Quantitative in-situ measurement of fouling processes

Abstract

The search for non-toxic alternatives as anti-fouling coatings for the marine environment includes screening of new chemical compounds. Of key relevance are analytical methods to quantitatively determine fouling-retention and fouling-release properties of coating candidates as feedback for material developers. We develop and apply microfluidic adhesion tests to assess attachment of fouling organisms to new materials. To understand the relevance of the obtained laboratory data, they will be compared against dynamic field tests. The fouling populations will be analyzed by deep learning and new online-monitoring systems. For both, laboratory and field tests, kinetic models will be developed that enable the analysis of fouling progression. These kinetic models will allow to shed light on the mechanism and the thermodynamic driving forces for attachment. As the field experiments are done under comparable shear stress conditions as the laboratory experiments, the validity of the kinetic models will be explored and if necessary refined. As silt accumulation was found to be a critical problem in the field tests challenging predominantly hydrophilic coatings, a silt accumulation assay in the laboratory will be established that allows to characterize the susceptibility of coating prototypes towards sediment adsorption and thus to the associated failure in the field tests. While self-assembled monolayers are used whenever benchmark coatings are demanded, different polymers that form thin, hydrophilic layers or domains and thus hydration layers on the surface will be studied in detail.

Document Details

Document Type
DoD Grant Award
Publication Date
Apr 29, 2020
Source ID
N000142012244

Entities

People

  • Axel Rosenhahn

Organizations

  • Office of Naval Research
  • Ruhr University Bochum
  • United States Navy

Tags

Readers

  • Computational Fluid Dynamics (CFD)
  • Surface Engineering/Surface Coating Technology.
  • Underwater engineering and Marine Technology.

Technology Areas

  • AI & ML