Abstract: A method for detecting crystal defects includes scanning a first FOV on a first sample using a charged particle beam with a plurality of different tilt angles. BSE emitted from the first sample are detected and a first image of the first FOV is created. A first area within the first image is identified where signals from the BSE are lower than other areas of the first image. A second FOV on a second sample is scanned using approximately the same tilt angles or deflections as those used to scan the first area. The BSE emitted from the second sample are detected and a second image of the second FOV is created. Crystal defects within the second sample are identified by identifying areas within the second image where signals from the BSE are different than other areas of the second image.

Abstract: A method for detecting crystal defects includes scanning a first FOV on a first sample using a charged particle beam with a plurality of different tilt angles. BSE emitted from the first sample are detected and a first image of the first FOV is created. A first area within the first image is identified where signals from the BSE are lower than other areas of the first image. A second FOV on a second sample is scanned using approximately the same tilt angles or deflections as those used to scan the first area. The BSE emitted from the second sample are detected and a second image of the second FOV is created. Crystal defects within the second sample are identified by identifying areas within the second image where signals from the BSE are different than other areas of the second image.

Abstract: A method for classifying defects of a wafer, the method is executed by a computerized system, the method may include obtaining defect candidate information about a group of defect candidates, wherein the defect candidate information comprises values of attributes per each defect candidate of the group; selecting, by a processor of the computerized system, a selected sub-group of defect candidates in response to values of attributes of defect candidates that belong to at least the selected sub-group; classifying defect candidates of the selected sub-group to provide selected sub-group classification results; repeating, until fulfilling a stop condition: selecting an additional selected sub-group of defect candidates in response to (a) values of attributes of defect candidates that belong to at least the additional selected sub-group; and (b) classification results obtained from classifying at least one other selected sub-group; and classifying defect candidates of the additional selected sub-group to provide a

Abstract: A system for electrically testing an object, the system may include a scanning electron microscope that comprises a column; and nano-probe modules that are mechanically connected to the column; wherein the column is configured to illuminate areas of the object, with a beam of charged particles; wherein nano-probes of the nano-probe modules are configured to electrically contact elements of the object, during electrical tests of the object, wherein the elements of the object are located within the areas of the object.

Abstract: A computerized system that may include a recipe module and a yield diagnostics module. The yield diagnostics module may be configured to generate evaluation results that are indicative of an outcome of an evaluation process of at least one manufacturing stage of at least one electrical circuit. The evaluation results differ from end of line (EOL) results. The recipe module may be configured to receive EOL results relating to the at least one electrical circuit, to receive the evaluation results relating to the at least one electrical circuit; to correlate the evaluation results and the EOL results to provide correlation results; and respond to the correlation results. The responding to the correlation results may include determining whether to alter a recipe in response to the correlation results and altering the recipe if it is determined to alter the recipe.

Abstract: A computerized system that may include a recipe module and a yield diagnostics module. The yield diagnostics module may be configured to generate evaluation results that are indicative of an outcome of an evaluation process of at least one manufacturing stage of at least one electrical circuit. The evaluation results differ from end of line (EOL) results. The recipe module may be configured to receive EOL results relating to the at least one electrical circuit, to receive the evaluation results relating to the at least one electrical circuit; to correlate the evaluation results and the EOL results to provide correlation results; and respond to the correlation results. The responding to the correlation results may include determining whether to alter a recipe in response to the correlation results and altering the recipe if it is determined to alter the recipe.

Abstract: A method for classifying defects of a wafer, the method is executed by a computerized system, the method may include obtaining defect candidate information about a group of defect candidates, wherein the defect candidate information comprises values of attributes per each defect candidate of the group; selecting, by a processor of the computerized system, a selected sub-group of defect candidates in response to values of attributes of defect candidates that belong to at least the selected sub-group; classifying defect candidates of the selected sub-group to provide selected sub-group classification results; repeating, until fulfilling a stop condition: selecting an additional selected sub-group of defect candidates in response to (a) values of attributes of defect candidates that belong to at least the additional selected sub-group; and (b) classification results obtained from classifying at least one other selected sub-group; and classifying defect candidates of the additional selected sub-group to provide a

Abstract: A method for classifying defects of a wafer, the method is executed by a computerized system, the method may include obtaining defect candidate information about a group of defect candidates, wherein the defect candidate information comprises values of attributes per each defect candidate of the group; selecting, by a processor of the computerized system, a selected sub-group of defect candidates in response to values of attributes of defect candidates that belong to at least the selected sub-group; classifying defect candidates of the selected sub-group to provide selected sub-group classification results; repeating, until fulfilling a stop condition: selecting an additional selected sub-group of defect candidates in response to (a) values of attributes of defect candidates that belong to at least the additional selected sub-group; and (b) classification results obtained from classifying at least one other selected sub-group; and classifying defect candidates of the additional selected sub-group to provide a

Abstract: A method and apparatus for removing surface impurities from a surface of a material, particularly silicon wafers, includes identifying the location of at least one impurity particle on a surface of the material and applying a liquid to the surface in the vicinity of the at least one impurity particle. The liquid is explosively evaporated to remove the surface particle as part of the evaporation of the liquid. The apparatus can include a source of humidified gas for the liquid and a laser apparatus to provide the heat for liquid evaporation.

Abstract: Apparatus and a method for removing particles from the surface of a substrate include determining respective position coordinates of the particles on the surface. A beam of electromagnetic energy is directed via an optical cleaning arm at the coordinates of each of the particles in turn, such that absorption of the electromagnetic energy at the surface causes the particles to be dislodged from the surface substantially without damage to the surface itself.

Abstract: Apparatus and a method for removing particles from the surface of a substrate include determining respective position coordinates of the particles on the surface. A beam of electromagnetic energy is directed via an optical cleaning arm at the coordinates of each of the particles in turn, such that absorption of the electromagnetic energy at the surface causes the particles to be dislodged from the surface substantially without damage to the surface itself.

Abstract: Apparatus and a method for removing particles from the surface of a substrate include determining respective position coordinates of the particles on the surface. A beam of electromagnetic energy is directed via an optical cleaning arm at the coordinates of each of the particles in turn, such that absorption of the electromagnetic energy at the surface causes the particles to be dislodged from the surface substantially without damage to the surface itself.

Abstract: This invention is directed to apparatus and a method for removing particles from a surface, such as a semiconductor wafer. A fluid is applied to the surface on which the particles are distributed so as to coat the particles with the fluid. At least some of these particles have a dimension of less than approximately one micron. A suction force is applied in the vicinity of the surface after applying the fluid so as to remove from the surface the majority of those particles having the dimension of less than approximately one micron.

Abstract: This invention is directed to apparatus and a method for removing particles from a surface, such as a semiconductor wafer. A fluid is applied to the surface on which the particles are distributed so as to coat the particles with the fluid. At least some of these particles have a dimension of less than approximately one micron. A suction force is applied in the vicinity of the surface after applying the fluid so as to remove from the surface the majority of those particles having the dimension of less than approximately one micron.

Abstract: A method of quality control in the fabrication of semiconductor devices. During and after the deposition and patterning of two successive layers on a semiconductor wafer, two independent measures of the alignment of the two layers are obtained. From each of these measures of the alignment, there is obtained a measure of the quality of a corresponding model of the alignment. These two measures of the quality of the models are compared. In one preferred independent measure of model quality, the model is a model of upper layer misalignment that is constructed by the stepper that positions the wafer for the patterning of the upper layer. In another preferred independent measure of model quality, the model is a model of mutual layer misalignment that is determined from mutual displacement of the overlay keys of the two layers. The measures of model quality are based on the residuals of these models.