A method for evaluating a specimen, the method can include positioning an energy dispersive X-ray (EDX) detector at a first position; scanning a flat surface of the specimen by a charged particle beam that exits from a charged particle beam optics tip and propagates through an aperture of an EDX detector tip; detecting, by the EDX detector, x-ray photons emitted from the flat surface as a result of the scanning of the flat surface with the charged particle beam; after a completion of the scanning of the flat surface, positioning the EDX detector at a second position in which a distance between the EDX detector tip and a plane of the flat surface exceeds a distance between the plane of the flat surface and the charged particle beam optics tip; and wherein a projection of the EDX detector on the plane of the flat surface virtually falls on the flat surface when the EDX detector is positioned at the first position and when the EDX detector is positioned at the second position.

A method for generating cross-sectional profiles using a scanning electron microscope (SEM) includes scanning a sample with an electron beam to gather an energy-dispersive X-ray spectroscopy (EDS) spectrum for an energy level to determine element composition across an area of interest. A mesh is generated to locate positions where a depth profile will be taken. EDS spectra are gathered for energy levels at mesh locations. A number of layers of the sample are determined by distinguishing differences in chemical composition between depths as beam energies are stepped through. A depth profile is generated for the area of interest by compiling the number of layers and the element composition across the mesh.

A method and apparatus are provided for identifying a material with a sample-specific reference spectral list or library. A sequential approach to SEM-EDS automated mineralogy classification is carried out by performing two or more material classification analyses. A pre-classification step restricts the processing of spectra deconvolution algorithms to a subset of spectra that pass a dominant mineral criteria resulting in a significantly reduced subset of reference spectra that occur within the measured sample in pure enough form at a given minimum quantity. The following complex classification stages involving deconvolution of multiple constituents within measured spectra is based on this sample relevant subset.

A method for evaluating a specimen, the method can include positioning an energy dispersive X-ray (EDX) detector at a first position; scanning a flat surface of the specimen by a charged particle beam that exits from a charged particle beam optics tip and propagates through an aperture of an EDX detector tip; detecting, by the EDX detector, x-ray photons emitted from the flat surface as a result of the scanning of the flat surface with the charged particle beam; after a completion of the scanning of the flat surface, positioning the EDX detector at a second position in which a distance between the EDX detector tip and a plane of the flat surface exceeds a distance between the plane of the flat surface and the charged particle beam optics tip; and wherein a projection of the EDX detector on the plane of the flat surface virtually falls on the flat surface when the EDX detector is positioned at the first position and when the EDX detector is positioned at the second position.

A method for generating cross-sectional profiles using a scanning electron microscope (SEM) includes scanning a sample with an electron beam to gather an energy-dispersive X-ray spectroscopy (EDS) spectrum for an energy level to determine element composition across an area of interest. A mesh is generated to locate positions where a depth profile will be taken. EDS spectra are gathered for energy levels at mesh locations. A number of layers of the sample are determined by distinguishing differences in chemical composition between depths as beam energies are stepped through. A depth profile is generated for the area of interest by compiling the number of layers and the element composition across the mesh.

A method for generating cross-sectional profiles using a scanning electron microscope (SEM) includes scanning a sample with an electron beam to gather an energy-dispersive X-ray spectroscopy (EDS) spectrum for an energy level to determine element composition across an area of interest. A mesh is generated to locate positions where a depth profile will be taken. EDS spectra are gathered for energy levels at mesh locations. A number of layers of the sample are determined by distinguishing differences in chemical composition between depths as beam energies are stepped through. A depth profile is generated for the area of interest by compiling the number of layers and the element composition across the mesh.

A method for generating cross-sectional profiles using a scanning electron microscope (SEM) includes scanning a sample with an electron beam to gather an energy-dispersive X-ray spectroscopy (EDS) spectrum for an energy level to determine element composition across an area of interest. A mesh is generated to locate positions where a depth profile will be taken. EDS spectra are gathered for energy levels at mesh locations. A number of layers of the sample are determined by distinguishing differences in chemical composition between depths as beam energies are stepped through. A depth profile is generated for the area of interest by compiling the number of layers and the element composition across the mesh.

One embodiment relates to a method for automated review of defects detected in a defective die on the target substrate. The method includes: performing an automated review of the defects using an secondary electron microscope (SEM) so as to obtain electron-beam images of the defects; performing an automated classification of the defects into types based on morphology of the defects as determined from the electron-beam images; selecting defects of a specific type for automated energy-dispersive x-ray (EDX) review; and performing the automated EDX review on the defects of the specific type. In addition, automated techniques are disclosed for obtaining an accurate reference so as to improve the usefulness of the EDX results. Furthermore, an automated method of classifying the defects based on the EDX results is disclosed which provides a final pareto that combines both morphological and elemental information. Other embodiments, aspects and features are also disclosed.

The system described herein detects charged particles which, for example, are generated by interaction of a charged particle beam with an object to be analyzed using, for example, a particle beam device. Detection is carried out for imaging of the object. The system described herein allows detection of charged particles with the same detection principle when the ambient pressures in an object chamber are in a first pressure range being lower than or equal to 10.sup.3 hPa or in a second pressure range being equal to or above 10.sup.3 hPa. When operating with the object chamber in the second pressure range, the system described herein generates photons in a scintillator using cascade particles generated by using the charged particles and a gas, and detects the photons using a light detector.

A method for generating cross-sectional profiles using a scanning electron microscope (SEM) includes scanning a sample with an electron beam to gather an energy-dispersive X-ray spectroscopy (EDS) spectrum for an energy level to determine element composition across an area of interest. A mesh is generated to locate positions where a depth profile will be taken. EDS spectra are gathered for energy levels at mesh locations. A number of layers of the sample are determined by distinguishing differences in chemical composition between depths as beam energies are stepped through. A depth profile is generated for the area of interest by compiling the number of layers and the element composition across the mesh.