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

Ramya Kumar, Joerg Lahann

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


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 languageEnglish (US)
Pages (from-to)16595-16603
Number of pages9
JournalACS Applied Materials and Interfaces
Issue number26
StatePublished - Jul 6 2016


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

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