Aerospace & Defence

  1. Correlation of NewView Profilers to Traceable Standards

    Introduction

    Correlation to traceable certified standards is absolutely critical for any metrology tool. In an effort to show how well scanning white light interferometry (SWLI) compares to traditional methods of certifying roughness artifacts, a correlation study was performed which used three Zygo NewView profilers and four traceable roughness standards. The NewView profilers were compared by measuring several standards and calculating correlation coefficients between results and certified values. Correlation coefficients on the order of 0.999 were achieved for almost all comparisons; and differences between tools and standards were either smaller than or very close to the uncertainty of the certification. The high degree of correlation (as measured by the correlation coefficients) and small differences between the average measured values for most of the individual parameters for each tool lead to the conclusion that the NewView 5000, 6300, and 6300 with 1k camera are well correlated to each other and with traceable standards.

    Study Description

    Several versions of the NewView optical profilers measured the same parts and part locations to determine correlation. This application note will focus on roughness specimens. For additional detail as well as information on step height correlation, please refer to the supporting data for this document.

    All roughness measurements used the same 5x SLWD Michelson objective with image zoom set to 1x. The same vertical and lateral standards calibrated the PZT objective scanner and lateral coordinates in the field of view prior to making measurements. Following calibration, the part was aligned using a crosshair and then moved a defined distance (laterally) away from the initial position by using a MetroPro pattern. Software post-processed 20 SWLI (scanning white light interferometry) data sets for each instrument at similar locations for using identical acquisition and analysis settings for each measurement.

    Instrumentation

    The following NewView Profilers were used for this study:

      • NewView 5032 with analog VGA camera

     

    • NewView 6300 with standard digital VGA camera

     

    • NewView 6300 with optional digital 1k camera

    Traceable Standards

    The following standards were used for this study:

      • Halle KNT2058-01 Ra = 216 nm

     

    • Halle KNT2070-03 Ra = 23.8 nm
    • Mahr PGN-1 Ra = 566 nm

     

    • Mahr PGN-3 Ra = 820 nm

    Roughness (Ra) Correlation

    The instruments’ performance with respect to the certified Ra value for the four roughness standards was compared to the Makers’ certified measurements in two ways. The first method compared the horizontal and vertical lay data separately. The second method averaged the results from the horizontal and vertical lay tests. The standards’ certified Ra value – referred to as Maker’s Ra and Stylus Cert in the charts below – is subtracted from the measured Ra – referred to as WLI using FDA in the charts below (WLI refers to White Light Interferometry). This difference should be nominally zero. The maker’s calibration uncertainty for the certified value is shown as the Y-axis error bars around zero in the charts below.

    For each standard, there are three measurement points in the plots – one for each of the NewView instruments used in this study.

    Figure 1 - Differences - horizontal lay Ra

    Figure 1 – Differences with sample in a horizontal orientation

    Figure 2 - Differences - verticallay Ra

    Figure 2 - Differences with sample in vertical orientation

    Figure 1 - Differences - averaged lay Ra

    Figure 3 - Differences with horizontal and vertical readings averaged

    It can be seen that in the horizontal orientation, all the differences are quite close to the makers’ uncertainties. In the vertical lay orientation, there is an obvious outlier on the high side of the sinusoidal standards. This outlier is explained by the footnote¹ below.

    Finally, when the lay data are averaged together and differenced from the certified values, we see very close agreement with the Makers’ uncertainties on all standards.

    Observations and Conclusion

    For the Halle standards, the parameter of particular interest is the Ra parameter which did measure within the uncertainty of the standard for all tools. The same can be said for Ra and Rz on the Mahr standards.

    The high degree of correlation (as measured by the correlation coefficients) and small differences between the average measured values for most of the individual parameters for each tool lead to the conclusion that the NewView 5000, 6300, and 6300 with 1k camera are well correlated to each other and with traceable standards.

    footnote¹ This is the NV 5000 data which experiences data dropout due to the use of an analog camera when the lay is vertical. This dropout cannot be corrected. The NV6000 is an all digital system whose data does not suffer this data dropout, and its data is very similar to the data seen in the horizontal lay plot.

    To speak with a Sales & Applications Engineer please call 01582 764334 or click here to email.
  2. Measuring Sub-Angstrom Surface Texture

    Introduction

    The application of measuring surface texture with a white light optical profiler has been well-known for many years. As the capabilities of optical manufacturing and precision machining increase, the production of ‘super smooth’ or ‘sub-angstrom’ surfaces has become more common, and quantification of these surfaces is critical for effective process control. The NewView™ 6000 series of optical profilers using Scanning White Light Interferometry (SWLI) with MetroPro™ software and patented FDA analysis enable rather straightforward quantification of surfaces with texture measured on the order of fractions of a nanometer. With good control over the measurement environment, proper selection of measurement parameters, and effective instrument calibration, quantification of surfaces with roughness measured in tens of picometers (1x10-12 m) is possible. With the NewView 6300’s best-in-class acquisition speed and resolution, areal measurement of supersmooth surface texture has never been so easy.

