Substrate Support Heat Transfer Management via ML
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Solution Overview
Problem
Conventional substrate support systems face challenges in precise heat transfer management due to inadequate heat transfer coefficients and non-uniform heating, leading to poor substrate quality and reduced yield.
Innovation Solution
A method that involves identifying property data and target performance data for a substrate support system, using a trained machine learning model to determine heat transfer management data, and configuring the system to achieve precise heat transfer by performing material operations or adjusting zone configurations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If conventional substrate support systems are used, then the system structure is simple, but heat transfer management precision is inadequate and thermal uniformity is poor
Solution Approach 1:
The substrate support system is divided into multiple independently controllable heating zones and cooling zones. Each zone can be controlled separately to achieve precise thermal management across different regions of the substrate, resolving the contradiction between thermal uniformity and system complexity by breaking down the control into manageable segments.
Solution Approach 2:
Different regions of the substrate support system are equipped with different thermal control characteristics - some zones with heating elements, others with cooling channels, and varying thermal conductivities. This local differentiation enables precise heat transfer management in each zone while maintaining overall system feasibility.
2Manufacturing precision
If conventional heating methods are used, then the system is easy to operate, but thermal uniformity across the substrate is non-uniform
Solution Approach 1:
The system dynamically adjusts heating and cooling parameters in real-time based on feedback from temperature sensors. The control system continuously monitors thermal conditions and modifies zone configurations, material operations, and operational parameters to maintain optimal thermal uniformity across the substrate throughout the processing cycle.
Solution Approach 2:
Temperature sensors distributed across the substrate support system provide real-time feedback to the control system. This feedback enables closed-loop control where thermal conditions are continuously monitored and adjusted, ensuring substrate thermal uniformity while automating the complexity of thermal management.
3Manufacturing precision
If expensive specialized equipment is used to achieve precise heat transfer, then thermal uniformity improves, but system cost increases
Solution Approach 1:
The substrate support system performs multiple functions within a single integrated structure - heating, cooling, substrate positioning, and thermal sensing. This multi-functionality achieves precise heat transfer management without requiring multiple separate expensive equipment components, thereby reducing overall system cost while maintaining thermal precision.
Solution Approach 2:
The system achieves precise heat transfer management by adjusting operational parameters such as heating power, cooling flow rates, and zone configurations rather than requiring expensive hardware modifications. This parameter-based control enables flexible thermal management at lower system cost.
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
This approach enables more precise heat transfer management, improving substrate thermal uniformity, enhancing substrate quality, and increasing yield while reducing the need for expensive equipment.
Implementation Method 1
heat transfer management of the substrate support system
Implementation Method 2
heat transfer management data indicative of an amount of material to be added to or removed from the substrate support system
Data Source
AI summary
A method includes: identifying property data associated with a substrate support system; identifying target performance data associated with the substrate support system; and causing, based on the property data and the target performance data, heat transfer management of the substrate support system.