A multi-modal sensor system includes: an underlying sensor system; a polarization camera system configured to capture polarization raw frames corresponding to a plurality of different polarization states; and a processing system including a processor and memory, the processing system being configured to control the underlying sensor system and the polarization camera system, the memory storing instructions that, when executed by the processor, cause the processor to: control the underlying sensor system to perform sensing on a scene and the polarization camera system to capture a plurality of polarization raw frames of the scene; extract first tensors in polarization representation spaces based on the plurality of polarization raw frames; and compute a characterization output based on an output of the underlying sensor system and the first tensors in polarization representation spaces.

The present invention relates to an apparatus and a method for measuring a thickness and a refractive index of a multilayer thin film using an angle-resolved spectral interference image according to polarization. More specifically, the present invention relates to an apparatus for measuring a thickness and a refractive index of a multilayer thin film using an angle-resolved spectral interference image according to polarization in an apparatus for measuring a thickness and a refractive index of a measurement object coated with the multilayer thin film, the apparatus including: an illumination optical module having a light source emitting light; a first beam splitter configured to reflect some of the light emitted from the illumination optical module; an objective lens configured to input some of the light reflected from the first beam splitter to the measurement object constituted by the multilayer thin film and reflect the remaining light to a reference plane to form interference light on a back focal plane; a second beam splitter in which interference light where the reflected light incident and reflected to the measurement object interferes with the reflected light reflected from the reference plane is incident, wherein some of the interference light is reflected and the remaining interference light is transmitted; a first angle-resolved spectral image acquiring unit configured to receive interference light reflected from the second beam splitter and first-polarize the interference light located in the back focal plane of the objective lens to acquire a first polarized interference image; and a second angle-resolved spectral image acquiring unit configured to receive interference light transmitted from the second beam splitter and second-polarize the interference light located in the back focal plane of the objective lens to acquire a second polarized interference image.

A thickness measurement device is provided for measuring a thickness of a first layer of an entire plant leaf including the first layer and a second layer, the first layer having an incident surface and an opposing surface opposing the incident surface, the second layer being in contact with the opposing surface of the first layer. The thickness measurement device includes: a light source that causes light of a predetermined wavelength λ to enter the incident surface as an incident light from an air layer at a predetermined incident angle θ.sub.i; a spectroscopic camera that receives a combined reflected light obtained by combining first and second reflected lights, and acquires a two-dimensional image including a light intensity of an S-polarized light component perpendicular to the incident surface among the combined reflected light; and a controller that calculates the thickness t of the first layer by using a predetermined equation.

An optical metrology model for in-line thickness measurements of a film overlying non-ideal structures on a substrate is generated by performing pre-measurements prior to deposition of the film and performing post-measurements after the deposition. The pre- and post-measurements are performed at at least one of multiple polarization angles or multiple orientations of the substrate. Differences in reflectance between the pre- and post-measurements are determined at the multiple polarization angles and the multiple orientations. At least one of the multiple polarization angles or the multiple orientations are identified where the differences in reflectance are indicative of a suppressed influence from the non-ideal structures. The optical metrology model is generated using the identified polarization angles and the identified orientations as inputs to a machine-learning algorithm

The light from an optical metrology device is focused into a measurement spot on a sample using a focusing system. The focusing system uses an image of the light reflected from the measurement spot to determine a best focal position at a desired position of the sample. The focusing system selects a characteristic of reflected light, such as polarization state or wavelengths, to use for focusing. The characteristic of the reflected light that is selected for use in determining focal position is affected different by different portions of the sample. For example, light reflected from a top surface of a sample may have a different characteristic than light reflected by an underlying layer. The selected characteristic of the reflected light is used by the focusing system to focus the measurement spot at the top surface or an underlying layer of the sample.

A computer-implemented method for measuring a parameter of a semiconductor. A non-limiting example of the computer-implemented method includes receiving, using a processor, a raw signal from a first tool representing a measured parameter of a semiconductor device. The method also receives, using the processor, data on the measured parameter from a second tool, and calculates, using the processor, the measured parameter based on the data received from the second tool and on a constraint based on the raw signal from the first tool.

A parameterized geometric model of a structure can be determined based on spectra from a wafer metrology tool. The structure can have geometry-induced anisotropic effects. Dispersion parameters of the structure can be determined from the parameterized geometric model. This can enable metrology techniques to measure nanostructures that have geometries and relative positions with surrounding structures that induce non-negligible anisotropic effects. These techniques can be used to characterize process steps involving metal and semiconductor targets in semiconductor manufacturing of, for example, FinFETs or and gate-all-around field-effect transistors.

A semiconductor structure and a method for managing semiconductor wafer stress are disclosed. The semiconductor structure includes a semiconductor wafer, a first stress layer disposed on and in contact with a backside of the semiconductor wafer, and a second stress layer on and in contact with the first stress layer. The first stress layer exerts a first stress on the semiconductor wafer and the second layer exerts a second stress on the semiconductor wafer that is opposite the first backside stress. The method includes forming a first stress layer on and in contact with a backside of a semiconductor wafer, and further forming a second stress layer on and in contact with the first stress layer. The first stress layer exerts a first stress on the semiconductor wafer and the second stress layer exerts a second stress on the semiconductor wafer that is opposite to the first stress.

Methods and systems for performing spectroscopic measurements of semiconductor structures including ultraviolet, visible, and infrared wavelengths greater than two micrometers are presented herein. A spectroscopic measurement system includes a combined illumination source including a first illumination source that generates ultraviolet, visible, and near infrared wavelengths (wavelengths less than two micrometers) and a second illumination source that generates mid infrared and long infrared wavelengths (wavelengths of two micrometers and greater). Furthermore, the spectroscopic measurement system includes one or more measurement channels spanning the range of illumination wavelengths employed to perform measurements of semiconductor structures. In some embodiments, the one or more measurement channels simultaneously measure the sample throughout the wavelength range. In some other embodiments, the one or more measurement channels sequentially measure the sample throughout the wavelength range.

Methods and systems for solving measurement models of complex device structures with reduced computational effort and memory requirements are presented. The computational efficiency of electromagnetic simulation algorithms based on truncated spatial harmonic series is improved for periodic targets that exhibit a fundamental spatial period and one or more approximate periods that are integer fractions of the fundamental spatial period. Spatial harmonics are classified according to each distinct period of the target exhibiting multiple periodicity. A distinct truncation order is selected for each group of spatial harmonics. This approach produces optimal, sparse truncation order sampling patterns, and ensures that only harmonics with significant contributions to the approximation of the target are selected for computation. Metrology systems employing these techniques are configured to measure process parameters and structural and material characteristics associated with different semiconductor fabrication processes.