Bibliographic record
Abstract
Extreme Ultraviolet (EUV) lithography is the leading candidate of the next generation lithography technology.To date, insufficient source power remains a critical issue for the High Volume Manufacturing (HVM) of EUV lithography.Z-pinch is an efficient method for producing the 13.5 nm EUV radiation.However, it is inherently susceptible to Magneto-Rayleigh-Taylor (MRT) instabilities, which causes the non-uniformity of the EUV radiation and degrades the output.In this thesis, both experimental and numerical investigations on the Z-pinch dynamics of an gas jet type Xenon ( Xe) Discharge Produced Plasma (DPP) EUV source are presented.The EUV radiation characteristics, time-resolved visible plasma imaging, time-integrated EUV pinhole imaging, electron density evolution, and ion kinetics in decay phase are studied experimentally.The EUV radiation fluctuation caused by MRT instability with a wavelength 1 mm is observed by EUV pinhole imaging.To investigate the Z-pinch dynamics and the MRT instabilities in the DPP EUV source, a Magneto-Hydrodynamics (MHD) code is developed.Important plasma parameters for Z-pinch (e.g.electron density and electron temperature) are simulated.The evolutions of MRT instabilities with single mode, multi-mode and random mode initial perturbations are presented.The simulation shows that MRT instabilities tend to converge to a mm-scale wavelength around 1 mm, in consistence with experimental result.The MRT instabilities will cause the electron density and temperature fluctuations along Z axis at pinch stagnation, which finally lead to the non-uniformity of the EUV radiation.Preferred initial conditions and possible MRT mitigation methods are also proposed to optimize the EUV source.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".