Tokyo Electron Limited

Lam Research Corporation

Jun Shinagawa

John Patrick Holland

Akira Koshiishi

Peter L G Ventzek

Chungjong Lee

Toshihiro Kitao

Alok Ranjan

Harmeet Singh

Megan Wooley

Masaki Kitsunezuka

S M Reza Sadjadi

Jisoo Kim

Carlos A Fonseca

Hiroshi Nagahata

Conan Chiang

Koichiro Nakamura

Brian Pfeifer

Yutaka Hirooka

John Solis

Brian Gessler

Atsushi Suzuki

Provided is a method for monitoring a plasma-related process in a plasma tool. The method includes measuring data associated with the plasma-related process using a plurality of sensors while executing the plasma-related process on a wafer. Respective data measured by each sensor of the plurality of sensors are input into a respective individual estimation method to output a respective individual wafer state of the wafer, which results in a plurality of individual wafer states. The respective individual estimation method is configured to estimate the respective individual wafer state using at least the respective data. The plurality of individual wafer states is input into an integrated estimation method to output an integrated wafer state of the wafer. The integrated estimation method is configured to estimate the integrated wafer state using at least the plurality of individual wafer states.

Data fusion of multiple sensors

A method of operating a plasma tool includes executing a plasma process on a wafer. Data associated with the plasma process are measured using a plurality of sensors while the plasma process is executed on the wafer. The plasma process is terminated at an endpoint time. A post-process fault detection is executed by determining whether a post-process wafer state is within a target range. When the post-process wafer state is outside the target range so that a fault is detected, the fault is corrected using the data associated with the plasma process.

Autonomous operation of plasma processing tool

Aspects of the disclosure provide a method for wafer result prediction. The method includes determining predictor parameters of a semiconductor process using domain knowledge that includes knowledge of the semiconductor process, a processing tool associated with the semiconductor process, a metrology tool, and/or the wafer. The method also includes removing collinearity among the predictor parameters to obtain key predictor parameters, and selecting a subset of the key predictor parameters based on metrology data of the wafer obtained from the metrology tool. The method further includes building a virtual metrology (VM) model on the subset of the key predictor parameters and may include predicting wafer results using the VM model.

Virtual metrology for wafer result prediction

A method for detecting an endpoint of a seasoning process for a plasma tool includes (a) operating the plasma tool to run a seasoning recipe on at least one seasoning wafer before running a monitoring recipe on at least one monitoring wafer; (b) collecting, while running the monitoring recipe on the monitoring wafer, monitoring data associated with the running the monitoring recipe; and (c) generating an estimated product parameter using a virtual metrology (VM) model that is configured to estimate a product parameter using the monitoring data. The VM model is based on production data associated with running a production recipe on production wafers and product parameters of the production wafers measured after the running the production recipe. The endpoint of the seasoning process is obtained by repeating (a), (b) and (c), and the endpoint is obtained when the estimated product parameter stabilizes.

Virtual metrology model based seasoning optimization

A method of optimizing a recipe for a plasma process includes (a) building a virtual metrology (VM) model that predicts a wafer characteristic resulting from the plasma process based on a plasma parameter and (b) building a control model that describes a relationship between the plasma parameter and a recipe parameter. (c) The wafer characteristic is measured after performing the plasma process according to the recipe. (d) Whether the wafer characteristic is within a predetermined range is determined. (e) The VM model and the control model are calibrated based on the wafer characteristic. (f) The recipe is optimized by updating the plasma parameter based on the wafer characteristic using the VM model and updating the recipe parameter based on the plasma parameter using the control model. (c), (d), (e) and (f) are repeated until the wafer characteristic is within the predetermined range.

Virtual metrology enhanced plasma process optimization method

A method of evaluating tool health of a plasma tool is provided. The method includes providing a virtual metrology (VM) model that predicts a wafer characteristic based on parameters measured by module sensors and in-situ sensors of the plasma tool. A classification model is provided that identifies a plurality of failure modes of the plasma tool. An initial test is performed on an incoming wafer to determine whether the incoming wafer meets a preset requirement. The wafer characteristic is predicted using the VM model when the incoming wafer meets the preset requirement. A current failure mode is identified using the classification model when the wafer characteristic predicted by using the VM model is outside a pre-determined range.

