A Study of Photoresist Pattern Freezing for Double Imaging using 172nm VUV Flood Exposure
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Bibliographic record
Abstract
Numerous alternate processes are under industry wide evaluation as simplifications to current double patterning methods. Reduction in process complexity and cost may be achieved by use of track-based photoresist stabilization methods that eliminate one etch step by allowing a second resist to be patterned over a first resist pattern. Here, we describe studies of 172nm flood UV exposure as one example of a resist stabilization method. When properly implemented, we observe that 172nm stabilization allows superior retention of photoresist profiles vs. longer wavelength UV treatment. For the commercial 193nm photoresist studied, judicious choice of 172nm dose and subsequent bake is required for pattern stabilization to second resist processing. FT-IR studies indicate that distinct chemical processes occur during 172nm flood exposure and subsequent bake: 172nm flood exposure appears to cause selective decarboxylation of lactones present in the photoresist, while baking leads to photoacid-mediated loss of blocking groups and other processes that are not conclusively characterized at present. At 800 mJ/cm2 172nm dose, resist patterns are sufficiently stabilized to prevent reflow in the subsequent bake. Approximately 25% volumetric shrinkage accompanies 172nm stabilization. This shrinkage is manifested as controllable CD trimming and thickness loss as well as 3-dimensional resist pattern distortion including line-end tilting and corner bowing. At insufficient 172nm cure doses, photoresist reflow occurs during the subsequent stabilizing bake. 3-Dimensional resist pattern distortions are dramatically larger under these conditions. These findings indicate that shrinkage control during any stabilizing process is a critical factor in resist design for simplified double patterning methods.
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Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
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Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
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