Performance characterization of freeform finished surfaces of potassium dihydrogen phosphate using fluid jet polishing with a nonaqueous slurry
Why this work is in the frame
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Bibliographic record
Abstract
Potassium dihydrogen phosphate (KDP) and its deuterated analog (DKDP) are unique nonlinear optical materials for high power laser systems. They are used widely for frequency conversion and polarization control by virtue of the ability to grow optical-quality crystals at apertures suitable for fusion-class laser systems. Existing methods for freeform figuring of KDP/DKDP optics do not produce surfaces with sufficient laser-induced-damage thresholds (LIDT's) for operation in the ultraviolet portion of high-peak-power laser systems. In this work, we investigate fluid jet polishing (FJP) using a nonaqueous slurry as a sub-aperture finishing method for producing freeform KDP surfaces. This method was used to selectively polish surface areas to different depths on the same substrate with removals ranging from 0.16 μm to 5.13 μm. The finished surfaces demonstrated a slight increase in roughness as the removal depth increased along with a small number of fracture pits. Laser damage testing with 351 nm, 1 ns pulses demonstrated excellent surface damage thresholds, with the highest values in areas devoid of fracture pits. This work demonstrates, for the first time, a method that enables fabrication of a waveplate that provides tailored polarization randomization that can be scaled to meter-sized optics. Furthermore, this method is based on FJP technology that incorporates a nonaqueous slurry specially designed for use with KDP. This novel nonaqueous FJP process can be also used for figuring other types of materials that exhibit similar challenging inherent properties such as softness, brittleness, water-solubility, and temperature sensitivity.
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Full frame distilled prediction
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it