Processor system, semiconductor inspection system, and program

A semiconductor inspection system for inspecting a three-dimensional shape including a cross-sectional shape of a pattern of a semiconductor which is a sample, the semiconductor inspection system comprising:

• an electron microscope;
• and
• a processor system including at least one processor and at least one memory resource, wherein
• the processor is configured to:
• acquire one or more images captured by the electron microscope for each of one or more samples,
• calculate, for a singular reference region defined on each surface of the one or more samples, first feature data corresponding to each of a plurality of locations in the singular reference region from the captured image,
• calculate a first statistical value based on the first feature data at the plurality of locations,
• calculate, for each of a plurality of evaluation regions defined on each of the surfaces of the one or more samples corresponding to the singular reference region, second feature data corresponding to each of one or more locations in the plurality of evaluation regions from the captured image, as feature data of a same type as the first feature data, and
• convert the second feature data using the first statistical value to obtain a cross-sectional shape index,
• wherein each of the first feature data and the second feature data is at least one type of feature data among a line width, a white band peak, a bottom signal value, a top signal value, an inclination calculated based on signal waveform of the captured image, or a value that is calculated from the captured image by calculation, and
• wherein the processor is configured to:
• store, into the memory resource, the cross-sectional shape index, a target uniformity value, the first feature data and a manufacturing parameter in association with the first feature data,
• determine a uniformity of the one or more samples based on the cross-sectional shape index, and
• adjust the manufacturing parameter based on the association between the manufacturing parameter and the first feature data such that the uniformity of the one or more samples is greater than the target uniformity value.

A program for causing a processor system for evaluating a three-dimensional shape including a cross-sectional shape of a pattern of a semiconductor which is a sample, to perform processing, wherein

• a processor of the processor system is caused to perform the following processing:
• acquiring one or more images captured by an electron microscope for each of one or more samples;
• calculating, for a singular reference region defined on each surface of the one or more samples, first feature data corresponding to each of a plurality of locations in the singular reference region from the captured image;
• calculating a first statistical value based on the first feature data at the plurality of locations;
• calculating, for each of a plurality of evaluation regions defined on each of the surfaces of the one or more samples corresponding to the singular reference region, second feature data corresponding to each of one or more locations in the plurality of evaluation regions from the captured image, as feature data of a same type as the first feature data;
• and
• converting the second feature data using the first statistical value to obtain a cross-sectional shape index,
• wherein each of the first feature data and the second feature data is at least one type of feature data among a line width, a white band peak, a bottom signal value, a top signal value, an inclination calculated based on signal waveform of the captured image, or a value that is calculated from the captured image by calculation, and
• wherein the processor is configured to:
• store, into a memory resource, the cross-sectional shape index, a target uniformity value, the first feature data and a manufacturing parameter in association with the first feature data,
• determine a uniformity of the one or more samples based on the cross-sectional shape index, and
• adjust the manufacturing parameter based on the association between the manufacturing parameter and the first feature data such that the uniformity of the one or more samples is greater than the target uniformity value.