High power continuous wave Nd:KGW laser with low quantum defect diode pumping
Bibliographic record
Abstract
High power diode-pumped solid state (DPSS) lasers are a rapidly growing technology that is attractive for various applications in scientific and industrial fields. DPSS lasers are highly efficient, reliable and durable with superior beam quality when compared to flash-lamp pumped solid state lasers. Double-tungstate crystal of neodymium-doped potassium gadolinium tungstate (Nd:KGW) is one of the most effective active media used in DPSS lasers for generation of continuous wave radiation and ultrashort (i.e. picosecond, 10-12 s) pulses. Unfortunately, the thermal conductivity of KGW host crystals is relatively low (~3 Wm-1K-1). This low thermal conductivity and large quantum defect while pumping with ~808 nm lead to significant thermo-optical distortions. One way to minimize thermo-optical distortions is to reduce the quantum defect. This can be done by pumping at longer wavelengths as compared to conventional 808 nm. In this work we demonstrate what we believe is the first continuous wave Nd:KGW laser with hot band diode pumping at ~910 nm. This pumping wavelength reduced the quantum defect by >46% as compared to the conventional ~808 nm pumping and resulted in significantly lower thermal lensing. The laser produced 2.9 W of average output power at 1067 nm in a diffraction limited beam for an absorbed pump power of 8.3 W. The slope efficiency and optical-to-optical efficiency were found to be 43% and 35%, respectively. Significant reduction of quantum defect offered by this pumping wavelength and availability of suitable high power laser diodes opens an attractive way to further power and efficiency scaling of the Nd:KGW lasers.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".