    Understanding System Noise

    The first step required in making quantitative measurements of super smooth surfaces is to understand that every measurement system has an inherent baseline system noise. This noise results from a number of factors including electronic noise, sensor noise, small irregularities in the reference surface, and small vibrations caused by changes in the measurement environment. For most samples, the measurement noise in the NewView can be essentially ignored, as the measurement value is much larger than the noise floor. However for very smooth samples, this is not the case. For these samples it is important to understand the noise sources and to control them as tightly as possible. Many sources of noise can be virtually eliminated or at least significantly reduced by both tightly controlling the measurement environment (acoustics, air currents, temperature, etc.) and also by performing a number of measurements and averaging them together into a single data file.

    Environmental Controls 
    The first task in setting up measurements for a super smoothpart is establishing control over the measurement environment. The ideal environment would be one which:

      • is mechanically and acoustically quiet to minimize part vibrations;

     

    • has tight temperature control to minimize sample and objective changes during the measurement period;
    • has well controlled airflow to minimize air currents between the microscope and the part.

     

    In order of importance, vibration, noise, and temperature rank at the top. When the objective working distance is small, airflow control may essentially be a non-issue after mechanics, acoustics, and temperature have been addressed. With long working distance objectives, however, air currents will be more critical to control.

    Measuring the System Merit Function 
    ZYGO has developed a process for quantifying the expected system noise as a function of measurement averages which we will call the System Merit Function (refer to the last page of this document for an illustration of this measurement method). The measurement process involves acquiring a number of measurements—typically 10 or more—with a given number of averages. Each of these data files are saved as D1, D2,…Di. These data are averaged together into one single file, Dse which represents the total system error during the measurement period. This Dse file is then subtracted from each of the component Di files to create an error map indicative of the expected system noise for a single measurement. The rms of the individual difference maps are recorded, and the mean and standard deviation are calculated for the series of differences. By adding twice the standard deviation of the series to the average rms of the series, the expected system noise for a given number of measurement averages can be estimated with good confidence. This process can be automated by using standard MetroPro and some very simple MetroScripting. An example application is available upon request from ZYGO.

    Predicting System Noise 

    Once the value of the System Merit Function for measurements with no averaging is known, the predicted system noise for a specific number of averages can be predicted using the formula.

    where SN1 is the system merit value measured with no measurement averages and AVG is the desired number of averages. For larger numbers of averages taking a longer time period to measure (typically greater than 32 measurements) this prediction can only hold true in very well controlled environments. For critical applications, it is recommended to test the measured noise floor against the predicted value and ensure that the environment is controlled well enough – morewell-controlled environments will generally require fewer averages. In the event that the environment is not satisfactory, the line for the measured values in Figure 1 will typically turn upward again and diverge from the predicted values. If a noise floor associated with averages beyond the upturn point were desired, it would be necessary to further improve the environment.

    Figure 1.

    Figure 1 –Excellent correlation is observed between predicted and actual system noise on the NewView 6300

    Phase Res - Which Level?

    Depending upon the smoothness of the surface to be measured, it may be necessary to increase the internal precision of the calculations made by the MetroPro software. Starting with version 8.1.1, MetroPro allows for three levels of precision with the Phase Res Measurement Control—Normal, High, and Super.Normal is the lowest resolution—useful primarily for large steps and rough surfaces. High is the standard setting for most typical measurement situations using scans up to 150µm and texture down to approximately 0.050 nm. The newest and highest precision setting, Super, enables measurement of very smooth surfaces using a large number of averages. Only very smooth surfaces will require the use of Super. This should be taken into consideration when determining baseline system noise.

    What Noise Floor do I Need?

    There is no one right way of selecting the number of averages (and by extension, the noise floor) for a particular application. For rougher surfaces, where the surface is measured in tens of nanometers or more, striving for a system noise on the order of 10x lower is often recommended. However for a surface which is on the order of 0.05 nm (0.5 Å) achieving a noise floor 10 times lower would theoretically require approximately 3000 averages! Rather than a hard and fast rule, a more empirical rule of thumb employed by ZYGO is that the lowest practical noise floor for an application is recommended, but that system noise should be at least 2 to 4 times smaller than the desired measurement surface features.

    System Error Characterization

    After determining the phase resolution and the number of averages required for the desired noise floor, it is recommended that the user perform a system error characterization. This process entails measuring a number of physical locations on an optical grade flat using the desired number of averages per site. 
    Typically, at least 8 distinct sites with no overlapping regions are recommended for generation of a system error file. For specific information and procedures for creating a system error file, please refer to the NewView MetroPro Microscope Application Booklet, OMP-0360 or Section 8, MetroPro Reference Guide, OMP-0347. The error map created will then be subtracted from each of the surface measurements made on the actual sample.

    Figure 2

    Figure 2 - A graphical representation for the process of measuring the System Merit Function


    Conclusion

    Using the methods and procedures described here, ZYGO has demonstrated the capability of measuring surfaces smoother than 0.05 nm. Tightly controlling the measurement environment, selecting an appropriate internal precision, and choosing the number of phase averages based on the System Merit Value all combine to provide the highest quality surface texture measurements available from an optical profiler.

    To speak with a Sales & Applications Engineer please call 01582 764334 or click here to email.

2 Item(s)