Increasing the Durability of Paint and Varnish Coatings in Building Products and Construction

By Loganina Valentina Ivanovna

Increasing the Durability of Paint and Varnish Coatings in Building Products and Construction presents data and analysis on regularities in the appearance quality of protective and decorative coatings for building products and structures, also detailing the relationship between the resistance of coatings and the quality of their appearance. Developing a method for ensuring the quality of painted surfaces for building products and developing control methods is an important scientific, technical and economic problem. The conditions needed depend largely on the rheological properties of paint and the processes of wetting and application, with different variables for metal or concrete structures.

• Presents data and methodological developments that increase the service-life of protective and decorative coatings
• Details regularities in the appearance quality of protective and decorative coatings
• Covers the relationship between coating resistance and appearance quality
• Develops methods for ensuring the quality of painted surfaces
• Considers the different variables for the application of paint to various surfaces of building products and structures

• Language: English
• Publisher: Elsevier Science
• Release date: Mar 15, 2019
• ISBN: 9780128170472

Loganina Valentina Ivanovna

Loganina Valentina Ivanovna is Doctor of Technical Sciences, Professor, and Head of quality control and construction technologies at Penza State University of Architecture in Russia. Her research interests include the development of finishing materials composition, and the forecasting of their durability. The author has published widley, has 70 patents, and and has supervised numerous dissertations and research projects.

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1

Regularities for formation of the quality of the external appearance of coatings

Abstract

This chapter covers the results of evaluation of coatings on a cement substrate. The regularities of the formation of the quality of coatings are described. A model for assessing the quality of coatings on a cement substrate is proposed.

Keywords

Coatings; appearance quality; regularities of formation of quality; quality model

1.1 Evaluation of the quality of the appearance of paint and varnish coatings

Coatings for finishing facades with aesthetic protective functions must have a high-quality appearance. The quality of appearance refers to the presence of defects (inclusions, streaks, shagreen, strokes and scratches, waviness, variability) paintwork. The presence of defects on the surface of the paintwork determines the quality of appearance.

According to GOST 9.032-74 Unified system of protection against corrosion and aging for coatings for paint and varnish, groups, technical requirements and designations, there are seven classes of the quality of the appearance of coatings on a metal substrate defined as follows:

I class—no defects can be allowed for high-gloss, glossy, semi-glossy and semi-matt. For matt coatings not more than 4 inclusions per m²;

II–VII classes—are possible weed or individual inclusions, taking into account their number (pcs/m²) depending on the length, width, diameter of the defect and the distance between them (mm), as well as risks and hatch.

In addition to the above defects, the quality classes III–YII include waviness, Y–YII streaks, and IY–YII offshade.

In Refs. [1,2], the quality of the appearance of protective-decorative coatings for cement concrete are evaluate IV–VII classes (Table 1.1).

Table 1.1

As noted earlier, the surface quality of the paintwork is also determined by its roughness, that is, its surface profile. Methods involving fractal physics can be used to estimate the coating surface profile. The fractal dimension index D of the coating surface profile ranges between 1<D<2 [3–6]. The greater the roughness of the coating, the more curved the coating profile and the greater the value of D. Thus, the fractal dimension D of the coating profile can serve as a criterion of its appearance quality, reflecting the presence of inclusions, streaks, and waviness.

In this chapter, we have attempted to evaluate the possibility of describing the coating surface quality using fractal dimension.

The paints were applied with a brush onto a mortar substrate in two layers with 24-hour intermediate drying. The coating profile was determined with a profile meter A1. The length of the coating surface profile was determined with a perambulator.

In addition, the coating surface quality was estimated with a gloss meter FB-2. The fractal dimension D of the coating surface profile was estimated using the geometrical method. For this purpose the image of the curve obtained by using a profile meter profilograph was covered by a grid consisting of squares with side L1. Then the number of the squares N curve N (L1) went through were counted. After changing the grid scale, we recounted the number of squares intersecting curve N (L2), N (L3) N (Ln). Then, in a log–log grid we plotted N (L), according to the inclination angle of which we determined the fractal dimension.

