Roughness measurement corrects a machine difference utilizing first PSD data indicating power spectral density of a line pattern measured for a line pattern formed on a wafer for machine difference management by a reference machine in roughness index calculation and second PSD data indicating power spectral density of a line pattern measured for the line pattern formed on the wafer for machine difference management by a correction target machine are used to obtain a correction method for correcting the power spectral density of the second PSD data to the power spectral density of the first PSD data, power spectral density of a line pattern is measured as third PSD data from a scanning image of the line pattern, and corrected power spectral density obtained by correcting the power spectral density of the third PSD data by the obtained correction method is calculated.

Provided is a method for estimating abrasion resistance of polymer composite materials. The present disclosure relates to a method for estimating abrasion resistance, the method including: irradiating a sulfur compound-containing polymer composite material with high intensity X-rays; measuring an X-ray absorption in a small region of the polymer composite material while varying an energy of the X-rays, whereby a dispersion state and a chemical state of the sulfur compound are analyzed; and quantifying an inhomogeneous state of cross-link degradation in the polymer composite material based on the dispersion state and the chemical state.

A system and method for stress testing a sample, the system comprising a high-intensity laser unit and a target for laser-matter interaction, wherein the high-intensity laser unit delivers an intensity of at least 10.sup.13 W/cm.sup.2 on the target, and resulting laser-accelerated particles generated by the target irradiate the sample.

Provided is a method for estimating abrasion resistance and fracture resistance by highly accurately analyzing aggregation (dispersion) of sulfur-based materials in polymer composite materials. The present invention relates to a method for estimating abrasion resistance and fracture resistance, the method including: irradiating a polymer composite material containing at least one sulfur-based material selected from the group consisting of sulfur and sulfur compounds with high intensity X-rays; measuring X-ray absorption of a measurement region of the polymer composite material while varying the energy of the X-rays; calculating areas of spots having a high sulfur concentration equal to or greater than a predetermined level in a two-dimensional mapping image of sulfur concentration of the measurement region; and estimating abrasion resistance and fracture resistance based on the areas.

Systems and methods are disclosed that remove noise from roughness measurements to determine roughness of a feature in a pattern structure. In one embodiment, a method for determining roughness of a feature in a pattern structure includes generating, using an imaging device, a set of one or more images, each including measured linescan information that includes noise. The method also includes detecting edges of the features within the pattern structure of each image without filtering the images, generating a biased power spectral density (PSD) dataset representing feature geometry information corresponding to the edge detection measurements, evaluating a high-frequency portion of the biased PSD dataset to determine a noise model for predicting noise over all frequencies of the biased PSD dataset, and subtracting the noise predicted by the determined noise model from a biased roughness measure to obtain an unbiased roughness measure.

Provided is a method for estimating abrasion resistance and fracture resistance by highly accurately analyzing aggregation (dispersion) of sulfur-based materials in polymer composite materials. The present invention relates to a method for estimating abrasion resistance and fracture resistance, the method including: irradiating a polymer composite material containing at least one sulfur-based material selected from the group consisting of sulfur and sulfur compounds with high intensity X-rays; measuring X-ray absorption of a measurement region of the polymer composite material while varying the energy of the X-rays; calculating areas of spots having a high sulfur concentration equal to or greater than a predetermined level in a two-dimensional mapping image of sulfur concentration of the measurement region; and estimating abrasion resistance and fracture resistance based on the areas.

A single-crystal silicon carbide substrate has a main surface having a surface roughness fulfilling Ra1 nm, and has a ratio of hidden scratches of less than 50%, where, in the case where the main surface is arbitrary observed at 50 or more observation points with a field of view having a diameter of 100 m, the ratio of hidden scratches is defined by a value obtained by dividing the number of the observation points at which a striped hidden scratch having a length of at least 50 m by the total number of the observation points.

Systems and methods are disclosed that remove noise from roughness measurements to determine roughness of a feature in a pattern structure. In one embodiment, a method for determining roughness of a feature in a pattern structure includes generating, using an imaging device, a set of one or more images, each including measured linescan information that includes noise. The method also includes detecting edges of the features within the pattern structure of each image without filtering the images, generating a biased power spectral density (PSD) dataset representing feature geometry information corresponding to the edge detection measurements, evaluating a high-frequency portion of the biased PSD dataset to determine a noise model for predicting noise over all frequencies of the biased PSD dataset, and subtracting the noise predicted by the determined noise model from a biased roughness measure to obtain an unbiased roughness measure.

A wafer inspection apparatus including a light emitter configured to emit light onto a to-be-inspected surface of a wafer, an imaging unit configured to obtain an image formed by the light emitted from the light emitter and reflected by the to-be-inspected surface, a moving unit configured to move a to-be-inspected position on the to-be-inspected surface by controlling a position of one of the wafer and the light emitter, and an inspecting unit configured to inspect the to-be-inspected surface by detecting a scatter image formed by the light that is emitted from the light emitter and scattered by a defect of the to-be-inspected surface, where the scatter image is formed outside an outline of the image formed by the light emitted from the light emitter.

A nitride crystal is characterized in that, in connection with plane spacing of arbitrary specific parallel crystal lattice planes of the nitride crystal obtained from X-ray diffraction measurement performed with variation of X-ray penetration depth from a surface of the crystal while X-ray diffraction conditions of the specific parallel crystal lattice planes are satisfied, a uniform distortion at a surface layer of the crystal represented by a value of |d.sub.1d.sub.2|/d.sub.2 obtained from the plane spacing d.sub.1 at the X-ray penetration depth of 0.3 m and the plane spacing d.sub.2 at the X-ray penetration depth of 5 m is equal to or lower than 2.110.sup.3. The above configuration provides the nitride crystal having a crystal surface layer that is evaluated directly and reliably without breaking the crystal so that it can be used in a preferred fashion as a substrate for a semiconductor device as well as the nitride crystal substrate, an epilayer-containing nitride crystal substrate, a semiconductor device and a method of manufacturing the same.