Predictive Model for the Design of Zwitterionic Polymer Brushes: A Statistical Design of Experiments Approach

Ramya Kumar; Joerg Lahann

doi:10.1021/acsami.6b04370

Predictive Model for the Design of Zwitterionic Polymer Brushes: A Statistical Design of Experiments Approach

Ramya Kumar, Joerg Lahann

Chemistry (Twin Cities)

Research output: Contribution to journal › Article › peer-review

11 Scopus citations

Abstract

The performance of polymer interfaces in biology is governed by a wide spectrum of interfacial properties. With the ultimate goal of identifying design parameters for stem cell culture coatings, we developed a statistical model that describes the dependence of brush properties on surface-initiated polymerization (SIP) parameters. Employing a design of experiments (DOE) approach, we identified operating boundaries within which four gel architecture regimes can be realized, including a new regime of associated brushes in thin films. Our statistical model can accurately predict the brush thickness and the degree of intermolecular association of poly[{2-(methacryloyloxy) ethyl} dimethyl-(3-sulfopropyl) ammonium hydroxide] (PMEDSAH), a previously reported synthetic substrate for feeder-free and xeno-free culture of human embryonic stem cells. DOE-based multifunctional predictions offer a powerful quantitative framework for designing polymer interfaces. For example, model predictions can be used to decrease the critical thickness at which the wettability transition occurs by simply increasing the catalyst quantity from 1 to 3 mol %.

Original language	English (US)
Pages (from-to)	16595-16603
Number of pages	9
Journal	ACS Applied Materials and Interfaces
Volume	8
Issue number	26
DOIs	https://doi.org/10.1021/acsami.6b04370
State	Published - Jul 6 2016

Bibliographical note

Funding Information:
We acknowledge the Defense Threat Reduction Agency (DTRA) for funding provided through Grant HDTRA1-12-1- 0039 as a part of the interfacial dynamics and reactivity program. We further acknowledge support from the Army Research Office (ARO) under rant W911NF-11-1-0251. We thank Prof. Anish Tuteja for access to the contact angleoniometer. Prof. Vijay Nair is gratefully acknowledged for sharing his valuable insights on statistical modeling.

Publisher Copyright:
© 2016 American Chemical Society.

Keywords

PMEDSAH
response surface methodology
stem cell culture
surface-initiated atom transfer radical polymerization
zwitterionic self-association

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abstract = "The performance of polymer interfaces in biology is governed by a wide spectrum of interfacial properties. With the ultimate goal of identifying design parameters for stem cell culture coatings, we developed a statistical model that describes the dependence of brush properties on surface-initiated polymerization (SIP) parameters. Employing a design of experiments (DOE) approach, we identified operating boundaries within which four gel architecture regimes can be realized, including a new regime of associated brushes in thin films. Our statistical model can accurately predict the brush thickness and the degree of intermolecular association of poly[{2-(methacryloyloxy) ethyl} dimethyl-(3-sulfopropyl) ammonium hydroxide] (PMEDSAH), a previously reported synthetic substrate for feeder-free and xeno-free culture of human embryonic stem cells. DOE-based multifunctional predictions offer a powerful quantitative framework for designing polymer interfaces. For example, model predictions can be used to decrease the critical thickness at which the wettability transition occurs by simply increasing the catalyst quantity from 1 to 3 mol %.",

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note = "Funding Information: We acknowledge the Defense Threat Reduction Agency (DTRA) for funding provided through Grant HDTRA1-12-1- 0039 as a part of the interfacial dynamics and reactivity program. We further acknowledge support from the Army Research Office (ARO) under rant W911NF-11-1-0251. We thank Prof. Anish Tuteja for access to the contact angleoniometer. Prof. Vijay Nair is gratefully acknowledged for sharing his valuable insights on statistical modeling. Publisher Copyright: {\textcopyright} 2016 American Chemical Society.",

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Predictive Model for the Design of Zwitterionic Polymer Brushes: A Statistical Design of Experiments Approach

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