Table 1.2 shows the results of the coating surface quality estimation that was carried out in accordance with GOST 9.407-74 using the fractal dimension of the coating surface profile.

Table 1.2

As can be seen, there is a correlation between the coating surface roughness and the appearance quality class. As the surface roughness increases the appearance quality class decreases and the fractal dimension D increases.

For example, the coating surface profile fractal dimension based on PF-115 with a coating surface roughness and appearance quality class of 0.2 m and Y is D=1.17, while with the coating surface roughness and the appearance quality class, it is 0.75 mkm and YI is D=1.35. Similar patterns were seen for other types of coatings.

Changes in the gloss and coating surface profile parameters on the sample were equal to 10 cm also prove the fact. When the coating surface profile fractal dimension increases, the gloss decreases and the numerical values of the profile perimeter increase.

The correlation between the length L of the coating surface profile on the sample length l and the fractal dimension D can be approximated as

(1.1)

where b is a constant factor.

In particular, for the coatings based on paint PF-115 the expression (1.1) is

For paint MA-15-based coating

For paint NC-based coating

For acrylic paint-based coating

For water-dispersible façade paint-based coating

The results of the research suggest that at the fractal dimension D, equal D=1–1.09, quality class is IY, at D=1.1–1.2 the coating appearance quality class is Y, when D=1.21–1.4—YI, and at D=1.41–1.99—YII.

When applying the integral performance index to the coatings appearance fractal dimensions help estimate paint coatings quality more objectively.

1.2 Quality of the appearance of paint and varnish coatings

Research has shown that the quality of the appearance of coatings is determined by the nature of the bottling of the paint. In accordance with [7] bottling is considered as a rheological process, which can be described by the following expression:

(1.2)

where h is the stroke height

b is the width of stroke

f is the shift limit stress of the paint

σ is the surface tension of the paint

The following procedure was used to determine the paint’s ability to flow on the surface of the substrate (applied by a brush). Five pairs of parallel strips of material were applied and the degree of spreading over the number of merged bands was determined. The strips were made with a special device. Estimation of the degree of spreading of the five pairs of parallel strips was determined using a 10-point scale.

To assess the spreading of paint a technique based on the determination of the surface profile of the coating was used. The following paints were used in the work: alkyd grade enamel PF-115, oil paint MA-15, enamel nitrocellulose paint of grade NC-123, acrylate paint class universal, and acrylic water-dispersion (facade).

The paints were applied on the cement substrates in two layers using a brush with intermediate drying within 24 hours. The surface tension of the paint composition was determined by the drop method (stalagmometric method). From a special capillary—a stalagmometer—the same volumes of water and the test liquid or solution are squeezed out. The number of drops formed from the same volume of liquid is proportional to the density of this liquid and inversely proportional to its surface tension.

The value of the surface tension of paint was calculated from the formula

(1.3)

was used as the reference liquid.

is brought to the surface and lowered (without a push). As soon as the movement of the ball becomes uniform, the electric second-timer is turned on and the travel time t of the ball is determined. The viscosity of the liquid is given by the formula:

(1.4)

where g is the acceleration of gravity m/s²

t is the time during which the ball passes the distance between the marks A and B, s

l is the distance between the marks A and B, cm

is the density of the ball and paint, g/cm³, respectively

The substrates were made of glass and cement-sand mortar. The results of the studies are given in Table 1.3. Analysis of the data (Table 1.3) indicates that there is some slowing down of the time of restoration of the structure of paint when applied to the porous surface of the solution. For example, on a glass substrate, the time for restoring the structure of the PF-115 paint composition is 3 minutes, and on the cement substrate it is 5 minutes, and filling in both cases is satisfactory. Undoubtedly, the time to restore the structure of the paint composition depends both on the porosity of the substrate and on the rheological properties of the paint.

Table 1.3