Intra- and Inter-Conduction Band Optical Absorption Processes in\n $\\beta$-Ga$_2$O$_3$
Bibliographic record
Abstract
$\\beta$-Ga$_2$O$_3$ is an ultra-wide bandgap semiconductor and is thus\nexpected to be optically transparent to light of sub-bandgap wavelengths well\ninto the ultraviolet. Contrary to this expectation, it is found here that free\nelectrons in n-doped $\\beta$-Ga$_2$O$_3$ absorb light from the IR to the UV\nwavelength range via intra- and inter-conduction band optical transitions.\nIntra-conduction band absorption occurs via an indirect optical phonon mediated\nprocess with a $1/\\omega^{3}$ dependence in the visible to near-IR wavelength\nrange. This frequency dependence markedly differs from the $1/\\omega^{2}$\ndependence predicted by the Drude model of free-carrier absorption. The\ninter-conduction band absorption between the lowest conduction band and a\nhigher conduction band occurs via a direct optical process at $\\lambda \\sim\n349$ nm (3.55 eV). Steady state and ultrafast optical spectroscopy measurements\nunambiguously identify both these absorption processes and enable quantitative\nmeasurements of the inter-conduction band energy, and the frequency dependence\nof absorption. Whereas the intra-conduction band absorption does not depend on\nlight polarization, inter-conduction band absorption is found to be strongly\npolarization dependent. The experimental observations, in excellent agreement\nwith recent theoretical predictions for $\\beta$-Ga$_2$O$_3$, provide important\nlimits of sub-bandgap transparency for optoelectronics in the deep-UV to\nvisible wavelength range, and are also of importance for high electric field\ntransport effects in this emerging semiconductor.\n
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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".