Systems for parsing material properties from within SHG signals
Semiconductor metrology systems based on directing radiation on a wafer, detecting second harmonic generated (SHG) radiation from the wafer and correlating the second harmonic generated (SHG) signal to one or more electrical properties of the wafer are disclosed. The disclosure also includes parsing the SHG signal to remove contribution to the SHG signal from one or more material properties of the sample such as thickness. Systems and methods described herein include machine learning methodologies to automatically classify obtained SHG signal.
1. A method for characterizing a sample, the method comprising:
directing a beam of electro-magnetic radiation to a sample using an optical source, wherein the beam comprises electro-magnetic radiation at a first wavelength;
detecting a Second Harmonic Generation (SHG) signal emitted from the sample using an optical detector, wherein the detected SHG signal comprises electro-magnetic radiation at a second wavelength different from the first wavelength that is at least partially attributed to one or more material properties of the sample;
measuring the one or more material properties of the sample using a secondary analysis device; and
under control of an electronic processing circuit:
correlating the detected SHG signal with the measured one or more material properties of the sample;
removing the portion attributed to one or more material properties of the sample to obtain a parsed SHG signal data; and
estimating a characteristic of the sample from the parsed SHG signal data.
2. The method of claim 1 , wherein the optical source is a laser.
3. The method of claim 1 , wherein the secondary analysis device system comprises at least one of: a reflectometer, a spectroscopic ellipsometer (SE), a CV-IV parametric analyzer, an Inductively Coupled Plasma Mass Spectrometry (ICPMS), Vapor Phase decomposition (VPD)-ICPMS, a Total Reflection X-Ray Fluorescence (TXRF), a Secondary Ion Mass Spectrometry (SIMS), a Rutherford Backscattering (RBS), a Scanning/Tunneling Electron Microscope (SEM/TEM), Atomic Force Microscope (AFM), Brightfield/Darkfield Microscopy, Glow Discharge Optical Emission Spectroscopy (GD-OES), X-Ray Photoelectron Spectroscopy (XPS), Fourier Transform Infrared Spectroscopy (FTIR), or a microwave detected photoconductive decay (μ-PCD).
4. The method of claim 1 , wherein the one or more material properties of the sample includes at least one of: thickness of one or more layers of the sample or presence of a known artifact.
5. The method of claim 1 , wherein the characteristic of the sample estimated from the parsed SHG signal data includes one or more electrical properties of the sample.
6. The method of claim 5 , wherein the one or more electrical properties of the sample includes at least one of: local surface and subsurface metal; organic or inorganic contaminants; trap charge density; strain or doping levels.
7. The method of claim 1 , wherein removing the portion attributed to one or more material properties of the sample comprises:
determining a quantitative relationship between the measured one or more material properties of the sample and the detected SHG signal; and
adjusting the detected SHG signal by an amount of SHG signal that is expected from a sample having the measured one or more material properties.
8. The method of claim 7 , wherein adjusting the detected SHG signal comprises dividing the detected SHG signal by an amount of SHG signal that is expected from a sample having the measured one or more material properties.
9. The method of claim 1 , wherein removing the portion attributed to one or more material properties of the sample comprises:
determining a quantitative relationship between the measured one or more material properties of the sample and the detected SHG signal; and
deconvoluting the detected SHG signal by an amount of SHG signal that is expected from a sample having the measured one or more material properties.