Hitachi-high-technologies Corporation

Hitachi, Ltd.

Hitachi High-tech Corporation

Atsuko Yamaguchi

Hiroki Kawada

Hiroshi Fukuda

Osamu Komuro

Makoto Iwayama

Yoshiki Niwa

Akihiko Takano

Shingo Nishioka

Kazuhiro Ono

Tatsuya Maeda

Tsuneo Terasawa

Tadashi Otaka

Takashi Iizumi

Yoshinori Momonoi

Kazuhisa Hasumi

Junichi Tanaka

Norio Hasegawa

Yasunari Sohda

Yasutaka Toyoda

Ryoichi Matsuoka

Ryuta Tsuchiya

Osamu Inoue

Osamu Nasu

Taro Osabe

Masami Ikota

Jiro Yamamoto

Hitoshi Namai

Shozo Yoneda

To provide an image analysis apparatus capable of easily extracting an edge of an upper layer pattern formed intersecting with a lower layer pattern so as not to be affected by the lower layer pattern, the image analysis apparatus includes a calculation unit that calculates an analysis range including a region where the lower layer pattern intersects with the upper layer pattern and a region where the lower pattern is not formed, a calculation unit that averages a plurality of signal profiles, a calculation unit that calculates a maximum value and a minimum value of a signal intensity, a calculation unit that calculates a threshold level difference using the maximum value and the minimum value, and a calculation unit that calculates the edge of the upper layer pattern on the signal profile.

Image analysis apparatus and charged particle beam apparatus

In order to provide an inspection device capable of quantitatively evaluating a pattern related to a state of a manufacturing process or performance of an element, it is assumed that an inspection device includes an image analyzing unit that analyzes a top-down image of a sample in which columnar patterns are formed at a regular interval, in which an image analyzing unitincludes a calculation unitthat obtains a major axis, a minor axis, an eccentricity, and an angle formed by a major axis direction with an image horizontal axis direction of the approximated ellipse as a first index and a Cr calculation unitthat obtains a circumferential length of an outline of a columnar pattern on the sample and a value obtained by dividing a square of the circumferential length by a value obtained by multiplying an area surrounded by the outline and 4&#x3c0; as a second index.

Inspection device

Provided is a charged particle beam device which can specify a position of an initial core with high accuracy even when fine line and space patterns are formed by an SADP in plural times. The charged particle beam device includes a detector () which detects secondary charged particles discharged from a sample () when a charged particle beam is emitted to the sample having a plurality of patterns of line shape, a display unit () which displays image data of a surface of the sample on the basis of a signal of the secondary charged particles, a calculation unit () which calculates an LER value with respect to the plurality of the patterns of line shape from the image data, and a determination unit () which compares the values to determine a position of the initial core.

Charged particle beam device and inspection device

The present invention pertains to a method and device for quantitatively evaluating the degree and characteristics of wiggling, which is a phenomenon that occurs in electronic device fabrication processes and consists of the deformation in the same shape of the left and right edges of fine line patterns, and takes advantage of the fact that this wiggling is included in measured values for line edge variation but not line width variation by acquiring the differences between these values. Further, the present invention is configured so as to calculate line center positions and use the distribution of the deviation from the average line center position as an indicator. Additionally, the present invention is configured to quantify wiggling characteristics by outputting a coefficient of wiggling correlation between lines or a wiggling component synchronized between lines as an indicator.

Method and device for line pattern shape evaluation

An object of the present invention is to provide an image processing apparatus and a computer program which detects a defect such as a scum at high speed and with high precision. In order to accomplish the above-described object, the present invention proposes an image processing apparatus and a computer program which acquires image data, and detects edge branch points from this image data. Here, at each of the edge branch points, an edge associated therewith branches off in at least three or more directions. According to this configuration, it becomes possible to detect a defect such as a scum without utilizing the reference-pattern image. As a consequence, it becomes possible to detect the scum at high speed and with high precision.

Image processing apparatus

Provided are a semiconductor inspection device and a semiconductor inspection method such that in a specimen image in a single field of view obtained by an electron microscope, it is possible to suppress variations in the edge position measurement error attributable to the materials and structures of the lower layers of measured patterns by a first method, wherein the area in the field of view obtained by electron beam scanning is divided into a plurality of regions on the basis of information regarding the structures and materials of the object to be observed and the electron beam scanning conditions are changed for individual regions (), a second method, wherein, the image processing conditions are changed for individual regions resulting from division of the obtained images, or a third method, wherein the edge detection conditions are changed for individual regions resulting from the division within the edge inspection regions of the obtained images.

