Applied Materials, Inc.

Michael Nichols

Tina Dhekial-Phukan

Shahid Rauf

Ajit Balakrishna

Sunil Srinivasan

Jason Andrew Kenney

Chung Liu

Venkata Ravishankar Kasibhotla

Kuan-Ting Liu

Sanggyum Kim

Shahab Arabshahi

Shreeram Jyoti Dash

Deyang Li

Aaron Eppler

Yi-Chuan Chou

Olivier P Joubert

Embodiments of the present disclosure generally relate to a system used in a semiconductor device manufacturing process. More specifically, embodiments provided herein generally include apparatus and methods for synchronizing and controlling the delivery of an RF bias signal and a pulsed voltage waveform to one or more electrodes within a plasma processing chamber. The apparatus and methods disclosed herein can be useful to at least minimize or eliminate a microloading effect created while processing small dimension features that have differing densities across various regions of a substrate. The plasma processing methods and apparatus described herein are configured to improve the control of various characteristics of the generated plasma and control an ion energy distribution (IED) of the plasma generated ions that interact with a surface of a substrate during plasma processing. The ability to synchronize and control waveform characteristics of a voltage waveform bias established on a substrate during processing allows for an improved control of the generated plasma and process of forming, for example, high-aspect ratio features in the surface of the substrate by a reactive ion etching process. As a result, greater precision for plasma processing can be achieved, which is described herein in more detail.

Reducing aspect ratio dependent etch with direct current bias pulsing

Methods and systems for processing substrates are provided. The system can include: a processing chamber configured to process a substrate based on a recipe; a plurality of sub-systems in operable communication with the processing chamber for controlling corresponding parameters associated with processing the substrate; and a controller in operable communication with the processing chamber and each of the plurality of sub-systems and configured to control each of the plurality of sub-systems and the processing chamber using information included in the recipe and feedback provided by at least one of the plurality of sub-systems. The controller is configured to compare information included in the recipe and feedback provided by at least one of the plurality of sub-systems with stored empirical information relating to the recipe and each of the plurality of sub-systems, and adjust at least one of the corresponding parameters associated with processing the substrate based on a determined comparison.

Method and apparatus for controlling a processing reactor

System and methods of improving dynamic pressure response during recipe step transitions. An exemplary method may include changing at least one of a plurality of recipe parameters in accordance with a processing recipe while running the processing recipe on a semiconductor substrate in a processing chamber. The method may further include measuring a pressure response in the processing chamber responsive to the changing of the at least one of the plurality of recipe parameters, and determining a response error based on the pressure response and a model pressure response calculated based on the processing recipe. The method may further include, in response to determining that the response error may be greater than a threshold value, calculating an adjustment to an operation of a valve downstream of the processing chamber when changing the at least one of the plurality of recipe parameters in accordance with the processing recipe in subsequent runs.

Dynamic pressure control for processing chambers implementing real-time learning

A method of detecting and classifying anomalies during semiconductor processing includes executing a wafer recipe a semiconductor processing system to process a semiconductor wafer; monitoring sensor outputs from a sensors that monitor conditions associated with the semiconductor processing system; providing the sensor outputs to models trained to identify when the conditions associated with the semiconductor processing system indicate a fault in the semiconductor wafer; receiving an indication of a fault from at least one of the models; and generating a fault output in response to receiving the indication of the fault.

Real-time anomaly detection and classification during semiconductor processing

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Sunnyvale, CA, United States of America

Michael Nichols