Thomas Rinder

Investigations of smooth surfaces by measuring the BRDF with a stray light sensor in comparison with PSD curves evaluated from topography of large AFM scans

For quality inspection of polished surfaces as applied in semiconductor and optical industry, various methods are used for a fast detection of microroughness, defects, and contaminations. With the aid of stray light sensors the intensity distribution of the reflected and scattered light, i.e. the BRDF, is measured. The probability distribution of values of a BRDF is parametrized to obtain a measure for roughness and for classes of defects. There is still need for justifying the choice of statistical moments to characterize and finally to classify different surfaces. Of course, a basic quantitative, i.e. metrological understanding of stray light sensors is necessary. The power spectrum of surface topographies sufficiently smooth to obey Rayleigh-Rice approximation is proportional to the BRDF. Therefore a comparison was only carried out with sample surfaces obeying this approximation. Defects and contaminations with lateral sizes smaller than the wavelength of the illuminating light employed in the stray light sensor, however, could not be analyzed within this investigation. We have measured the topography of large areas up to 600 micrometer X 100 micrometer with an AFM by patching several scans (up to 8) with overlap. BRDFs evaluated from AFM measurements agree well with BRDFs measured with a stray light sensor.

Characterization of surfaces using neural pattern recognition methods based on BRDF and AFM measurements

A major problem of in-situ surface characterization by using angle-resolved light scattering is the fast and accurate surface parameter identification. This paper will deal with surface parameter identification methods from BRDF measurements of rough surfaces with stochastical height topographies. First, neural classification methods will be discussed. Second, the discussed classification method will be applied to BRDF data taken by an ARS silicon sensor with 8013 polar photodiodes. The classification results will be compared to topography data taken from AFM measurements. Finally, neural self-organized networks will be applied to classify in unsupervised manner rough surfaces based on BRDF measurements.

Modeling of an ARS sensor system in spatial and time domain

Scatterometry is a powerful and fast measurement method to measure surfaces and its properties. The backscattered light from a coherently illuminated surface contains information about integral surface topography constants, material properties, surface defects and contamination. In this paper a generic system model of an angle resolved light scatter sensor (ARS sensor) will be discussed and exemplified by using the sensor system LARISSA (Large Dynamic Range Intelligent Scatter Sensor Approach). The system model consists of two parts - firstly in spatial domain and secondly in time (or frequency) domain. The part of the system model in spatial domain contains the characteristics of the optical map of the scattered light onto a detector system. The optical map will be discussed by using an elliptical mirror optics with regard to aberration effects. The part of the system model in time (or frequency) domain contains the characteristics of the conversion of scattered light into quantized signals. The basic steps of the conversion process will be considered. Furthermore, the characteristics in time domain of a single CMOS detector (photo diode) with logarithmical intensity characteristics will be discussed to estimate the opto electronic bandwidth limitation and the minimal exposure time for different applications. Based on the system model basic performance limits will be summarized and further design steps of the sensor system LARISSA will be outlined. This paper is a continuation of a previous paper.

Performance limits of ARS sensors based on CMOS photodiode array

Measuring the light scatter back from a coherently illuminated surface is a powerful and fast measurement method to observe surfaces and its properties. It opens the possibility to measure integral surface topography constants, material properties, surface defects and contamination. In this paper the performance limits of the angle resolved light scatter sensor (ARS sensor) LARISSA (Large Dynamic Range Intelligent Scatter Sensor Approach) will be discussed and exemplified by using a technical application. In the first part of the paper the experimental setup of the ARS sensor LARISSA will be considered. In the second part of the paper the performance limitation of the ARS sensor LARISSA concerning particle detection will be derived based on simulation and measurement results. Finally a short overview is given about further development of the ARS sensor.

Design problems of a calibrated BRDF sensor with respect to dynamic range, speed, and large angle of view

This paper deals with applications of angle resolved light scatter (ARS) measurements as well as with the discussion of design and application problems of ARS sensors. The first section gives a description of the experimental sensor setup. In the second section of the paper two applications will be outlined, firstly particle detection on smooth Si surfaces, and secondly defect detection in small Si v-grooves. In the third section of the paper principal drawbacks of the experimental ARS sensor and their elimination will be discussed.

