Can you correlate data from a stylus-type surface roughness measuring machine and a laser microscope?

Although laser microscopes are appreciated for their ability to quickly acquire data in a noncontact manner, there is a concern that the results may not correlate with data acquired using a traditional stylus-type tool. Although some differences are inevitable with when using different measurement principles, a high degree of correlation can be achieved by unifying the measurement and analysis conditions as much as possible.

The following is a comparison of data from a laser microscope and a stylus-type surface roughness measuring machine.

Figure 1 shows the raw data acquired with the laser microscope before applying the filter, and Figure 3 is the data from the stylus-type measuring machine. In the case of the stylus-type tool, a λs filter (λs=2.5 µm, in this case) is usually applied to the acquired data in advance, so the same λs filter is applied to the raw data of the laser microscope (Figure 1) for comparison.

Applying a filter of λs = 2.5 µm to Figure 1 results in the data in Figure 2.

By comparing Figure 2 and Figure 3, we can see that they match. Thus, we can deduce that by matching the measurement conditions and applying the same filter conditions, the data from the laser microscope and the stylus instrument can be correlated.

_{Sample: Rubert Roughness Standard No.504}

Figure 1. Laser (raw data): objective 20× (NA0.6)

 λs(2.5 µm) filter

Figure 2. Laser (with filter): Objective 20× (NA0.6)

Figure 3. Stylus (NA0.6)

The tip radius of a stylus is 2 to 10 µm, making it difficult to capture minute changes in roughness. And because of its size, it can be difficult for a stylus to make measurements on small areas, such as wires.

The laser used by the OLS5000 microscope, however, has only a 0.2 µm diameter, enabling it to measure fine irregularities and acquire data from small, targeted areas.

Another disadvantage of a stylus is that it requires direct contact between the probe and sample surface. For soft or delicate samples, the stylus can actually cause damage.

^{Stylus probes may damage the sample surface}

Because the laser used by the OLS5000 microscope acquires information without touching the sample, you can acquire accurate roughness measurements without  causing damage.

^{Adhesive tape 256 × 256 μm}

Although whiteness interferometers offer subnanometer-level detection sensitivity for smooth surfaces, they have several disadvantages. First, they have difficulty requiring accurate measurements of steeply inclined (rough) surfaces, making them unsuitable for many applications. Their sensors also tend to pass over weak signals, further complicating the interferometers’ ability to take accurate measurements. And while they do have an objective lens, the numerical aperture is smaller than that used on optical microscopes and has a lower horizontal resolution, making it difficult to obtain clear, live images of your sample.

The OLS5000 microscope, on the other hand, uses a laser to make measurements and has dedicated objectives with a high numerical aperture. These features enable you to obtain accurate measurements regardless of the sample’s surface, even if it’s very steep. The high-quality objectives also enable you to view your sample while capturing measurements and obtain image data while making your measurements.

Scanning probe microscopes are capable of subnanometer-level measurements, but their cantilever-based scanning system makes acquiring data a time-consuming process. Their scan area is also confined to about 100 µm, making them unsuitable to measuring large features and low magnification observation.

OLS5000 laser microscopes accomplish sub-nanometer-level measurements much more quickly. They also enable you to observe submicron irregularities using a broad field of view. The stitching function can be used to further expand the area of analysis.

Primary profile curve

The curve obtained by applying a low-pass filter with a cutoff value of λs to the primary profile measured. The surface texture parameter calculated from the primary profile is referred to as the primary profile parameter (P-parameter).

Roughness profile

The profile derived from the primary profile by suppressing the long wave component using the high-pass filter with a cutoff value of λc. The surface texture parameter calculated from the roughness profile is referred to as the roughness profile parameter (R-parameter).

Waviness profile

The profile obtained by sequential application of profile filters with cutoff values of λf and λc to the primary profile. λf cuts off the long wave component while the short wave component is cut off with filter λc. The surface texture parameter calculated from the waviness profile is referred to as the waviness profile parameter (W-parameter).

Profile filter

The filter for the isolation of the long and short wave components contained in the profile. Three types of filters are defined:

• λs filter: Filter designating the threshold between the roughness component and shorter wave components
• λc filter: Filter designating the threshold between the roughness component and waviness components
• λf filter: Filter designating the threshold between the waviness component and longer wave components

Cut-off wavelength

Threshold wavelength for profile filters. Wavelength indicating 50% transmission factor for a given amplitude.

Sampling length

The length in the direction of the X-axis used for the determination of profile characteristics.

Evaluation length

Length in the direction of the X-axis used for assessing the profile under evaluation.

^{Conceptual drawing of profile method}

Scale limited surface

The surface data are serving as the basis for the calculation of areal surface texture parameters (S-F surface or S-L surface). This is sometimes referred to as 'surface.'

Areal filter

The filter for the separation of the long and short wave components contained in the scale-limited surfaces. Three types of filters are defined according to function:

• S filter: Filter eliminates small wavelength components from scale-limited surfaces
• L filter: Filter eliminates large wavelength components from scale-limited surfaces
• F operation: Association or filter for the elimination of specific forms (spheres, cylinders, etc.)

Note: Gaussian filters are generally applied as S and L filters, and the total least square association is applied for the F operation.

Gaussian filter

A type of areal filter normally used in areal measurement. Filtration is applied by convolution based on weighting functions derived from a Gaussian function. The value of the nesting index is the wavelength of a sinusoidal profile for which 50% of the amplitude is transmitted.

Spline filter

A type of areal filter with smaller distortion in the peripheral edge when compared to the Gaussian filter.

Nesting index

The index representing the threshold wavelength for areal filters. The nesting index for the application of areal Gaussian filters are designated in terms of units of length and equivalent to the cutoff value in the profile method.

S-F surface

The surface obtained by eliminating small wavelength components using the S filter and then processed by removing certain form components using the F operation.

S-L surface

The surface obtained by eliminating small wavelength components using the S filter and then eliminating large wavelength components using L filtration.

Evaluation area

A rectangular portion of the surface designated for characteristic evaluation. The evaluation area shall be a square (if not otherwise specified).

^{Conceptual drawing of the areal method}

* Theoretical value.
** Standard value when using the OLS5000.

◎ :  Most suitable
○ :  Suitable
△ :  Acceptable depending on usage
X :  Not suitable

The functionality of the respective filters, the combination of filters, and the size of the filters used in surface feature analysis are as described below:

The filtering conditions are determined in accordance with the objectives of the analysis.

Filter functionality

In conducting surface feature parametric analysis, the application of three types of filters (F operation, S filter, and L filter) should be considered for the surface texture data acquired in accordance with the objectives of the measurement.