Paint panles layer thickness and particle sizing

Applied Research & Photonics
470 Friendship Road, Suite 10
Harrisburg, PA 17111, USA
Phone: +1-717-220-1003

http://arphotonics.net
Email: info@arphotonics.net

Paint thickness characterization of different layers and particle sizing
Five panels were received. These panels have different primer and paint layers
as well as clear over coats. The objective is to demonstrate the capabilities of
ARP’s terahertz nano-scanner for accurate characterization of the thicknesses
of different layers of the paint panels. In addition, the particle size of the
additives was also graphically characterized by 3D imaging.
Fig. 1 shows a schematic of the measurement system. The X-, Y-, and Z- axis
allows scanning in 3 dimensions. In addition, a -axis is available for scanning
conformal surfaces. Travel length and resolution of all axes are adjustable to
accommodate different sample shapes and sizes. Samples in solid, liquid and
gaseous forms may be measured. The schematic in Fig. 1 is for the samples to
be scanned while the source and detection system remain stationary. However,
a configuration is also available where the specimen remains stationary while
the source moves for scanning.
The standoff distance for both the reflected and transmitted beams may be
adjusted to accommodate for application as an on line quality assurance tester.

Fig. 1. Schematic diagram of the scanner.

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Fig. 2 shows the resolution of the scanner at a moderate speed. As seen from
Fig. 2, the resolution is ~27 nm. A higher resolution may also be achieved,
however, the current resolution is sufficient for accurate characterization of the
current paint panels for different layers. For particle size characterization,
resolution may be tuned down to a few nanometers.

Fig. 2. Data showing the resolution of the scanning system. The noise floor
is on the order of 103 counts, thus the signal is strong and clear.

Paint layer thickness characterization
In the following, the measured data for the individual panels are presented.
The thickness modeling from the reflectance measurement has been
demonstrated for one (Red panel) as an example. Similar analysis can be done
for all panels.
Fig. 3 shows a photograph of the sample “Red panel.” Layers 1, 2, 3, & 4 are
described in Table 1. The supplied thicknesses were used as the calibration for
calculating each layer’s measured thickness. However, a fine scale calibration

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of each layer of paints (or primer or overcoat, etc.) is important for a finer scale
measurement. Such a scheme is is available in the commercial version of
ARP’s terahertz scanner.

Red Panel
(contains mica flakes)

Table 1. Red Panel
Layer# Description Thick (µm) Cumulative (µm)
1
No label
0
0
2
Primer
15.24
15.24
3
Basecoat
16.37
31.61
4
Clear coat
64.35
95.96

4

3

2

1

102 mm

10 mm

Fig. 3. Photograph of the Red Panel. Layers are marked 1, 2, 3 & 4 as described
in the Table above. The arrow shows the scanning direction. Scan length is 92
mm as shown in the X scale (see Fig. 4).

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Fig. 4. Scanning traces (left Y-axis) and calculated thicknesses (right Yaxis) of different layers. The blue, red and green curves are the traces
from different trials. They overlap on each other, indicating accurate
reproducibility of the measurement system. The layer boundary is
indicated by a sudden change in the reflectance (up and down spikes on
the blue curve). The thickness was calculated based on the known
thicknesses of different layers in Table 1. The spikes were excluded from
thickness calculation.

As seen from Fig. 4, all four layers exhibit different reflectance with
clearly identifiable boundary for each layer. The final layer of paint being
composed of all 4 layers, exhibit higher reflectance. Estimated average
thickness of layer 4 is ~95 µm, while that of layer 3 is ~32 µm. This gives a
thickness for the overcoat layer ~63 µm. Similarly, the thickness of the paint
layer (layer 2) is ~16 µm. The observed fluctuation in the layer 4 thickness is
not necessary indicative or measure of the paint layer roughness. This

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fluctuation may occur from several factors. However, most likely contributing
factor being the surface roughness of the substrate on which the layers were
deposited. As such the roughness of the substrate must be characterized
before putting the primer and paint layers. Such calibration may be used as
the reference for subsequent layer’s thickness measurements.
Particle size characterization
An attempt was made to characterize the particle size of mica flakes
within the paint. Fig. 5 shows a 3D surface plot of a small area on the Red
panel while Fig. 6 shows a contour plot of the same area. The surface texture
in Fig. 5 is presumed due to the mica flake particles. In view of the smallest
contours in Fig. 6, it may be surmised that there is size distribution of the mica
particles embedded in the paint. The smallest particles may be estimated to be
a few microns. A quantitative analysis may be conducted to determine the size
distribution.

Fig. 5. Surface plot of the Red Panel over 250 µm x 225 µm area

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Fig. 6. Contour plot of the same area as in Fig. 5. Smallest contour size may
be assigned to the particle size after a size calibration is conducted.

Figs. 7 through 14 respectively exhibit a photograph followed by scanning data
of the rest of the 4 panels. Analyses similar to the red panel may be conducted
for all of these panels.
Conclusions
It has been demonstrated that ARP’s terahertz nano-scanner may be used for
non-destructive, non-invasive, and non-contact measurement of paint layer
thicknesses and the embedded particle size estimation. The remote
measurement system may be implemented for auto body paint quality
inspection at the production line as well as for various paint related research
and development.
Contact
For more information please contact:
Anis Rahman, PhD
Phone: 717-623-8201
Email: a.rahman@arphotonics.net

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Paint panles layer thickness and particle sizing

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Paint panles layer thickness and particle sizing