Intense sub-terahertz radiation from wide-bandgap semiconductor based large-aperture photoconductive antennas pumped by UV lasers
Bibliographic record
Abstract
Abstract The characteristics of terahertz (THz) radiation generated from large-aperture photoconductive antennas (LAPCAs) were investigated. The antennas were fabricated using different wide-bandgap semiconductor crystals (ZnSe, GaN, 6H–SiC, 4H–SiC and β–Ga2O3) as the substrate. We used an amplified sub-picosecond KrF excimer laser for illumination of the LAPCAs. THz emission scaling was studied as a function of the bias field and the pump laser energy. It was found that the radiated THz energy scales quadratically as a function of the bias field and sub-linearly as a function of the optical fluence for most of the substrates. Further, we demonstrate that SiC, and especially 4H–SiC LAPCAs offer the best THz generation performances. In order to generate intense THz radiation, we fabricated both 6H- and 4H–SiC LAPCAs with an interdigitated structure. From the field autocorrelation trace, it was found that the spectra lie in the sub-THz regime, extending up to 400 GHz, with a peak frequency at 50 GHz, making the bridge between the microwaves band and the THz band. The maximum generated THz energy was 11 μJ, which is to date the highest THz energy measured from LAPCA sources, with a corresponding peak electric field of 115 kV cm−1 and a corresponding ponderomotive potential of 60 eV. Nonlinear THz experiments were performed using these energetic THz pulses, and open aperture Z-scan experiments in an n-doped InGaAs layer revealed a transmission enhancement of 1.7. It was also shown that in order to have efficient THz generation, the energy contrast of the laser must be kept high.
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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) | 0.001 | 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".