration of leaching components from devices. This minireview shows the large diversity of approaches and uses of brain phantoms, which converge punctually. All these phantoms are complementary to numeric models, which benefit, reciprocally, of their respective advances. It also suggests avenues of research for the analysis of leaching components from implantable devices.

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Section: Discussionmentioning

confidence: 99%

A Minireview on Brain Models Simulating Geometrical, Physical, and Biochemical Properties of the Human Brain

Bouattour¹,

Sautou

Hmede

et al. 2022

Front. Bioeng. Biotechnol.

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“…This work was motivated by two reasons. (a) The gel dynamics is now being quantitatively studied for precisely controlled gel samples, [12][13][14] and the effect of shear modulus G has been studied. Results of rigorous calculation is needed in such studies.…”

Section: Introductionmentioning

confidence: 99%

Swelling Dynamics of a Disk-Shaped Gel

Man,

Doi

2021

Preprint

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When a gel absorbs solvent from surrounding, stress field is created in the gel, and this causes complex dynamics of the swelling behavior. Here we study this effect for disk-shaped gel by rigorously solving the diffusio-mechanical coupling equation. We show that (a) while the macroscopic thickness and the radius of the gel increases monotonically in time, the gel is compressed near the mid-plane, and that (b) while the swelling time depends on the shear modulus G of the gel, its dependence is weak, and the time is mainly determined by the friction constant of the gel network and the osmotic bulk modulus of the gel. We also show that these characteristic features are reproduced accurately by a simple variational calculation for the gel deformation. An analytical expression is given for the swelling time.

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“…We measured D via DLS on an ALV/CGS-3 compact goniometer system (ALV, Langen, Germany) in the same way as in Refs. [17,18]. A He-Ne laser with a power of 22 mW emitting polarized light at 632.8 nm was used.…”

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confidence: 99%

“…We cannot directly compare our experimental results with D = [K + (4/3)G]/f because K = K mix +K el includes both polymer-solvent mixing contributions (K mix = c∂Π mix /∂c) and elastic contribution (K el = c∂Π el /∂c). Assuming that (i) Π el = −G [22], (ii) the scaling law G ∼ c β during the swelling [23], and (iii) f (T, c, p) f (T, c) (the water permeation experiments [24,25] confirm that the dependence of f on p is quite weak), we have [17,18] FIG. 3.…”

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confidence: 99%

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Temperature Dependence of Polymer Network Diffusion

Fujiyabu,

Sakai,

Kudo

et al. 2021

Preprint

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The swelling dynamics of polymer gels are characterized by the (collective) diffusion coefficient of the polymer network. Here, we measure the temperature dependence of the diffusion coefficients of polymer gels with controlled homogeneous network structures using dynamic light scattering. By developing the procedure for decomposing the diffusion coefficient into mixing and elastic contributions, we find that the elastic contribution is a linear function of the absolute temperature with a significant negative constant term. This feature is formally identical to the recently discovered "negative energy elasticity." Our findings further advance practical applications of polymer gels because the diffusion coefficient determines the swelling response time.

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Shear Modulus Dependence of the Diffusion Coefficient of a Polymer Network

Abstract: Dynamics of a polymer gel network is described by the theory proposed by Tanaka, Hocker, and Benedek (THB) that gives the diffusion coefficient of a polymer network D K G f 4 3

Cited by 12 publications

References 36 publications

A Minireview on Brain Models Simulating Geometrical, Physical, and Biochemical Properties of the Human Brain

A Minireview on Brain Models Simulating Geometrical, Physical, and Biochemical Properties of the Human Brain

Swelling Dynamics of a Disk-Shaped Gel

Temperature Dependence of Polymer Network Diffusion

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