Curable Composition Simulation Boundary Volume Adjustment
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Solution Overview
Problem
Existing simulation methods for predicting the behavior of a curable composition in film forming processes often result in false recognition due to local increases or decreases in film thickness near the boundary of the prediction target region, leading to inefficiencies and inaccuracies in the adjustment of film forming conditions.
Innovation Solution
A simulation method that determines the volume of specific droplets within a prediction target region based on an index indicating their positional relationship with the boundary, allowing for more accurate prediction of the curable composition's behavior and reducing false recognition by adjusting the simulation volume accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If simulation is performed for the entire region on the substrate, then prediction accuracy is improved, but computation cost increases
Solution Approach 1:
The substrate region is divided into a prediction target region (where droplets are arranged) and a non-prediction region. Simulation is performed only for the prediction target region, reducing computation time while maintaining prediction accuracy for the relevant area.
Solution Approach 2:
Different regions of the substrate are treated differently: the prediction target region undergoes detailed simulation while the non-prediction region is excluded. This local differentiation optimizes computation by focusing resources where they are most needed.
2Loss of time
If simulation is performed for a partial region (prediction target region), then computation cost is reduced, but false recognition occurs due to boundary effects
Solution Approach 1:
The harmful boundary effect is extracted and identified as a separate issue. By recognizing that droplets near the boundary of the prediction target region are affected by the boundary itself, the simulation can apply special handling or exclusion rules for these boundary-affected droplets, removing the source of false recognition.
Solution Approach 2:
The simulation parameters for droplets near the boundary are changed or adjusted. Droplets whose centers are within a predetermined distance from the boundary are identified and handled differently, either by adjusting their initial parameters or by applying correction factors, thereby eliminating the false recognition caused by boundary effects.
3Manufacturing precision
If trial and error adjustment is performed using film forming apparatus, then film formation conditions can be optimized, but enormous time and cost are required
Solution Approach 1:
Simulation is performed in advance to predict droplet behavior and film formation outcomes before actual film forming is attempted. This preliminary virtual experimentation allows conditions to be optimized on computer before physical trial, reducing the time and cost of actual adjustment while maintaining manufacturing precision.
Solution Approach 2:
A virtual copy of the film forming process is created through simulation. Instead of repeatedly performing physical trial and error, the simulation creates a digital replica that can be tested and adjusted indefinitely without consuming materials or time, thereby optimizing conditions efficiently.
Data Source
AI summary
The present invention provides a simulation method of predicting a behavior of a curable composition in a process of bringing a second member into contact with a plurality of droplets of the curable composition arranged on a first member and forming a film of the curable composition on the first member, the method comprising: determining a volume used for predicting the behavior with respect to each of a plurality of specific droplets which are arranged inside a prediction target region for predicting the behavior, among the plurality of droplets, based on an index indicating a positional relationship between a boundary of the prediction target region and each specific droplet; and predicting the behavior of the curable composition inside the prediction target region based on the volume determined with respect to each of the plurality of specific droplets.