Antifouling Stainless Steel Surface: Competition between Roughness and Surface Energy

Abstract

To increase the shelf-life qualities of dairy products, a heat treatment is usually done. However, heat treatments induce physico-chemical modifications of the products. Some of them lead to the expected product but an unwanted consequence of this process is the formation of a fouling deposit on the surfaces in contact with the processed fluid. To eliminate fouling, cleaning processes have to be done once a day. It increases the processing and maintenance costs. To control and to decrease the fouling are the main problems in food industries and an active research is carried out on efficient antifouling surface treatments. In the present study, a 316L 2B stainless steel was submitted to different surface treatments (Flame and plasma pre-treatments, Plasma Enhanced Chemical Vapour Deposition, hydrophobic coatings, mechanical polishing ...) to try to establish correlations between different surface parameters (roughness, hydrophobicity, nanostructuration, surface energy, ...) onto the fouling in heat exchangers. All the treated plates were then submitted to a fouling test using an aqueous solution of β-lactoglobulin at 1% (p/p) with a final calcium concentration of 910 mg/L and compared to a bare steel plate. The results obtained imply different influences of each parameter depending on the surface roughness: the effect of a non organized micrometric roughness is preponderant compared to the surface energy: the fouling comes from a mechanical effect mainly due to rubbing. However, when the surface is nanostructured, fouling decreases. When the roughness reaches the nanometer scale (between 100 and 400 nm), it is the surface energy and the polar/apolar components which become preponderant compared to the roughness. Fouling is this time mainly due to the hydrophilicity of the surface and to the adsorption of the β-lactoglobulin on acido-basic sites. Finally, when the roughness reaches less than 50 nm, polar/apolar components show no effect anymore, the preponderant parameter is the hydrophobicity of the surface.

A critical review on surface modifications mitigating dairy fouling

“…On the contrary, rough surfaces favour prevail the attachment of native (1-10 nm; Boxler, 2014) and denatured whey proteins (50-60 nm; Jimenez et al, 2013) as well as calcium and phosphate clusters (1 nm; Boxler, 2014), as depicted in Figure 10. Jimenez et al (2012) confirmed the latter hypothesis by observing calcium deposit at the grain boundary, leading to an increase in dairy fouling.…”

“…In food industries, surfaces should present R a < 0.8 μm (Verran & Redfern, 2016). Nevertheless, works exhibit the effectiveness of smoother coatings for mitigating dairy fouling and cleaning, ranging from 0.02 to 0.5 μm (Gordon et al, 1968;Jimenez et al, 2012;Piepiórka Stepuk et al, 2016;. But AFM probes relatively small areas.…”

Surface-water Interface Induces Conformational Changes Critical for Protein Adsorption: Implications for Monolayer Formation of EAS Hydrophobin

“…We also examine the behavior of water at the protein-silica interface, specifically the role of water bridged interactions that promote protein adhesion to the surface. These interfaces are prominent in both biomedical and industrial environments (Jimenez et al, 2012 ; Kobayashi et al, 2012 ; Puddu and Perry, 2014 ) and understanding the behavior and interactions in these systems at the nanoscale (Patel et al, 2012 ; Treuel and Nienhaus, 2012 ; Yiapanis et al, 2012 ) will be critical for the rational design of anti-fouling surfaces.…”

Understanding stickiness in sugar‐rich food systems: A review of mechanisms, analyses, and solutions of adhesion

“…For instance, the water contact angle on a relatively flat printer paper was on average 57 • , whereas that on more porous filter paper was only 15 • , corresponding to higher surface energy (Carvalho et al, 2005;Wang & Hartel, 2021a). It was found that surface irregularities multiplied the chance of soiling and fouling of milk (Jimenez et al, 2012;Joanna et al, 2016), yogurt (Leclercq-Perlat & Lalande, 1994, oils, and emulsions to processing surfaces, resulting in reduced cleanability. Roughness can be characterized through optical, laser, and force-based tech-niques, expressed in average roughness (R a ), root-meansquare (RMS or R q ), or others.…”