Comparison of PSD measurements using stray light sensors with PSD curves evaluated from topography of large AFM scans

For monitoring processes of semi conductor or optical industry automatically, stray light sensors are employed for a fast surface san to measure rms, defects, and contamination on surfaces. Surfaces can be characterized by the BRDF. The BRDF is parametrized to classify different surfaces. Classification may be done with various pattern recognition tools, but up to now no proof exists that justifies any choice of classes found empirically. Of course, a basic quantitative, i.e. metrological understanding of stray light sensors is necessary, which could successfully be obtained after comparing BRDFs evaluated from AFM topography scans with smooth surfaces. The power spectrum of surface topographies sufficiently smooth to obey Rayleigh-Rice approximation is proportional to the BRDF. Surfaces obeying this approximation, however, may not include defects and contamination with lateral sizes smaller than the wavelength of the illuminating light employed in the stray light sensor. Thus the comparison was only carried out with specially prepared samples. We have measured the topography of large areas up to 600 micrometer X 100 micrometer with an AFM by patching several scans (up to 8) with overlap. BRDFs evaluated from AFM measurements agree well with BRDFs measured with a stray light sensor.

Development review of an angle-resolved light scatter (ARS) sensor LARISSA

Scatterometry is a powerful and fast measurement method to measure surfaces and its properties. The backscattered light from a coherently illuminated surface contains information about integral surface topography constants, material properties, surface defects and contamination. This paper is a continuation a previous paper. In this paper the development of the angle resolved light scatter sensor system LARISSA (Large Dynamic Range Intelligent Scatter Sensor Approach) will be reviewed. In the first part of the paper the system components will be outlined. The system consists of an elliptical mirror optics and a CMOS photodiode detector array. The elliptical mirror optics enables the angle resolved and the integral scatter measurement in a solid angle of Pi sr. The CMOS photodiode detector array consists of 32k single detector elements which are aligned in a circular form. Each single detector element is calibrated in a dynamic range of 7 decades of intensity. The ARS system can be used to realize a scatter measurements without moving parts which is a significant advantage in speed over conventional goniometer setups. In the second part of the paper typical applications will be described which were examined by using the ARS system. Thereby surface roughness measurements in a rms range of 4..32 nm on smooth metallic surfaces will be considered by using BRDF measurements and the Rayleigh-Rice theory. In the third part of the paper the theoretical performance limits of surface roughness measurement will be derived based on measurements and simulation models. Finally the development and measurement results will be summarized and further the system will be outlined.

Deducing light scatter from AFM measurements

For the numerical prediction of the scattering behavior of arbitrary surfaces the use of a multi pole mthod is a potentially successful way. One reason is its direct addressing of the free space problem, which is primarily not possible with methods such as FEM. For purposes of verification with a reduced set of degrees of freedom the multi pole method is applied on gold plated blazed optical gratings, which are described as surfaces with one-dimensional height function and ideally conductive boundary, leading to a 2D-problem with a simplified matching of the boundary conditions. The geometry is deduced from AFM measurements, numerical results are compared with measurements. An outlook is given on further extensions of the multipole method to 3D-problems with arbitrary boundary conditions such as dielectric layers with losses.

Polarized light-scattering measurements of polished and etched steel surfaces

The directional dependence of the intensity and polarization of light scattered by a series of steel surfaces was measured. The samples differ by polishing procedure. Theories for light scattering from microroughness and permittivity variations are reviews and used to interpret the results. It is shown that the experimental data can be fit to a combination of the two scattering mechanisms, whereby the relative amplitude of the two scattering sources and the complex degree of correlation are treated as adjustable parameters. The fits show at low degree of correlation at high spatial frequencies. This correlation has a characteristic phase, common for all of the samples. Comparison at the fitted roughness power spectral density (PSD) functions with those obtained by atomic force microscopy (AFM) showed reasonable but not perfect agreement. This study demonstrates how measurements of the polarization of scattered light can be used to quantify the scatter from two different scattering sources.

Derivation of BRDF data from smooth surface topography of large AFM scans: investigation of the influences of surface figures and AFM artifacts

To measure microroughness, defects and contamination on surfaces such as wafers or optical instruments stray light sensors are a fast means. In order to obtain a traceable quantitative, i.e. metrological, measure of roughness (rms) the relation between rms from BRDF of a stray light sensor and rms from topography has to be given. The quantification of stray light sensor signals can well be done with smooth surfaces that have no defects, since forward simulation of the bidirectional reflectance distribution function (BRDF) from smooth surfaces obeying Rayleigh-Rice approximation is possible. We have measured the topography of large areas up to 315 X 315 micrometer2 with an atomic force microscope (AFM) by patching several scans (up to 25) with overlap to obtain bandwidth limits compatible to our stray light sensor. In profilometry roughness usually is evaluated after detrending, i.e. subtraction of surface figures. Hence for an evaluation of the roughness parameter rms by integrating the BRDF of a stray light measurement, the integration limits need to be chosen carefully. This paper gives a detailed discussion on a quantification of roughness measures.