Semiconductor inspection device and semiconductor inspection method using the same

In order that a displacement between patterns of different heights, formed on a sample in a plurality of different pattern-forming steps, can be measured at fixed throughput and with high accuracy, correspondence between parameters of lenses and beam deflector of an electron optical system and an angle of incidence of a beam upon the sample is recorded as data, then a correction value for the amount of displacement or edge positions is calculated, and a true amount of displacement is calculated from the correction value and an image under observation.

Method and apparatus for measuring displacement between patterns and scanning electron microscope installing unit for measuring displacement between patterns

A measurement tool apparatus for evaluating degradation of pattern features in a semiconductor device manufacturing process. The measurement tool apparatus detects variations in the patterns from SEM images thereof and extracts pattern edge points along the circumference of each pattern. The measurement tool apparatus compares the pattern edge points to corresponding edge points of an ideal shape so as to determine deviation of the patterns. Metrics are derived from analysis of the deviations. The measurement tool apparatus uses the metrics in calculating an index representative of the geometry of edge spokes of the pattern, an indicator of the orientation of the edge spokes, and/or anticipated effects of the edge spokes on device performance.

Apparatus for evaluating degradation of pattern features

Disclosed herewith is a length measurement system, which obtains a value closer to its true one when figuring out the size and edge roughness of a pattern from a noise-included pattern image. Among plural band-like regions representing a portion around an edge in an image respectively, the system calculates the dependency of the edge point position on the image processing parameter at each of a narrow width band-like portion and a wide width band-like portion to calculate an image processing condition that calculates each measured value closer to its true value or estimates the true value itself.

Length measurement system

Edge points are extracted by specifying a height (values indicating a distance from a substrate) on a pattern when edges of the pattern are extracted from a CD-SEM image. Further, LER values obtained by the extraction of a Fourier spectrum of the LER are obtained. When the same sample is previously observed with the AFM and the CD-SEM, a size of the LER obtained by specifying a height, an auto-correlation distance of the LER, or an index called the spectrum is obtained from results of the AFM observation. Further, theses indices obtained by specifying image processing conditions for detecting the edge points from the CD-SEM observation result are obtained. Also, it is determined that heights providing values when the values are matched correspond to the image processing conditions and then, the edge points are extracted from the CD-SEM IMAGE instead of the AFM observation by using the image processing conditions.

Apparatus for data analysis

Equipment extracts components of spatial frequency that need to be evaluated in manufacturing a device or in analyzing a material or process out of edge roughness on fine line patterns and displays them as indexes. The equipment acquires data of edge roughness over a sufficiently long area, integrates components corresponding to a spatial frequency region being set on a power spectrum by the operator, and displays them on a length measuring SEM. Alternatively, the equipment divides the edge roughness data of the sufficiently long area, computes long-period roughness and short-period roughness that correspond to an arbitrary inspection area by performing statistical processing and fitting based on theoretical calculation, and displays them on the length measuring SEM.

Evaluation method of fine pattern feature, its equipment, and method of semiconductor device fabrication

A quantity (or dispersion value) of a distribution of edge position due to random noise is expected to be reduced statistically to 1/N when N edge position data items are averaged. Using this property, the single page image is averaged in a vertical direction with various values of parameter S, and then the edge roughness index is calculated. The S-dependence of the edge roughness index is analyzed and a term of a dispersion value directly proportional to 1/S is determined as being due to noise.

High-accuracy pattern shape evaluating method and apparatus

A system for measuring a pattern on a sample, including: a data processing system that processes a set of two-dimensional distribution data of intensities from the sample, to calculate: a set of edge points indicative of position of edges of the pattern in a two-dimensional plane from the two-dimensional distribution data; an approximation edge indicative of the edge of the pattern; an edge fluctuation data by calculating a difference between the set of edge points and the approximation edge; and a correlation between a first portion of the edge fluctuation data and a second portion of the edge fluctuation data.

Method and apparatus for circuit pattern inspection

Equipment extracts components of spatial frequency that need to be evaluated in manufacturing a device or in analyzing a material or process out of edge roughness on fine line patterns and displays them as indexes. The equipment acquires data of edge roughness over a sufficiently long area, integrates a components corresponding to a spatial frequency region being set on a power spectrum by the operator, and displays them on a length measuring SEM. Alternatively, the equipment divides the edge roughness data of the sufficiently long area, computes long-period roughness and short-period roughness that correspond to an arbitrary inspection area by performing statistical processing and fitting based on theoretical calculation, and displays them on the length measuring SEM.

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Kodaira, Japan

Atsuko Yamaguchi