Optical Film Reflection Monitoring for Non-LOS Deposition

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Solution Overview

Problem

Conventional methods for monitoring chemical-dose deposition and substrate process results in non-line-of-sight (non-LOS) surfaces are time-consuming and resource-intensive, often requiring destructive techniques like cross-sectional scanning electron microscopy (SEM) or transmission electron microscopy (TEM), which render the substrate unfit for reuse.

Innovation Solution

The development of a substrate monitoring device and system that includes an enclosure structure with a first interior volume to direct mass transport of reactive species to a substrate's surfaces, utilizing machine-learning models (MLMs) to analyze reflected light data, and providing real-time process result predictions on a graphical user interface (GUI).

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If conventional destructive techniques (cross-sectional SEM or TEM) are used to monitor chemical-dose deposition in non-LOS surfaces, then measurement precision is improved, but the substrate is rendered unfit for reuse and the process becomes time-consuming and resource-intensive

Engineering Contradiction:
Improvedeposition monitoring accuracyVSAvoidprocess efficiency
Core Design Contradiction:
Measurement precisionVSProductivity

Solution Approach 1:

The patent replaces destructive mechanical/physical analysis methods (cross-sectional SEM, TEM) with optical detection methods. The system uses light reflection measurements to monitor deposition thickness and uniformity in real-time, eliminating the need for substrate destruction while maintaining measurement precision.

Inventive Principle:
Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The substrate itself serves as the measurement target without requiring external destructive analysis. By measuring light reflection from the substrate surface during the deposition process, the system obtains deposition information directly from the substrate in its functional state, enabling continuous monitoring without removal or destruction.

Inventive Principle:
Principle #25Self-service

2Measurement precision

If conventional metrology techniques are used for process monitoring, then measurement precision is improved, but loss of time and loss of substance increase

Engineering Contradiction:
Improveprocess monitoring accuracyVSAvoidmonitoring time
Core Design Contradiction:
Measurement precisionVSLoss of time

Solution Approach 1:

The system enables continuous real-time monitoring of the deposition process through optical measurements taken during substrate processing. This continuous feedback allows for immediate process adjustments, eliminating the time loss associated with post-process destructive analysis and enabling closed-loop control.

Inventive Principle:
Principle #20Continuity of useful action

Solution Approach 2:

The system performs deposition monitoring during the deposition process itself rather than after completion. By measuring deposition progress in real-time, the system enables preliminary detection of process deviations and immediate correction, preventing time loss from rework or repeated measurements.

Inventive Principle:
Principle #10Preliminary action

3Productivity

If real-time monitoring is implemented, then productivity is improved, but device complexity increases

Engineering Contradiction:
Improveprocess throughputVSAvoidmonitoring system complexity
Core Design Contradiction:
ProductivityVSDevice complexity

Solution Approach 1:

The patent replaces complex destructive analysis equipment (SEM, TEM) with relatively simple optical measurement systems. The use of light reflection measurements and machine learning algorithms provides real-time monitoring capability with simpler, more integrated equipment that can be incorporated into existing substrate processing chambers.

Inventive Principle:
Principle #28Mechanics substitution (Replace mechanical system)

Applied Scientific Principles

This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.

Function Achieved in This Case

Enables non-destructive, efficient monitoring of chemical-dose deposition in non-LOS surfaces, allowing for real-time process adjustments and improving process uniformity and quality without the need for costly and time-consuming metrology techniques.

Implementation Method 1

direct a first mass transport (e.g., chemical diffusion with or without gas-phase convection) of a reactive species

Methodology Applied
Scientific EffectDiffusion: Diffusion

Implementation Method 2

direct a first mass transport (e.g., chemical diffusion with or without gas-phase convection) of a reactive species

Methodology Applied
Scientific EffectConvection: Convection

Implementation Method 3

provide a second mass transport of the reactive species to a second surface of the substrate

Methodology Applied
Scientific EffectDiffusion: Diffusion

Implementation Method 4

provide a second mass transport of the reactive species

Methodology Applied
Scientific EffectGas flow: Convection

Implementation Method 5

receiving, by a processing device, image data characterizing light reflected from a substrate surface

Methodology Applied
Scientific EffectReflection: Reflection

Data Source

PatentUS20250371699A1Chemical-dose substrate deposition monitoring
Publication Date: 2025.12.04 APPLIED MATERIALS INC
  • US20250371699A1 patent drawing
  • US20250371699A1 patent drawing
  • US20250371699A1 patent drawing

AI summary

A method including receiving, by a processing device, image data characterizing light reflected from of a film disposed on a processed surface of a substrate. The image data corresponds to one or more locations across a surface of the film and indicates a camera perspective angle associated with capturing the image data. The method further includes determining, by the processing device using the image data, reflection data indicating reflection effect of the light reflected from the film. The method further includes processing the reflection data using one or more machine-learning model (MLMs). The method further includes determining one or more process result metrics of the film corresponding to the one or more locations. The method may further includes preparing the one or more process result metrics for display on a graphical user interface (GUI). The method may further include preparing the one or more process result metrics for processing in a script-based environment.