Enhancing Structural Surface Durability in Building Facades with Hyaluronic Acid Nanofiber Coatings

Ensuring the long-term durability of building facades is crucial for maintaining their structural integrity and promoting sustainability. This study aimed to explore the effectiveness of incorporating Hyaluronic Acid (HA) nanofiber-reinforced coatings as a means of enhancing facade durability. The coatings were fabricated by adding HA nanofibers, ranging from ۰-۳ wt.%, to commercially available acrylic-silicone coating substrates. Standardized techniques were employed to assess the elastic modulus, compressive strength, and impact resistance of the resulting coatings. Additionally, an Artificial Neural Network (ANN) was developed to predict these properties for new combinations of HA and facades. The inclusion of HA nanofibers had a significant concentration-dependent influence on the mechanical properties of the coatings. Increasing the HA loading led to proportional improvements in the elastic modulus, with enhancements of up to ۲۲% observed at a ۳ wt.% of HA loading. Likewise, the highest HA content resulted in an ۱۸% increase in compressive strength. The impact toughness also exhibited a progressive rise, demonstrating a ۲۹% higher energy absorption for the ۳ wt.% HA compared to the unmodified control coating. The implemented ANN demonstrated its ability to accurately capture the dose-dependent patterns and effectively predict relevant properties of compositions that were not subjected to experimental evaluation. In conclusion, the proficient dispersion of HA nanofibers emerged as a crucial factor in fortifying the facades, establishing a harmonious interplay at the nanoscale level, and ultimately augmenting their long-term resilience.

کلیدواژه ها:

Hyaluronic acid nanofibers ، Coating ، Mechanical properties ، Artificial neural network ، Nanoreinforcement