Infrared photocarrier radiometry of semiconductors: Physical principles, quantitative depth profilometry, and scanning imaging of deep subsurface electronic defects
Bibliographic record
Abstract
Laser-induced infrared photocarrier radiometry (PCR) is introduced theoretically and experimentally through deep subsurface scanning imaging and signal frequency dependencies from Si wafers. A room-temperature InGaAs detector $(0.8--1.8\ensuremath{\mu}\mathrm{m})$ with integrated amplification electronics is used instead of the liquid-nitrogen-cooled HgCdTe photodetector $(2--12\ensuremath{\mu}\mathrm{m})$ of conventional photothermal radiometry. PCR measures purely electronic carrier-wave (CW) recombination. The InGaAs detector completely obliterates the thermal-infrared emission band $(8--12\ensuremath{\mu}\mathrm{m}),$ unlike the known photothermal signal types, which invariably contain combinations of carrier-wave and thermal-wave infrared emissions due to the concurrent lattice absorption of the incident beam and nonradiative heating. The PCR theory is presented as infrared depth integrals of CW density profiles. Experimental aspects of this methodology are given, including the determination of photocarrier transport parameters through modulation frequency scans, as well as CW scanning imaging. The PCR coordinate scans at the front surface of $500\ensuremath{-}\ensuremath{\mu}\mathrm{m}$-thick Si wafers with slight back-surface mechanical defects can easily ``see'' and create clear images of the defects at modulation frequencies up to 100 kHz, at laser-beam optical penetration depth $\ensuremath{\sim}1\ensuremath{\mu}\mathrm{m}$ below the surface (at 514 nm). The physics of the contrast mechanism for the nonthermal nature of the PCR signal is described: it involves self-reabsorption of CW-recombination-generated IR photons emitted by the photoexcited carrier-wave distribution depth profile throughout the wafer bulk. The distribution is modified by enhanced recombination at localized or extended defects, even as remote as the back surface of the material. The high-frequency, deep-defect PCR images thus obtained prove that very-near-surface (where optoelectronic device fabrication takes place) photocarrier generation can be detrimentally affected not only by local electronic defects as is commonly assumed, but also by defects in remote wafer regions much deeper than the extent of the electronically active thin surface layer.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".