Applied Materials, Inc.

Globalfoundries Inc.

Asml Masktools B.v.

Tamer Coskun

Jang Fung Chen

Azat M Latypov

Thomas L Laidig

Hwan J Jeong

Yi Zou

Wei-Long Wang

Qin Zhong

Aidyn Kemeldinov

Sangbong Park

Uwe Hollerbach

Chung-Shin Kang

Gabriel Berger

Muhammet Poyraz

Pacha Mongkolwongrojn

Todd P Lukanc

Lei Sun

Ryan Ryoung-Han Kim

Wenhui Wang

Moshe E Preil

Bernd Geh

Rudolf C Brunner

Christopher Heinz Clifford

SangBong Park

Yen-Shuo Lin

Ting Chen

Douglas Joseph Van Den Broeke

The present disclosure generally relates to photolithography systems, and methods for correcting positional errors in photolithography systems. When a photolithography system is first started, the system enters a stabilization period. During the stabilization period, positional readings and data, such as temperature, pressure, and humidity data, are collected as the system prints or exposes a substrate. A model is created based on the collected data and the positional readings. The model is then used to estimate errors in subsequent stabilization periods, and the estimated errors are dynamically corrected during the subsequent stabilization periods.

Model based dynamic positional correction for digital lithography tools

Embodiments described herein relate to a system, methods, and non-transitory computer-readable mediums that accurately align subsequent patterned layers in a photoresist utilizing a deep learning model and utilizing device patterns to replace alignment marks in lithography processes. The deep learning model is trained to recognize unique device patterns called alignment patterns in the FOV of the camera. Cameras in the lithography system capture images of the alignment patterns. The deep learning model finds the alignment patterns in the field of view of the cameras. An ideal image generated from a design file is matched with the camera with respect to the center of the field of view of the camera. A shift model and a rotation model are output from the deep learning model to create an alignment model. The alignment model is applied to the currently printing layer.

Deep learning based adaptive alignment precision metrology for digital overlay

Embodiments of the present disclosure relate to a system, a software application, and a method of a lithography process to update one or more of a mask pattern, maskless lithography device parameters, lithography process parameters utilizing a file readable by each of the components of a lithography environment. The file readable by each of the components of a lithography environment stores and shares textual data and facilitates communication between of the components of a lithography environment such that the mask pattern corresponds to a pattern to be written is updated, the maskless lithography device of the lithography environment is calibrated, and process parameters of the lithography process are corrected for accurate writing of the mask pattern on successive substrates.

Universal metrology file, protocol, and process for maskless lithography systems

Systems and methods disclosed are generally related to masklessly developing connections between a chip-group and a design connection point on a substrate. In placement of the chip-group on the substrate, according to certain embodiments the chip-group may be dispositioned relative to an expected position per a substrate layout design, causing a connection misalignment with the design connection point. According to certain embodiments, a machine learning (ML) model is trained on historical and simulated pixel models of chip-group connections and design connection points. Upon determining the chip-group misalignment by a metrology measurement, the trained ML model determines a pixel model to connect the misaligned chip-group, and causes the pixel model to be exposed to a substrate with a digital lithography tool, thereby connecting the dispositioned chip-group to the design connection point.

Overlaying on locally dispositioned patterns by ML based dynamic digital corrections (ML-DDC)

Methods and systems are provided that, in some embodiments, print and process a layer. The layer can be on a wafer or on an application panel. Thereafter, locations of the features that were actually printed and processed are measured. Based upon differences between the measured differences and designed locations for those features at least one distortion model is created. Each distortion model is inverted to create a corresponding correction model. When there are multiple sections, a distortion model and a correction model can be created for each section. Multiple correction models can be combined to create a global correction model.

