DIFFUSION-SOFTENING OF CELLULOSE NANOCRYSTAL AND THERMOPLASTIC POLYURETHANE COMPOSITES

Cailean Q. Pritchard; Jacob J. Fallon; Jeffrey Shelton; Michael J. Bortner; Cody Weyhrich; Katherine Heifferon; Boer Liu; Timothy E. Long; E. Johan Foster

DIFFUSION-SOFTENING OF CELLULOSE NANOCRYSTAL AND THERMOPLASTIC POLYURETHANE COMPOSITES

Cailean Q. Pritchard, Jacob J. Fallon, Jeffrey Shelton, Michael J. Bortner, Cody Weyhrich, Katherine Heifferon, Boer Liu, Timothy E. Long, E. Johan Foster

Molecular Sciences, School of (SMS)

Research output: Contribution to conference › Paper › peer-review

Abstract

Smart materials that can adapt their mechanical response in the presence of an external stimuli are popular for their applications in 4D printing. Such printing methods exploit a smart material's capability to interact with these stimuli to impart controlled material deformation tailored to specific applications. A modified percolation model was formulated to predict the dynamic transition exhibited in polymer composites containing cellulose nanocrystals (CNCs) which undergo mechanical softening in the presence of water. Coupling the effects water diffusion to the degree of CNC connectivity provided a method to capture the dynamic softening of CNC-based, water responsive smart materials as a function of filler loading. This modeling approach can be implemented to develop humidity sensing actuators and water-sensitive shape memory devices.

Original language	English (US)
State	Published - 2022
Event	SPE ANTEC 2022 Conference - Charlotte, United States Duration: Jun 14 2022 → Jun 16 2022

Conference

Conference	SPE ANTEC 2022 Conference
Country/Territory	United States
City	Charlotte
Period	6/14/22 → 6/16/22

ASJC Scopus subject areas

General Chemical Engineering
Polymers and Plastics

Cite this

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title = "DIFFUSION-SOFTENING OF CELLULOSE NANOCRYSTAL AND THERMOPLASTIC POLYURETHANE COMPOSITES",

abstract = "Smart materials that can adapt their mechanical response in the presence of an external stimuli are popular for their applications in 4D printing. Such printing methods exploit a smart material's capability to interact with these stimuli to impart controlled material deformation tailored to specific applications. A modified percolation model was formulated to predict the dynamic transition exhibited in polymer composites containing cellulose nanocrystals (CNCs) which undergo mechanical softening in the presence of water. Coupling the effects water diffusion to the degree of CNC connectivity provided a method to capture the dynamic softening of CNC-based, water responsive smart materials as a function of filler loading. This modeling approach can be implemented to develop humidity sensing actuators and water-sensitive shape memory devices.",

author = "Pritchard, {Cailean Q.} and Fallon, {Jacob J.} and Jeffrey Shelton and Bortner, {Michael J.} and Cody Weyhrich and Katherine Heifferon and Boer Liu and Long, {Timothy E.} and {Johan Foster}, E.",

year = "2022",

language = "English (US)",

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TY - CONF

T1 - DIFFUSION-SOFTENING OF CELLULOSE NANOCRYSTAL AND THERMOPLASTIC POLYURETHANE COMPOSITES

AU - Pritchard, Cailean Q.

AU - Fallon, Jacob J.

AU - Shelton, Jeffrey

AU - Bortner, Michael J.

AU - Weyhrich, Cody

AU - Heifferon, Katherine

AU - Liu, Boer

AU - Long, Timothy E.

AU - Johan Foster, E.

PY - 2022

Y1 - 2022

N2 - Smart materials that can adapt their mechanical response in the presence of an external stimuli are popular for their applications in 4D printing. Such printing methods exploit a smart material's capability to interact with these stimuli to impart controlled material deformation tailored to specific applications. A modified percolation model was formulated to predict the dynamic transition exhibited in polymer composites containing cellulose nanocrystals (CNCs) which undergo mechanical softening in the presence of water. Coupling the effects water diffusion to the degree of CNC connectivity provided a method to capture the dynamic softening of CNC-based, water responsive smart materials as a function of filler loading. This modeling approach can be implemented to develop humidity sensing actuators and water-sensitive shape memory devices.

AB - Smart materials that can adapt their mechanical response in the presence of an external stimuli are popular for their applications in 4D printing. Such printing methods exploit a smart material's capability to interact with these stimuli to impart controlled material deformation tailored to specific applications. A modified percolation model was formulated to predict the dynamic transition exhibited in polymer composites containing cellulose nanocrystals (CNCs) which undergo mechanical softening in the presence of water. Coupling the effects water diffusion to the degree of CNC connectivity provided a method to capture the dynamic softening of CNC-based, water responsive smart materials as a function of filler loading. This modeling approach can be implemented to develop humidity sensing actuators and water-sensitive shape memory devices.

UR - http://www.scopus.com/inward/record.url?scp=85146935900&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85146935900&partnerID=8YFLogxK

M3 - Paper

AN - SCOPUS:85146935900

T2 - SPE ANTEC 2022 Conference

Y2 - 14 June 2022 through 16 June 2022

ER -

DIFFUSION-SOFTENING OF CELLULOSE NANOCRYSTAL AND THERMOPLASTIC POLYURETHANE COMPOSITES

Abstract

Conference

ASJC Scopus subject areas

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