Patents by Inventor Lawrence V. Bot

Lawrence V. Bot has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Patent number: 11029148
    Abstract: Methods and systems for feed-forward of multi-layer and multi-process information using XPS and XRF technologies are disclosed. In an example, a method of thin film characterization includes measuring first XPS and XRF intensity signals for a sample having a first layer above a substrate. The first XPS and XRF intensity signals include information for the first layer and for the substrate. The method also involves determining a thickness of the first layer based on the first XPS and XRF intensity signals. The method also involves combining the information for the first layer and for the substrate to estimate an effective substrate. The method also involves measuring second XPS and XRF intensity signals for a sample having a second layer above the first layer above the substrate. The second XPS and XRF intensity signals include information for the second layer, for the first layer and for the substrate.
    Type: Grant
    Filed: May 12, 2020
    Date of Patent: June 8, 2021
    Assignee: NOVA MEASURING INSTRUMENTS, INC.
    Inventors: Heath A. Pois, Wei Ti Lee, Lawrence V. Bot, Michael C. Kwan, Mark Klare, Charles Thomas Larson
  • Publication number: 20200370885
    Abstract: Methods and systems for feed-forward of multi-layer and multi-process information using XPS and XRF technologies are disclosed. In an example, a method of thin film characterization includes measuring first XPS and XRF intensity signals for a sample having a first layer above a substrate. The first XPS and XRF intensity signals include information for the first layer and for the substrate. The method also involves determining a thickness of the first layer based on the first XPS and XRF intensity signals. The method also involves combining the information for the first layer and for the substrate to estimate an effective substrate. The method also involves measuring second XPS and XRF intensity signals for a sample having a second layer above the first layer above the substrate. The second XPS and XRF intensity signals include information for the second layer, for the first layer and for the substrate.
    Type: Application
    Filed: May 12, 2020
    Publication date: November 26, 2020
    Inventors: Heath A. Pois, Wei Ti Lee, Lawrence V. Bot, Michael C. Kwan, Mark Klare, Charles Thomas Larson
  • Patent number: 10648802
    Abstract: Methods and systems for feed-forward of multi-layer and multi-process information using XPS and XRF technologies are disclosed. In an example, a method of thin film characterization includes measuring first XPS and XRF intensity signals for a sample having a first layer above a substrate. The first XPS and XRF intensity signals include information for the first layer and for the substrate. The method also involves determining a thickness of the first layer based on the first XPS and XRF intensity signals. The method also involves combining the information for the first layer and for the substrate to estimate an effective substrate. The method also involves measuring second XPS and XRF intensity signals for a sample having a second layer above the first layer above the substrate. The second XPS and XRF intensity signals include information for the second layer, for the first layer and for the substrate.
    Type: Grant
    Filed: August 8, 2019
    Date of Patent: May 12, 2020
    Assignee: NOVA MEASURING INSTRUMENTS, INC.
    Inventors: Heath A. Pois, Wei Ti Lee, Lawrence V. Bot, Michael C. Kwan, Mark Klare, Charles Thomas Larson
  • Publication number: 20190360800
    Abstract: Methods and systems for feed-forward of multi-layer and multi-process information using XPS and XRF technologies are disclosed. In an example, a method of thin film characterization includes measuring first XPS and XRF intensity signals for a sample having a first layer above a substrate. The first XPS and XRF intensity signals include information for the first layer and for the substrate. The method also involves determining a thickness of the first layer based on the first XPS and XRF intensity signals. The method also involves combining the information for the first layer and for the substrate to estimate an effective substrate. The method also involves measuring second XPS and XRF intensity signals for a sample having a second layer above the first layer above the substrate. The second XPS and XRF intensity signals include information for the second layer, for the first layer and for the substrate.
    Type: Application
    Filed: August 8, 2019
    Publication date: November 28, 2019
    Inventors: Heath A. Pois, Wei Ti Lee, Lawrence V. Bot, Michael C. Kwan, Mark Klare, Charles Thomas Larson
  • Publication number: 20190033069
    Abstract: Methods and systems for feed-forward of multi-layer and multi-process information using XPS and XRF technologies are disclosed. In an example, a method of thin film characterization includes measuring first XPS and XRF intensity signals for a sample having a first layer above a substrate. The first XPS and XRF intensity signals include information for the first layer and for the substrate. The method also involves determining a thickness of the first layer based on the first XPS and XRF intensity signals. The method also involves combining the information for the first layer and for the substrate to estimate an effective substrate. The method also involves measuring second XPS and XRF intensity signals for a sample having a second layer above the first layer above the substrate. The second XPS and XRF intensity signals include information for the second layer, for the first layer and for the substrate.
    Type: Application
    Filed: September 24, 2018
    Publication date: January 31, 2019
    Inventors: Heath A. Pois, Wei Ti Lee, Lawrence V. Bot, Michael C. Kwan, Mark Klare, Charles Thomas Larson
  • Patent number: 10082390
    Abstract: Methods and systems for feed-forward of multi-layer and multi-process information using XPS and XRF technolgies are disclosed. In an example, a method of thin film characterization includes measuring first XPS and XRF intensity signals for a sample having a first layer above a substrate. A thickness of the first layer is determined based on the first XPS and XRF intensity signals. The information for the first layer and for the substrate is combined to estimate an effective substrate. Second XPS and XRF intensity signals are measured for a sample having a second layer above the first layer above the substrate. The method also involves determining a thickness of the second layer based on the second XPS and XRF intensity signals, the thickness accounting for the effective substrate.
    Type: Grant
    Filed: June 19, 2015
    Date of Patent: September 25, 2018
    Assignee: NOVA MEASURING INSTRUMENTS INC.
    Inventors: Heath A. Pois, Wei Ti Lee, Lawrence V. Bot, Michael C. Kwan, Mark Klare, Charles Thomas Larson
  • Publication number: 20170160081
    Abstract: Methods and systems for feed-forward of multi-layer and multi-process information using XPS and XRF technolgies are disclosed. In an example, a method of thin film characterization includes measuring first XPS and XRF intensity signals for a sample having a first layer above a substrate. A thickness of the first layer is determined based on the first XPS and XRF intensity signals. The information for the first layer and for the substrate is combined to estimate an effective substrate. Second XPS and XRF intensity signals are measured for a sample having a second layer above the first layer above the substrate. The method also involves determining a thickness of the second layer based on the second XPS and XRF intensity signals, the thickness accounting for the effective substrate.
    Type: Application
    Filed: June 19, 2015
    Publication date: June 8, 2017
    Applicant: ReVera, Incorporated
    Inventors: Heath A. Pois, Wei Ti Lee, Lawrence V. Bot, Michael C. Kwan, Mark Klare, Charles Thomas Larson