Freeform distortion correction

In one embodiment, a method for creating a forecasting model for a multiple-imaging unit DLT is disclosed. A stage of the DLT is positioned so that a set of alignment marks provided on a substrate are placed under a set of the DLT's eyes. For each alignment mark in the set, a first image is acquired using a camera coupled to the eye above it at a first time, and a first position of the alignment mark is obtained within the camera's FOV from the first image, to determine a first measured position. One or more additional images of the alignment mark are subsequently obtained at subsequent times, and one or more corresponding subsequent measured positions are determined. Differences between sequential ones of the measured positions are respectively calculated, a forecasting model to correct for eye center drift of the set of eyes is created, and corrections digitally applied.

Learning based digital corrections to compensate variations on lithography systems with multiple imaging units

A method of aligning a plate containing a substrate is disclosed wherein multiple cameras with distinct fields of view are aligned with mark cells that are within the field of view of each of the multiple cameras.

Self aligning systems and methods for lithography systems

Methods are provided that, in some embodiments that provide alignment of a first layer of a printing plate on a chuck. For example, in one embodiment, images of reference marks on a chuck are captured to determine the initial positions of the reference marks on the chuck. A reference model is created from those initial positions. Images of alignment marks on a reference plate are captured and the locations of the alignment marks are determined. A reference plate model is created from the positions of the alignment marks. A mapping model is then created from the reference model and the reference plate model.

Exposure system alignment and calibration method

In one embodiment of the invention, a method for correcting a pattern placement on a substrate is disclosed. The method begins by detecting three reference points for a substrate. A plurality of sets of three die location points are detected, each set indicative of an orientation of a die structure, the plurality of sets include a first set associated with a first dies and a second set associated with a second die. A local transformation is calculated for the orientation of the first die and the second on the substrate. Three orientation points are selected from the plurality of sets of three die location points wherein the orientation points are not set members of the same die. A first global orientation of the substrate is calculated from the selected three points from the set of points and the first global transformation and the local transformation for the substrate are stored.

Method of pattern placement correction

Methods are provided and generally relate to adjusting exposure parameters of a substrate in response to an overlay error. The method includes partitioning the substrate into one or more sections. Each section corresponds to an image projection system. A total overlay error of a first layer deposited on the substrate is determined. For each section, a sectional overlay error is calculated. For each overlap area, in which two or more sections overlap, an average overlay error is calculated. The exposure parameters are adjusted in response to the total overlay error.

Piecewise alignment modeling method

Methods and apparatuses are provided that determine an offset between actual feature/mark locations and the designed feature/mark locations in a maskless lithography system. For example, in one embodiment, a method is provided that includes opening a camera shutter in a maskless lithography system. Light is directed from a configuration of non-adjacent mirrors in a mirror array towards a first substrate layer. An image of the first substrate layer on a camera is captured and accumulated. Light is directed and images are captured repeatedly using different configurations of non-adjacent mirrors to cover an entire field-of-view (FOV) of the camera on the first substrate layer. Thereafter, the camera shutter is closed and the accumulated image is stored in memory.

Image improvement for alignment through incoherent illumination blending

Methods for fabricating integrated circuits are provided. In one example, a method includes providing a circuit structure layer over a substrate and at least one etch layer over the circuit structure layer, in the at least one etch layer patterning at least one primary pattern feature having at least one primary pattern feature dimension and at least one assist pattern feature having at least one assist pattern feature dimension, where the primary pattern feature dimension is greater than the assist pattern feature dimension, reducing the at least one primary pattern feature dimension and closing the assist pattern feature to form an etch pattern, and etching a circuit structure feature using the etch pattern.

Shrink process aware assist features

Embodiments disclosed herein generally relate to adjusting exposure parameters of a substrate in response to an overlay error. The method includes partitioning the substrate into one or more sections. Each section corresponds to an image projection system. A total overlay error of a first layer deposited on the substrate is determined. For each section, a sectional overlay error is calculated. For each overlap area, in which two or more sections overlap, an average overlay error is calculated. The exposure parameters are adjusted in response to the total overlay error.

Growing community of inventors

San Jose, CA, United States of America

Tamer Coskun