公开(公告)号：US20240014080A1

公开(公告)日：2024-01-11

申请号：US18471893

申请日：2023-09-21

Applicant: Applied Materials, Inc.

Inventor： Kun Xu ,  Kiran Lall Shrestha ,  Doyle E. Bennett ,  David Maxwell Gage ,  Benjamin Cherian ,  Jun Qian ,  Harry Q. Lee

IPC: H01L21/66 ,  G06N3/08 ,  H01L21/304 ,  G06F17/15 ,  B24B37/013 ,  B24B49/10 ,  H01L21/321

CPC classification number: H01L22/14 ,  G06N3/08 ,  H01L21/304 ,  H01L22/12 ,  G06F17/15 ,  B24B37/013 ,  B24B49/105 ,  H01L21/3212 ,  H01L22/26

Abstract: A method of polishing a substrate includes polishing a conductive layer on the substrate at a polishing station, monitoring the layer with an in-situ eddy current monitoring system to generate a plurality of measured signals values for a plurality of different locations on the layer, generating thickness measurements the locations, and detecting a polishing endpoint or modifying a polishing parameter based on the thickness measurements. The conductive layer is formed of a first material having a first conductivity. Generating includes calculating initial thickness values based on the plurality of measured signals values and processing the initial thickness values through a neural network that was trained using training data acquired by measuring calibration substrates having a conductive layer formed of a second material having a second conductivity that is lower than the first conductivity to generated adjusted thickness values.

公开(公告)号：US11847776B2

公开(公告)日：2023-12-19

申请号：US17359345

申请日：2021-06-25

Applicant: Applied Materials, Inc.

Inventor： Sivakumar Dhandapani ,  Arash Alahgholipouromrani ,  Dominic J. Benvegnu ,  Jun Qian ,  Kiran Lall Shrestha

IPC: G06T7/00 ,  G06T7/60 ,  B24B37/013

CPC classification number: G06T7/001 ,  B24B37/013 ,  G06T7/60 ,  G06T2207/10024 ,  G06T2207/20021 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30148

Abstract: A neural network is trained for use in a substrate thickness measurement system by obtaining ground truth thickness measurements of a top layer of a calibration substrate at a plurality of locations, each location at a defined position for a die being fabricated on the substrate. A plurality of color images of the calibration substrate are obtained, each color image corresponding to a region for a die being fabricated on the substrate. A neural network is trained to convert color images of die regions from an in-line substrate imager to thickness measurements for the top layer in the die region. The training is performed using training data that includes the plurality of color images and ground truth thickness measurements with each respective color image paired with a ground truth thickness measurement for the die region associated with the respective color image.

公开(公告)号：US20230381912A1

公开(公告)日：2023-11-30

申请号：US18365527

申请日：2023-08-04

Applicant: Applied Materials, Inc.

Inventor： Kun Xu ,  Benjamin Cherian ,  Jun Qian ,  Kiran Lall Shrestha

IPC: B24B37/013 ,  G06N3/08

CPC classification number: B24B37/013 ,  G06N3/08

Abstract: A method of training a neural network includes obtaining two ground truth thickness profiles a test substrate, obtaining two thickness profiles for the test substrate as measured by an in-situ monitoring system while the test substrate is on polishing pads of different thicknesses, generating an estimated thickness profile for another thickness value that is between the two thickness values by interpolating between the two profiles, and training a neural network using the estimated thickness profile.

公开(公告)号：US11780047B2

公开(公告)日：2023-10-10

申请号：US17344779

申请日：2021-06-10

Applicant: Applied Materials, Inc.

Inventor： Kun Xu ,  Benjamin Cherian ,  Jun Qian ,  Kiran Lall Shrestha

IPC: B24B37/00 ,  B24B37/013 ,  G06N3/08

CPC classification number: B24B37/013 ,  G06N3/08

Abstract: A method of training a neural network includes obtaining two ground truth thickness profiles a test substrate, obtaining two thickness profiles for the test substrate as measured by an in-situ monitoring system while the test substrate is on polishing pads of different thicknesses, generating an estimated thickness profile for another thickness value that is between the two thickness values by interpolating between the two profiles, and training a neural network using the estimated thickness profile.

公开(公告)号：US11658078B2

公开(公告)日：2023-05-23

申请号：US17317501

申请日：2021-05-11

Applicant: Applied Materials, Inc.

Inventor： Kun Xu ,  Kiran Lall Shrestha ,  Doyle E. Bennett ,  David Maxwell Gage ,  Benjamin Cherian ,  Jun Qian ,  Harry Q. Lee

IPC: H01L21/66 ,  H01L21/304 ,  B24B37/013 ,  B24B49/10 ,  H01L21/321 ,  G06N3/08 ,  G06F17/15

CPC classification number: H01L22/14 ,  B24B37/013 ,  B24B49/105 ,  G06F17/15 ,  G06N3/08 ,  H01L21/304 ,  H01L21/3212 ,  H01L22/12 ,  H01L22/26

Abstract: A method of polishing a substrate includes polishing a conductive layer on the substrate at a polishing station, monitoring the layer with an in-situ eddy current monitoring system to generate a plurality of measured signals values for a plurality of different locations on the layer, generating thickness measurements the locations, and detecting a polishing endpoint or modifying a polishing parameter based on the thickness measurements. The conductive layer is formed of a first material having a first conductivity. Generating includes calculating initial thickness values based on the plurality of measured signals values and processing the initial thickness values through a neural network that was trained using training data acquired by measuring calibration substrates having a conductive layer formed of a second material having a second conductivity that is lower than the first conductivity to generated adjusted thickness values.