Modeling bacterial adhesion onto nanostructured silicon carbide using a new physicochemical approach: Statistical...

Area of Science:

• Materials Science
• Biophysics
• Surface Chemistry

Background:

• Bacterial adhesion on ceramic materials is critical for water nanofiltration.
• Extended DLVO theory is the current standard for analyzing adhesion.
• An alternative theoretical framework is needed for detailed characterization.

Purpose of the Study:

• To apply statistical physics formalism to model bacterial adhesion.
• To quantitatively and qualitatively describe Pseudomonas putida (P.putida) adhesion on silicon carbide (SiC) micro- and nanostructures.
• To characterize adhesion stereography, energy, and thermodynamics at varying pH.

Main Methods:

• Modeling experimental adsorption isotherms using statistical physics.
• Utilizing the Hill model for bacterial adsorption analysis.
• Thermodynamic analysis of the adhesion process.

Main Results:

• P.putida exhibits multicellular, perpendicular adhesion on SiC nanofibers (NFSiC) and nanorods (NRSiC), influenced by pH.
• Adhesion on microscale SiC (µmSiC) is parallel across all pH.
• Adsorption capacity is higher on NRSiC and NFSiC, indicating strong chemical adsorption (> -187 kJ/mol) and exothermic, pH-dependent processes.

Conclusions:

• Statistical physics provides a robust alternative to DLVO theory for bacterial adhesion studies.
• SiC nanostructures demonstrate significantly stronger P.putida adhesion (∼95 kT) than µmSiC (∼80 kT).
• Adhesion is a strong chemical process, exothermic and sensitive to pH, particularly on nanostructured surfaces.