A device and method for measuring angles of orientation of an x-ray imaging system including an x-ray source, an x-ray detector and a sample holder arranged to receive a sample to be analysed. The method includes: emitting a polychromatic x-ray beam through a reference sample installed on the sample holder in order to form a diffraction pattern on the sensing area of the x-ray detector, generating, with the x-ray detector, an observed image comprising the diffraction pattern, and determining the orientation of the x-ray source and the orientation of the x-ray detector by comparing the observed image with at least one target image comprising a diffraction pattern obtained for the reference sample with preset orientations of the x-ray source and of the x-ray detector.

There is provided a system and method of measuring a lateral recess in a semiconductor specimen, comprising: obtaining a first image acquired by collecting SEs emitted from the surface of the specimen, and a second image acquired by collecting BSEs scattered from an interior region of the specimen between the surface and a target second layer, the specimen scanned using an electron beam with a landing energy selected to penetrate to a depth corresponding to the target second layer; generating a first GL waveform based on the first image, and a second GL waveform based on the second image; estimating a first width of the first layers based on the first GL waveform, and a second width with respect to at least the target second layer based on the second GL; and measuring a lateral recess based on the first width and the second width.

Method and system are disclosed for determining sample composition from spectral data acquired by a charged particle microscopy system. Chemical elements in a sample are identified by processing the spectral data with a trained neural network (NN). If the identified chemical elements not matching with a known elemental composition of the sample, the trained NN is retrained with the spectral data and the known elemental composition of the sample. The retrained NN can then be used to identify chemical elements within other samples.

Provided is a portable XRF data screening method for heavy metal contaminated soil, relating to the technical field of heavy metal contamination test. The method includes the following steps: (1) laboratory test; (2) XRF test; and (3) calculation of a recheck interval: dividing test data into four areas by a contaminant screening value X.sub.c as a horizontal line and a correlation-derived site screening value as a vertical line to calculate the recheck interval. The method is simple and efficient, and is beneficial to saving investigation costs and shortening a project cycle.

Method and system are disclosed for determining sample composition from spectral data acquired by a charged particle microscopy system. Chemical elements in a sample are identified by processing the spectral data with a trained neural network (NN). If the identified chemical elements not matching with a known elemental composition of the sample, the trained NN is retrained with the spectral data and the known elemental composition of the sample. The retrained NN can then be used to identify chemical elements within other samples.

Methods and systems for improving a measurement recipe describing a sequence of measurements employed to characterize semiconductor structures are described herein. A measurement recipe is repeatedly updated before a queue of measurements defined by the previous measurement recipe is fully executed. In some examples, an improved measurement recipe identifies a minimum set of measurement options that increases wafer throughput while meeting measurement uncertainty requirements. In some examples, measurement recipe optimization is controlled to trade off measurement robustness and measurement time. This enables flexibility in the case of outliers and process excursions. In some examples, measurement recipe optimization is controlled to minimize any combination of measurement uncertainty, measurement time, move time, and target dose. In some examples, a measurement recipe is updated while measurement data is being collected. In some examples, a measurement recipe is updated at a site while data is collected at another site.

Volume data is generated by performing a CT scan with a spherical calibration jig having known dimensions in contact with an object. A profile of the surface shape of the object in the volume data is obtained, and a boundary surface of the spherical calibration jig is calculated from the center coordinates of the spherical calibration jig. A correction value for adjusting a boundary surface of the object determined from the gradient of the profile to the boundary surface of the spherical calibration jig is determined, and the boundary surface of the object is corrected by using the correction value. The shape of the object is determined by using the corrected boundary surface. The precision of measurement X-ray CT can thus be increased by accurately detecting the boundary surface of the object.

This application relates to apparatus and method for x-ray fluorescence analysis. There is provided an X-ray fluorescence analysis apparatus for analysing a sample, The X-ray fluorescence analysis apparatus comprises an X-ray source, a measurement chamber for holding the sample in air, and an X-ray detector. The X-ray source is arranged to irradiate the sample with a primary X-ray beam, to cause the sample to fluoresce. The X-ray detector is arranged to detect characteristic X-rays emitted by the sample and to determine a measured X-ray intensity associated with the characteristic X-rays. An X-ray filter, which transmits the primary X-ray beam, is arranged between the X-ray source and the sample. The X-ray source comprises an anode of material having an atomic number that is less than 25. The X-ray fluorescence analysis apparatus further comprises a sensor arrangement configured to sense air pressure and air temperature. A processor receives the measured X-ray intensity. The processor also receives air pressure data and air temperature data from the sensor arrangement. The processor is configured to carry out a compensation calculation for adjusting the measured X-ray intensity using the air pressure data and the air temperature data.

A system and method can determine one or more CT scanner calibration parameters from a plurality of calibration object projections in a plurality of radiographs.

A calibration method for an X-ray measuring device includes mounting a calibration tool on a rotating table, identifying centroid positions from an output of an X-ray image detector, calculating projection transformation matrixes from the centroid positions and known relative positional intervals, repeating to identify the centroid positions from the output of the X-ray image detector and to calculate the projection transformation matrixes from the centroid positions and known relative positional intervals while the rotating table is rotated twice or more by a predetermined angle, and calculating a rotation center position of the rotating table on the basis of the projection transformation matrixes. The calibration method thereby allows easy calculation of the rotation center position of the rotating table on which an object to be measured is mounted in a rotatable manner, with the simple process.