Applied Materials, Inc.

Bindusagar Marath Sankarathodi

Patricia M Liu

Ala Moradian

Zuoming Zhu

Zhiyuan Ye

Errol Antonio C Sanchez

Surendra Singh Srivastava

Schubert S Chu

Flora Fong-Song Chang

Jenny Lin

Enle Choo

Maxim Shaposhnikov

Shu-Kwan Danny Lau

Zhepeng Cong

Martin A Hilkene

Vilen K Nestorov

Dayal Ramachandran

Stephen Moffatt

Abhilash J Mayur

Kartik Bhupendra Shah

Wolfgang R Aderhold

Nyi O Myo

Errol C Sanchez

Saurabh Chopra

Kartik Santhanam

Jyothi Rajeevan

Amritha Rammohan

Eugene Lobanov

Balakrishnam R Jampana

Avinash Shervegar

Boris Axelrod

Methods for detection using optical emission spectroscopy in which an optical signal is delivered from the process chamber to an optical emission spectrometer (OES). The OES identifies emission peaks of photons, which corresponds to the optical intensity of radiation from the photons, to determine the concentrations of each of the precursor gases and reaction products. The OES sends input signals of the data results to a controller. The controller can adjust process variables within the process chamber in real time during deposition based on the comparison. In other embodiments, the controller can automatically trigger a process chamber clean based on a comparison of input signals of process chamber residues received before the deposition process and input signals of process chamber residues received after the deposition process.

Methods for detection using optical emission spectroscopy

Embodiments disclosed herein include methods of processing substrates in a tool. In an embodiment, the method of processing the substrate in the tool, comprises receiving an augmented recipe with a machine learning (ML) and/or an artificial intelligence (AI) module. In an embodiment, the augmented recipe comprises, a recipe for processing the substrate in the tool, and a matrix identifier that corresponds to one or more substrate properties. In an embodiment the method further comprises using the ML and/or AI module to retrieve a data set from a database, where the data set is associated with the matrix identifier, and using the ML and/or AI module to modify the augmented recipe to form a modified recipe, where the modification is dependent on the data set.

Coded substrate material identifier communication tool

An apparatus for controlling temperature profile of a substrate within an epitaxial chamber includes a bottom center pyrometer and a bottom outer pyrometer to respectively measure temperatures at a center location and an outer location of a first surface of a susceptor of an epitaxy chamber, a top center pyrometer and a top outer pyrometer to respectively measure temperatures at a center location and an outer location of a substrate disposed on a second surface of the susceptor opposite the first surface, a first controller to receive signals, from the bottom center pyrometer and the bottom outer pyrometer, and output a feedback signal to a first heating lamp module that heats the first surface based on the measured temperatures of the first surface, and a second controller to receive signals, from the top center pyrometer, the top outer pyrometer, the bottom center pyrometer, and the bottom outer pyrometer, and output a feedback signal to a second heating lamp module that heats the substrate based on the measured temperatures of a substrate and the measured temperatures of the first surface.

Temperature profile measurement and synchronized control on substrate and susceptor in an epitaxy chamber

A method for processing a substrate within a processing chamber comprises receiving a first radiation signal corresponding to a film on a target element disposed within the processing chamber, analyzing the first radiation signal, and controlling the processing of the substrate based on the analyzed first radiation signal. The processing chamber includes a substrate support configured to support the substrate within a processing volume and a controller coupled to a first sensing device configured to receive the first radiation signal.

Substrate processing monitoring

Systems, apparatus, and methods are disclosed for foreline diagnostics and control. A foreline coupled to a chamber exhaust is instrumented with one or more sensors, in some embodiments placed between the chamber exhaust and an abatement system. The one or more sensors are positioned to measure pressure in the foreline as an indicator of conductance. The sensors are coupled to a trained machine learning model configured to provide a signal when the foreline needs a cleaning cycle or when preventive maintenance should be performed. In some embodiments, the trained machine learning predicts when cleaning or preventive maintenance will be needed.

Method and system for foreline deposition diagnostics and control

Aspects generally relate to methods, systems, and apparatus for conducting a calibration operation for a plurality of mass flow controllers (MFCs) of a substrate processing system. In one aspect, a corrected flow curve is created for a range of target flow rates across a plurality of setpoints. In one implementation, a method of conducting a calibration operation for a plurality of mass flow controllers (MFCs) of a substrate processing system includes prioritizing the plurality of MFCs for the calibration operation. The prioritizing includes determining an operation time for each MFC of the plurality of MFCs, and ranking the plurality of MFCs in a rank list according to the operation time for each MFC. The method includes conducting the calibration operation for the plurality of MFCs according to the rank list and during an idle time for the substrate processing system.

Methods, systems, and apparatus for conducting a calibration operation for a plurality of mass flow controllers (MFCs) of a substrate processing system

Display screen or portion thereof with graphical user interface

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San Jose, CA, United States of America

Bindusagar Marath Sankarathodi