Predictive Systematic Error Correction in Gas Cluster Ion Beam Processing
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Solution Overview
Problem
In semiconductor manufacturing, gas cluster ion beam (GCIB) technology faces challenges in correcting systematic errors and non-uniformities on workpieces, particularly due to equipment-specific process anomalies, which are costly and time-intensive to address using sacrificial workpieces.
Innovation Solution
A predictive method is employed to correct systematic errors during GCIB location-specific processing by collecting parametric data, determining a predicted systematic error response, and spatially modulating the applied properties of the GCIB based on this data to achieve a target profile on the workpiece.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If sacrificial workpieces are used to determine systematic error for GCIB processing, then the corrective capability is improved, but the cost and time consumption increase
Solution Approach 1:
The patent creates a predictive model of systematic error in advance by processing sacrificial workpieces and storing the error patterns. This preliminary characterization allows the model to predict and compensate for systematic errors during actual production processing without requiring additional sacrificial workpieces for each batch, thus resolving the contradiction between improved corrective capability and reduced time consumption
Solution Approach 2:
The patent uses a computational model that replicates the systematic error patterns observed from sacrificial workpieces. This virtual copy of the error behavior can be applied to correct actual workpieces without physically consuming additional sacrificial materials, thereby maintaining high corrective capability while eliminating the ongoing time and material costs
2Reliability
If sacrificial workpieces are used to determine systematic error for GCIB processing, then the corrective capability is improved, but the cost increases
Solution Approach 1:
The patent performs systematic error characterization once using sacrificial workpieces to build a predictive model, then reuses this model for unlimited subsequent corrections. This preliminary investment converts variable costs (sacrificial workpieces for each batch) into a fixed cost (one-time model creation), improving corrective capability while reducing ongoing material costs to near zero
Solution Approach 2:
The patent creates a digital replica of systematic error behavior through computational modeling. This virtual model can be applied indefinitely without consuming additional physical sacrificial workpieces, thereby maintaining high corrective capability while eliminating recurring material costs
3Manufacturing precision
If spatially modulated GCIB processing is applied, then the manufacturing precision is improved, but the device complexity increases
Solution Approach 1:
The patent applies different GCIB processing parameters (dose, scan speed, energy) to different spatial locations on the workpiece based on the predictive error model. This location-specific processing compensates for position-dependent systematic errors, achieving high manufacturing precision through localized parameter adjustment without requiring complex hardware modifications
Solution Approach 2:
The patent dynamically adjusts GCIB processing parameters during scanning based on real-time position information and the predictive error model. The scan speed and dose are continuously modulated as functions of position to compensate for systematic errors, achieving high precision through dynamic control rather than static, complex hardware solutions
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 enhances the corrective capability of GCIB processing, reducing the difference between the target and actual profiles, and allows for adaptive adjustment of processing parameters to improve uniformity and precision in feature height control.
Implementation Method 1
The gas clusters can be ionized by electron bombardment, which permits the gas clusters to be accelerated using an electric field to form directed beams of controllable beam energy
Implementation Method 2
The gas clusters can be ionized by electron bombardment, which permits the gas clusters to be accelerated using an electric field to form directed beams of controllable beam energy
Implementation Method 3
Gas cluster ion beam (GCIB) technology has been demonstrated as a useful processing technique for modifying, etching, cleaning, smoothing, and forming thin films on workpieces
Data Source
AI summary
A method of modifying an upper layer of a workpiece using a gas cluster ion beam (GCIB) is described. The method includes collecting parametric data relating to an upper layer of a workpiece, and determining a predicted systematic error response for applying a GCIB to the upper layer to alter an initial profile of a measured attribute by using the parametric data. Additionally, the method includes identifying a target profile of the measured attribute, directing the GCIB toward the upper layer of the workpiece, and spatially modulating an applied property of the GCIB, based at least in part on the predicted systematic error response and the parametric data, as a function of position on the upper layer of the workpiece to achieve the target profile of the measured attribute.