Applied Materials, Inc.

Apple Inc.

Amazon Technologies, Inc.

Fei Wu

Abdul Aziz Khaja

Ganesh Balasubramanian

Vinay K Prabhakar

Sungwon Ha

Jun Ma

Jian Li

Shizhe Shen

Mark N Gamadia

Rahul Raghavendra Huilgol

Hyung Je Woo

Yutong Zhang

Indu Thangakrishnan

Anirudh Subramanian

Christopher Cade Daniel

Ajay Paidi

Akhil Mehra

Can Karakus

Luis Alves Pereira Quintela

Exemplary processing methods may include forming a plasma of a cleaning precursor in a remote region of a semiconductor processing chamber. The methods may include flowing plasma effluents of the cleaning precursor into a processing region of the semiconductor processing chamber. The methods may include contacting a substrate support with the plasma effluents for a first period of time. The methods may include lowering the substrate support from a first position to a second position while continuing to flow plasma effluents of the cleaning precursor. The methods may include cleaning the processing region of the semiconductor processing chamber for a second period of time.

Chamber configurations and processes for particle control

Automatic partitioning of a machine learning model may be performed for training across multiple processing devices. A training job for a machine learning model may specify a number of partitions for a machine learning model. An optimization parameter may be determined for the machine learning model. Different partitions of the machine learning model to be trained across multiple processing devices may be determined based on the specified number of partitions and the optimization parameter. A schedule for executing the training job may be generated according to the respective partitions of the machine learning model. The training job may be executed according to the schedule.

Automatic partitioning of machine learning models for training across multiple devices

A processing system comprises a chamber body, a substrate support and a lid assembly. The substrate support is located in the chamber body and comprises a first electrode. The lid assembly is positioned over the chamber body and defines a processing volume. The lid assembly comprises a faceplate, a second electrode positioned between the faceplate and the chamber body, and an insulating member positioned between the second electrode and the processing volume. A power supply system is coupled to the first electrode and the faceplate and is configured to generate a plasma in the processing volume.

Process chamber with reduced plasma arc

A substrate support is disclosed. The substrate support has a dielectric body with a plurality of features formed thereon. A ledge surrounds the plurality of features about a periphery thereof. The features increase in number from a central region of the substrate support towards the ledge. A seasoning layer is optionally disposed on the dielectric body.

High temperature electrostatic chuck

Optical characteristics of an optical component for a high volume manufacture consumer electronics device can be tested using a test chart composed of a superposition of two or more groups of parallel line pairs, wherein all the groups of parallel line pairs are oriented at a different inclination. The groups of line pairs could be oriented so that they are perpendicular to each other. A test system can quickly and objectively assess for example the sharpness of the optical component in different directions across a full image field of view of an imaging system that is capturing a digital image of the chart using the optical component for through-the-lens imaging. Other embodiments are also described and claimed.

Line pair based full field sharpness test

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Sunnyvale, CA, United States of America

Fei Wu