Laboratory screening of coating libraries for algal adhesion

Area of Science:

• Materials Science
• Marine Biology
• Image Analysis

Background:

• Combinatorial chemistry generates large coating libraries for antifouling applications.
• Existing algal biomass quantification methods are not suitable for array formats.
• Developing efficient screening tools for fouling-release coatings is crucial.

Purpose of the Study:

• To develop and validate an algorithm for quantifying algal coverage on coated surfaces from digital images.
• To enable rapid down-selection of coatings with fouling-release properties.
• To assess the antifouling performance of siloxane-polyurethane coatings against Ulva biofilms.

Main Methods:

• A probability distribution-based algorithm was developed to quantify surface area covered by green algae from digital images.
• Combinatorial chemistry was used to create 12 siloxane-polyurethane coating formulations on aluminum panels.
• Automated water jetting was employed to assess the ease of biofilm removal, followed by image analysis for coverage quantification.

Main Results:

• The developed algorithm accurately quantifies algal coverage from digital images.
• Siloxane-polyurethane coatings demonstrated varying degrees of fouling-release properties.
• Biofilm coverage post-jetting correlated with coating composition, allowing for performance assessment.

Conclusions:

• The image analysis algorithm provides a robust method for quantifying algal biomass in array formats.
• This approach facilitates the efficient screening and selection of novel fouling-release coatings.
• Coating composition significantly influences the performance of antifouling surfaces against Ulva biofilms.