Tool health monitoring and classifications with virtual metrology and incoming wafer monitoring enhancements

Embodiments are described herein for sensor-to-sensor matching methods for chamber matching across multiple plasma processing chambers. For disclosed embodiments, a baseline signature in a first processing chamber is compared to a signature generated in a second processing chamber in order to adjust and match sensor display values for the second processing chamber. The baseline signature is determined using a golden reference sensor disposed within the first processing chamber and plasma sensors monitoring a baseline plasma. The signature of the plasma is determined using the golden reference sensor disposed within the second processing chamber and plasma sensors monitoring the plasma. Differences are determined between the baseline signature and the signature, and a display value for the plasma sensors for the second processing chamber is adjusted based on the differences to provide chamber matching with the first processing chamber. The golden reference sensor can be a wafer with embedded sensors.

Sensor-to-sensor matching methods for chamber matching

A method and a system for monitoring a plasma chamber are provided. The method includes receiving process chamber characteristics from the plasma chamber; determining whether one or more variables associated with the process chamber characteristics are within predetermined specification. The method further includes updating a status of the plasma chamber to failure when the chamber characteristics are not within the predetermined specification. The method generates a warning notification when the chamber characteristics are within predetermined specification and when an operation status of the plasma chamber received from a fault detection system indicates a failure.

Methods and systems for chamber matching and monitoring

A method and a system for plasma etching are provided. The method includes measuring a first set of plasma etch processing parameters; determining an etch rate; altering the plasma etch processing chamber hardware configuration if the determined etch rate differs from a standard etch rate by more than a predetermined etch rate difference threshold, thereafter repeating the determining and altering until the determined etch rate differs from the standard etch rate by less than the predetermined etch rate difference threshold. The method further includes measuring a critical dimension of an etched feature and altering the etch processing parameters if the measured critical dimension differs from a standard critical dimension by more than a predetermined critical dimension difference threshold, thereafter repeating the determining and altering until the measured critical dimension differs from the standard critical dimension by less than the predetermined critical dimension difference threshold.

A semiconductor substrate processing system includes a processing chamber and a substrate support defined to support a substrate in the processing chamber. The system also includes a plasma chamber defined separate from the processing chamber. The plasma chamber is defined to generate a plasma. The system also includes a plurality of fluid transmission pathways fluidly connecting the plasma chamber to the processing chamber. The plurality of fluid transmission pathways are defined to supply reactive constituents of the plasma from the plasma chamber to the processing chamber. The system further includes an electrode disposed within the processing chamber separate from the substrate support. The system also includes a power supply electrically connected to the electrode. The power supply is defined to supply electrical power to the electrode so as to liberate electrons from the electrode into the processing chamber.

E-beam enhanced decoupled source for semiconductor processing

A semiconductor substrate processing system includes a processing chamber and a substrate support defined to support a substrate in the processing chamber. The system also includes a plasma chamber defined separate from the processing chamber. The plasma chamber is defined to generate a plasma. The system also includes a plurality of fluid transmission pathways fluidly connecting the plasma chamber to the processing chamber. The plurality of fluid transmission pathways are defined to supply reactive constituents of the plasma from the plasma chamber to the processing chamber. The system further includes an electron injection device for injecting electrons into the processing chamber to control an electron energy distribution within the processing chamber so as to in turn control an ion-to-radical density ratio within the processing chamber. In one embodiment, an electron beam source is defined to transmit an electron beam through the processing chamber above and across the substrate support.

A top plate assembly is positioned above and spaced apart from the substrate support, such that a processing region exists between the top plate assembly and the substrate support. The top plate assembly includes a central plasma generation microchamber and a plurality of annular-shaped plasma generation microchambers positioned in a concentric manner about the central plasma generation microchamber. Adjacently positioned ones of the central and annular-shaped plasma generation microchambers are spaced apart from each other so as to form a number of axial exhaust vents therebetween. Each of the central and annular-shaped plasma generation microchambers is defined to generate a corresponding plasma therein and supply reactive constituents of its plasma to the processing region between the top plate assembly and the substrate support.

Semiconductor processing system with source for decoupled ion and radical control

A method for etching an etch layer disposed over a substrate and below an antireflective coating (ARC) layer and a patterned organic mask with mask features is provided. The substrate is placed in a process chamber. The ARC layer is opened. An oxide spacer deposition layer is formed. The oxide spacer deposition layer on the organic mask is partially removed, where at least the top portion of the oxide spacer deposition layer is removed. The organic mask and the ARC layer are removed by etching. The etch layer is etched through the sidewalls of the oxide spacer deposition layer. The substrate is removed from the process chamber.

Growing community of inventors

San Jose, CA, United States of America

Jun Shinagawa