A system for predicting rare earth elements (REEs) in a feedstock sample includes a measurement instrument that records a measurement for a sample, a processor communicatively coupled to the measuring instrument, and a memory communicatively coupled to the processor and containing machine readable instructions that, when executed by the processor, cause the processor to correlate the measurement series using a model; and predict a presence of one or more rare earth element based at least in part on the correlation. A method for predicting rare earth elements includes measuring feedstock samples via XRF or PGNAA, to generate a measurements of elements of interest with a lower atomic weight than REEs; correlating the measurements with a model; and predicting a presence of one or more rare earth elements based at least in part on the correlation.

Provided are a quantitative analysis method, a quantitative analysis program, and an X-ray fluorescence. The quantitative analysis method includes: a step of acquiring a representative composition set to represent contents of analysis components; a step of acquiring a plurality of comparative compositions, in each of which the content of one of the analysis components of the representative composition is changed by a predetermined content; a detection intensity calculation step of calculating a detection intensity indicating an intensity of fluorescent X-rays detected under the influence of the geometry effect through use of an FP method with respect to a virtual sample having a thickness set in advance and being indicated by each of the representative composition and the comparative compositions; and a step of calculating a matrix correction coefficient for each of the analysis components based on the detection intensity.

A system to characterize a film layer within a measurement box is disclosed. The system obtains a first mixing fraction corresponding to a first X-ray beam, the mixing fraction represents a fraction of the first X-ray beam inside a measurement box of a wafer sample, the measurement box represents a bore structure disposed over a substrate and having a film layer disposed inside the bore structure. The system obtains a contribution value for the measurement box corresponding to the first X-ray beam, the contribution value representing a species signal outside the measurement box that contributes to a same species signal inside the measurement box. The system obtains a first measurement detection signal corresponding to a measurement of the measurement box using the first X-ray beam. The system determines a measurement value of the film layer based on the first measurement detection signal, the contribution value, and the first mixing fraction.

An X-ray inspection apparatus includes an X-ray generator; an X-ray detector; and a determination unit determining a quality state of an inspection object, based on an X-ray detection signal. The apparatus has an X-ray image storing unit storing a first inspection image, corresponding to the X-ray detection signal outputted from the X-ray detector, whose observation direction is the direction in which the X-rays transmits the inspection object; a pseudo three-dimensional information generation model generating pseudo three-dimensional information regarding a type of object to be learned; and an inspection image generation unit creating a second inspection image regarding the type of object to be learned having an observation direction different from the first inspection image, based on the first inspection image regarding the type of object to be learned. The determination unit performs the determination based on at least the second inspection image created by the inspection image generation unit.

Provided is a fine structure determination method capable of easily determining tilt angles of columnar scattering bodies that are long in a thickness direction, and provided are an analysis apparatus and an analysis program thereof. There is provided an analysis method for a fine structure of a plate-shaped sample formed to have columnar scattering bodies that are long in a thickness direction and periodically arranged, comprising the steps of preparing scattering intensity data from the plate-shaped sample, that is generated via transmission of X-rays; and determining tilt angles of the scattering bodies in the plate-shaped sample with respect to a reference rotation position at which a surface of the plate-shaped sample is perpendicular to an incident direction of the X-rays, based on the prepared scattering intensity data.

A system for predicting rare earth elements (REEs) in a feedstock sample includes a measurement instrument that records a measurement for a sample, a processor communicatively coupled to the measuring instrument, and a memory communicatively coupled to the processor and containing machine readable instructions that, when executed by the processor, cause the processor to correlate the measurement series using a model; and predict a presence of one or more rare earth element based at least in part on the correlation. A method for predicting rare earth elements includes measuring feedstock samples via XRF or PGNAA, to generate a measurements of elements of interest with a lower atomic weight than REEs; correlating the measurements with a model; and predicting a presence of one or more rare earth elements based at least in part on the correlation.

The present invention provides a method for estimating the permeability of rock from a digital image of the rock. A three-dimensional image of a rock is obtained and segmented, and an image permeability is determined from the segmented image of the rock. Permeability correction factors are obtained from the segmented image and from a non-wetting liquid capillary pressure curve derived from the segmented image, and the permeability correction parameters are applied to the image permeability to obtain a corrected image permeability of the rock.

A monitoring system and method are provided for determining at least one property of an integrated circuit (IC) comprising a multi-layer structure formed by at least a layer on top of an underlayer. The monitoring system receives measured data comprising data indicative of optical measurements performed on the IC, data indicative of x-ray photoelectron spectroscopy (XPS) measurements performed on the IC and data indicative of x-ray fluorescence spectroscopy (XRF) measurements performed on the IC. An optical data analyzer module analyzes the data indicative of the optical measurements and generates geometrical data indicative of one or more geometrical parameters of the multi-layer structure formed by at least the layer on top of the underlayer. An XPS data analyzer module analyzes the data indicative of the XPS measurements and generates geometrical and material related data indicative of geometrical and material composition parameters for said layer and data indicative of material composition of the underlayer. An XRF data analyzer module analyzes the data indicative of the XRF measurements and generates data indicative of amount of a predetermined material composition in the multi-layer structure. A data interpretation module generates combined data received from analyzer modules and processes the combined data and determines the at least one property of at least one layer of the multi-layer structure.

A training data generation device that can rapidly generate a large amount of training data to be input into a learning program is provided. The training data generation device generates training data to be used in machine learning. A learned model generated by the machine learning using the training data generated by the training data generation device is used in an inspection device that performs inspection for determining whether or not an inspection target is a normal product by inputting an image capturing the inspection target into the learned model. The training data generation device includes the following: a determination-target image extraction unit that extracts, from an input image capturing the inspection target, one or more determination-target images containing a determination target that satisfies a predetermined condition; a sorting unit that associates, on the basis of a sorting operation of sorting the inspection target captured in the determination-target image into either a normal product or a non-normal product, each of the determination-target images and a result of the sorting with each other; and a training data memory unit that stores training data in which each of the determination-target images and a result of the sorting are associated with each other.

A method, system, use, and computer program product for inspection of an item are disclosed. The method (1) comprises acquiring (2) a projection image of the item using a radiation imaging system and obtaining (3) a plurality of simulated projection images of the item or a component thereof, based on a simulation of a numerical three-dimensional model, in which at least one geometric parameter relating to the relative orientation between the simulated item, a simulated radiation source, and a simulated detection plane varies over the plurality of simulated images. The method comprises determining (4) a relative orientation of the item with respect to the imaging system, said determining of the relative orientation comprises comparing (9) the projection image to the plurality of simulated images. The method comprises determining (5) at least one angle of rotation taking a viewing angle and the relative orientation into account, moving (6) the item and/or the imaging system in accordance with the at least one angle of rotation and acquiring (7) a further projection image of the item, after moving the item, such that the further projection image corresponds to a view of the item from the viewing angle.