Abstract: A spectroscopic metrology system includes a spectroscopic metrology tool and a controller. The controller generates a model of a multilayer grating including two or more layers, the model including geometric parameters indicative of a geometry of a test layer of the multilayer grating and dispersion parameters indicative of a dispersion of the test layer. The controller further receives a spectroscopic signal of a fabricated multilayer grating corresponding to the modeled multilayer grating from the spectroscopic metrology tool. The controller further determines values of the one or more parameters of the modeled multilayer grating providing a simulated spectroscopic signal corresponding to the measured spectroscopic signal within a selected tolerance. The controller further predicts a bandgap of the test layer of the fabricated multilayer grating based on the determined values of the one or more parameters of the test layer of the fabricated structure.

Abstract: A spectroscopic metrology system includes a spectroscopic metrology tool and a controller. The controller generates a model of a multilayer grating including two or more layers, the model including geometric parameters indicative of a geometry of a test layer of the multilayer grating and dispersion parameters indicative of a dispersion of the test layer. The controller further receives a spectroscopic signal of a fabricated multilayer grating corresponding to the modeled multilayer grating from the spectroscopic metrology tool. The controller further determines values of the one or more parameters of the modeled multilayer grating providing a simulated spectroscopic signal corresponding to the measured spectroscopic signal within a selected tolerance. The controller further predicts a bandgap of the test layer of the fabricated multilayer grating based on the determined values of the one or more parameters of the test layer of the fabricated structure.

Abstract: A spectroscopic metrology system includes a spectroscopic metrology tool and a controller. The controller generates a model of a multilayer grating including two or more layers, the model including geometric parameters indicative of a geometry of a test layer of the multilayer grating and dispersion parameters indicative of a dispersion of the test layer. The controller further receives a spectroscopic signal of a fabricated multilayer grating corresponding to the modeled multilayer grating from the spectroscopic metrology tool. The controller further determines values of the one or more parameters of the modeled multilayer grating providing a simulated spectroscopic signal corresponding to the measured spectroscopic signal within a selected tolerance. The controller further predicts a bandgap of the test layer of the fabricated multilayer grating based on the determined values of the one or more parameters of the test layer of the fabricated structure.

Abstract: A spectroscopic metrology system includes a spectroscopic metrology tool and a controller. The controller generates a model of a multilayer grating including two or more layers, the model including geometric parameters indicative of a geometry of a test layer of the multilayer grating and dispersion parameters indicative of a dispersion of the test layer. The controller further receives a spectroscopic signal of a fabricated multilayer grating corresponding to the modeled multilayer grating from the spectroscopic metrology tool. The controller further determines values of the one or more parameters of the modeled multilayer grating providing a simulated spectroscopic signal corresponding to the measured spectroscopic signal within a selected tolerance. The controller further predicts a bandgap of the test layer of the fabricated multilayer grating based on the determined values of the one or more parameters of the test layer of the fabricated structure.

Abstract: A system and method for local film stress calculation is disclosed. The method may include specifying a plurality of measurement points on a substrate, the substrate being configured to receive a film deposition; obtaining a local film thickness measurement for each measurement point; obtaining a local wafer shape parameter for each measurement point; and calculating a local film stress value for each measurement point based on the local film thickness measurement and the local wafer shape parameter for each corresponding measurement point. The method may further include specifying a plurality of estimation points on the substrate; obtaining a local wafer shape parameter for each estimation point; calculating an estimated local film thickness for each estimation point; and calculating a local film stress value for each estimation point based on the estimated local film thickness and the local wafer shape parameter for each corresponding estimation point.

Abstract: A local purging tool for purging a portion of a surface of a wafer with purging gas is disclosed. The purging tool includes a purging chamber configured to contain purging gas within a cavity of the purging chamber, a permeable portion of a surface of the purging chamber configured to diffuse purging gas from the cavity of the chamber to a portion of a surface of a wafer, and an aperture configured to transmit illumination received from an illumination source to a measurement location of the portion of the surface of the wafer and further configured to transmit illumination reflected from the measurement location to a detector.

Abstract: Ellipsometry systems and ellipsometry data collection methods with improved stabilities are disclosed. In accordance with the present disclosure, multiple predetermined, discrete analyzer angles are utilized to collect ellipsometry data for a single measurement, and data regression is performed based on the ellipsometry data collected at these predetermined, discrete analyzer angles. Utilizing multiple discrete analyzer angles for a single measurement improves the stability of the ellipsometry system.

Abstract: Ellipsometry systems and ellipsometry data collection methods with improved stabilities are disclosed. In accordance with the present disclosure, multiple predetermined, discrete analyzer angles are utilized to collect ellipsometry data for a single measurement, and data regression is performed based on the ellipsometry data collected at these predetermined, discrete analyzer angles. Utilizing multiple discrete analyzer angles for a single measurement improves the stability of the ellipsometry system.

Abstract: A local purging tool for purging a portion of a surface of a wafer with purging gas is disclosed. The purging tool includes a purging chamber configured to contain purging gas within a cavity of the purging chamber, a permeable portion of a surface of the purging chamber configured to diffuse purging gas from the cavity of the chamber to a portion of a surface of a wafer, and an aperture configured to transmit illumination received from an illumination source to a measurement location of the portion of the surface of the wafer and further configured to transmit illumination reflected from the measurement location to a detector.

Abstract: Ellipsometry systems and ellipsometry data collection methods with improved stabilities are disclosed. In accordance with the present disclosure, multiple predetermined, discrete analyzer angles are utilized to collect ellipsometry data for a single measurement, and data regression is performed based on the ellipsometry data collected at these predetermined, discrete analyzer angles. Utilizing multiple discrete analyzer angles for a single measurement improves the stability of the ellipsometry system.

Abstract: The present invention includes generating a three-dimensional design of experiment (DOE) for a plurality of semiconductor wafers, a first dimension of the DOE being a relative amount of a first component of the thin film, a second dimension of the DOE being a relative amount of a second component of the thin film, a third dimension of the DOE being a thickness of the thin film, acquiring a spectrum for each of the wafers, generating a set of optical dispersion data by extracting a real component (n) and an imaginary component (k) of the complex index of refraction for each of the acquired spectrum, identifying one or more systematic features of the set of optical dispersion data; and generating a multi-component Bruggeman effective medium approximation (BEMA) model utilizing the identified one or more systematic features of the set of optical dispersion data.

Abstract: A method of performing an investigation of a substrate, by measuring a reflectivity of the substrate, comparing the reflectivity of the substrate to an anticipated reflectivity value, selectively subjecting the substrate to a laser beam for a predetermined duration and at a predetermined energy only when the reflectivity of the substrate is within a specified tolerance of the anticipated reflectivity value, selectively signaling a fault condition when the reflectivity of the substrate is not within the specified tolerance of the anticipated reflectivity value, and selectively performing the investigation of the substrate only when the reflectivity of the substrate is within the specified tolerance of the anticipated reflectivity value.

Abstract: A method of performing a measurement of properties of a sample, by directing a first beam of light at the sample, where a combination of the wavelength, energy, and length of time is sufficient to cause temporary damage to the sample. The first beam is reflected from the sample. The properties of the reflected beam are sensed to create a signal. A length of time is waited, sufficient for the damage to substantially heal, before a second beam of light is directed at the sample, where a combination of the wavelength, energy, and length of time is sufficient to cause temporary damage to the sample. The second beam is reflected from the sample. The properties of the reflected beam are sensed to create a signal. The first and second electrical signals are analyzed to determine the properties of the sample.