Inline Material Characterization Using FTIR Spectroscopy and PLS Models
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current semiconductor manufacturing processes face challenges in efficiently monitoring and controlling material characteristics, particularly in complex metallization systems, due to limitations in conventional optical measurement techniques which struggle with gradual variations and material modifications, often requiring destructive analysis and resulting in inefficient process control and significant delays.
Innovation Solution
The implementation of non-destructive measurement techniques, such as Fourier transformed infrared spectroscopy, combined with advanced data analysis methods like partial least square algorithms, allows for the quantitative monitoring of material characteristics during manufacturing, enabling inline measurement and reduced delays by establishing relationships between measurement parameters and material properties.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If conventional optical measurement techniques are used for monitoring material characteristics, then measurement speed is improved, but measurement precision deteriorates due to inability to detect gradual variations and material modifications
Solution Approach 1:
The patent introduces an intermediary computational model that bridges the gap between fast but imprecise optical measurements and the need for precise material characterization. The model uses optical measurement data as input and produces accurate material characteristic outputs by incorporating knowledge from multiple sources including process parameters and material properties, thus resolving the contradiction between speed and precision
Solution Approach 2:
The patent transforms the measurement approach by changing from direct measurement of material characteristics to measurement of optical properties that are then converted to material characteristics through a model. This parameter transformation enables both fast optical measurement and precise material characterization by leveraging the relationship between optical and material properties
2Measurement precision
If destructive analysis techniques are used to accurately determine material characteristics, then measurement precision is improved, but productivity deteriorates due to loss of samples and process delays
Solution Approach 1:
The patent replaces destructive mechanical/chemical analysis methods with non-destructive optical measurement combined with computational modeling. This substitution maintains measurement precision for material characteristics while eliminating sample destruction and associated productivity losses, as the optical method does not require destroying the sample to obtain material property information
3Manufacturing precision
If comprehensive measurement and analysis are performed for each substrate, then manufacturing precision is improved, but loss of time increases due to extended measurement and assessment periods
Solution Approach 1:
The patent performs preliminary action by pre-establishing a computational model that encodes knowledge about material characteristics and their relationship to optical properties and process parameters. This pre-computed model enables rapid assessment of each substrate without requiring time-consuming comprehensive analysis, thus maintaining manufacturing precision while reducing measurement and assessment time
4Manufacturing precision
If advanced process control with detailed monitoring is implemented, then manufacturing precision is improved, but device complexity increases due to additional equipment and measurement systems
Solution Approach 1:
The patent makes the optical measurement system universal by designing it to extract multiple types of information (optical properties, material characteristics, process state) from a single measurement. The computational model serves multiple functions including characterization, process monitoring, and control, thus achieving enhanced manufacturing precision without proportionally increasing device complexity
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 provides enhanced monitoring and control of material characteristics, improving process efficiency and reducing delays in semiconductor manufacturing by enabling quantitative assessment and feedback within the manufacturing environment, thus enhancing overall process quality and productivity.
Implementation Method 1
Fourier transformed infrared spectroscopy
Implementation Method 2
Fourier transformed infrared spectroscopy
Data Source
AI summary
By using powerful data analysis techniques, such as PCR, PLS, CLS and the like, in combination with measurement techniques providing structural information, gradually varying material characteristics may be determined during semiconductor fabrication, thereby also enabling the monitoring of complex manufacturing sequences. For instance, the material characteristics of sensitive dielectric materials, such as ULK material, may be detected, for instance with respect to an extension of a damage zone, in order to monitor the quality of metallization systems of sophisticated semiconductor devices. The inline measurement data may be obtained on the basis of infrared spectroscopy, for instance using FTIR and the like, which may even allow directly obtaining the measurement data at process chambers, substantially without affecting the overall process throughput.