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High-Throughput Multiobjective Optimization of Patterned Multifunctional Surfaces.

Nourin Alsharif1, Joshua R Uzarski2, Timothy J Lawton2

  • 1Department of Mechanical Engineering, Boston University, Boston, Massachusetts 02215, United States.

ACS Applied Materials & Interfaces
|June 20, 2020
PubMed
Summary
This summary is machine-generated.

This study introduces a high-throughput method for creating multifunctional surfaces. The approach allows independent optimization of enzyme activity and water repellency by controlling pattern geometry.

Keywords:
enzyme immobilizationhigh-throughput experimentationmultifunctional surfacesmultiobjective optimizationsurface patterning

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Area of Science:

  • Materials Science
  • Surface Chemistry
  • Biomaterials

Background:

  • Developing multifunctional materials with competing properties (e.g., enzymatic activity and hydrophobicity) is challenging.
  • Surface patterning offers a route to multifunctionality, but optimization is hindered by numerous pattern permutations.
  • Existing methods lack the throughput to efficiently explore diverse patterned surface designs.

Purpose of the Study:

  • To develop a high-throughput platform for exploring and optimizing patterned multifunctional surfaces.
  • To decouple the control of enzymatic activity and wetting behavior on engineered surfaces.
  • To enable efficient multiobjective optimization of complex surface functionalities.

Main Methods:

  • A microtiter plate-inspired architecture was adapted for high-throughput surface patterning.
  • Horseradish peroxidase (HRP) was patterned onto hydrophobic fluorinated self-assembled monolayers.
  • Enzyme activity and water-repellent roll-off behavior were systematically measured across various pattern geometries.

Main Results:

  • Enzyme activity was found to be solely dependent on surface coverage.
  • Surface wetting behavior (roll-off angle) was strongly influenced by pattern geometry parameters.
  • Crucially, wetting properties could be tuned independently of enzymatic activity.

Conclusions:

  • The developed high-throughput platform enables efficient exploration of multifunctional surfaces.
  • Independent control over distinct surface properties like enzymatic activity and wettability is achievable.
  • This approach facilitates general and flexible multiobjective optimization for advanced material design.