A wavelet-analysis system and method for use in fabricating semiconductor device wafers, the system including a misregistration metrology tool operative to measure at least one measurement site on a wafer, thereby generating an output signal, and a wavelet-based analysis engine operative to generate at least one wavelet-transformed signal by applying at least one wavelet transformation to the output signal and generate a quality metric by analyzing the wavelet-transformed signal.

A system and method are disclosed for generating metrology measurements with second sub-system such as an optical sub-system. The method may include performing a training and a run-time operation. The training may include receiving first metrology data for device features from the first metrology sub-system (e.g., optical); generating first metrology measurements (e.g., critical dimensions, etc.); binning the device features into two or more device bins based on the first metrology measurements; and identifying representative metrology targets for the two or more device bins based on distributions of the first metrology measurements. The run-time operation may include receiving run-time metrology data (e.g., optical) of the representative metrology targets; and generating run-time metrology measurements based on the run-time metrology data.

The present application discloses a method for measuring critical dimension. The method for measuring critical dimension includes providing a substrate; forming a resist layer over the substrate; monitoring a volatile byproduct evolved from the resist layer to obtain a first amount of the volatile byproduct; exposing the resist layer to a radiation source; heating the resist layer; monitoring the volatile byproduct evolved from the resist layer to obtain a second amount of the volatile byproduct; and deducting the critical dimension according to a difference between the first amount of the volatile byproduct and the second amount of the volatile byproduct.

The present application discloses a method for measuring critical dimension. The method for measuring critical dimension includes providing a substrate; forming a resist layer over the substrate; monitoring a volatile byproduct evolved from the resist layer to obtain a first amount of the volatile byproduct; exposing the resist layer to a radiation source; heating the resist layer; monitoring the volatile byproduct evolved from the resist layer to obtain a second amount of the volatile byproduct; and deducting the critical dimension according to a difference between the first amount of the volatile byproduct and the second amount of the volatile byproduct.

An inspection system includes a controller including a memory maintaining program instructions and one or more processors configured to execute the program instructions. The program instructions cause the one or more processors to generate a geometric model of a structure of a sample, generate an optical response function model of the structure of the sample to illumination based at least in part on the geometric model, receive measured data from a detector, generate a parametric sub-structure model based on at least the optical response function model and the measured data, and extract one or more parameters of the structure based on the measured data.

A method of determining a stochastic metric, the method including: obtaining a trained model having been trained to correlate training optical metrology data to training stochastic metric data, wherein the training optical metrology data includes a plurality of measurement signals relating to distributions of an intensity related parameter across a zero or higher order of diffraction of radiation scattered from a plurality of training structures, and the training stochastic metric data includes stochastic metric values relating to the plurality of training structures, wherein the plurality of training structures have been formed with a variation in one or more dimensions on which the stochastic metric is dependent; obtaining optical metrology data including a distribution of the intensity related parameter across a zero or higher order of diffraction of radiation scattered from a structure; and using the trained model to infer a value of the stochastic metric from the optical metrology data.

A method of determining an overlay measurement of a substrate includes: injecting charge into a charge injection element of the substrate; determining a first capacitance of a first pair of elements and a second capacitance of a second pair of elements; and determining a capacitance ratio based on the first capacitance and the second capacitance. The overlay measurement may be determined based on the capacitance ratio, which may indicate an imbalance.

In some embodiments, one or more non-transitory, machine-readable medium has instructions thereon, the instructions when executed by a processor being configured to perform operations comprising obtaining scanning electron microscopy (SEM) metrology data for first areas on a training wafer, obtaining optical metrology data for second areas on the training wafer, and training a model, by using the SEM metrology data and the optical metrology data for the training wafer, to generate parameters for features on a production wafer based on optical metrology data for areas of the production wafer.

A method for detecting defects in a semiconductor structure is provided. The method includes the following operations. A semiconductor structure having a plurality of conductive structures is received. An electron beam inspection operation is performed on the plurality of conductive structures of the semiconductor structure to obtain an inspection data, wherein a pulsed electron beam utilized in the electron beam inspection operation is selected from the group consisting of a nanosecond pulsed beam, a picosecond pulsed beam, and a femtosecond pulsed beam. A first conductive structure having a non-open defect is identified from the inspection data. A method for classifying semiconductor structure is also provided.

An improved method and system for image alignment of an inspection image are disclosed. An improved method comprises acquiring an inspection image, acquiring a reference image corresponding to the inspection image, acquiring a target alignment between the inspection image and the reference image based on characteristics of the inspection image and the reference image, estimating an alignment parameter based on the target alignment, and applying the alignment parameter to a subsequent inspection image.