Computational design and analysis of multi-scale polymer machines

Perlitz, Daniel

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https://hdl.handle.net/2142/49676 Copy

Description

Title

Computational design and analysis of multi-scale polymer machines

Author(s)

Perlitz, Daniel

Issue Date

2014-05-30T17:04:14Z

Director of Research (if dissertation) or Advisor (if thesis)

Hsia, K. Jimmy

Department of Study

Mechanical Sci & Engineering

Discipline

Mechanical Engineering

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

M.S.

Degree Level

Thesis

Keyword(s)

• Self Assembly
• Finite Element
• Polymer Mechanics
• Limit Point Buckling

Abstract

This thesis discusses the computational analysis of multi-scale polymer systems for a variety of applications. Two geometries are analyzed, polymer sheets that fold into complex shapes due to a gradient in cross-linking throughout its volume, and a dome structure that experiences limit point buckling during inversion. The first chapter of this work discusses an analysis of the self-assembly of thin, programmable Polydimethylsiloxane (PDMS)/SU-8 sheets, which fold due to complex swelling ratio gradients throughout their volume. These could be used as a fabrication technique for small polymer devices or as a means of actuation in a polymer machine. An analytical elasticity model and a computational model in ABAQUS/Standard are used to predict the direction of folding for different sheet specimens. The model is also used to analyze specimens with more complex time varying deformations. Next a dome structure is investigated for its potential use as the scaffold of a biomechanical machine powered by cells. The machines are millimeter sized and are actuated by groups of cells cultured on the machine. These biological machines have important potential applications for drug delivery or chemical sensing. Finite element analysis is used to study these domes so that an optimal biological machine can be designed.

Graduation Semester

2014-05

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http://hdl.handle.net/2142/49676

Copyright and License Information

Copyright 2014 Daniel Perlitz. Selected figures and data Copyright 2014 Peixi Yuan. Copyright 2014 Elsevier Limited.

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