Unveiling competitions between carrier recombination pathways in semiconductors via mechanical damping
Bibliographic record
Abstract
The total rate of carrier recombination in semiconductors has conventionally been expressed using an additive model, r_total = Σr_i , which rules out the interactions between carrier recombination pathways. Here we challenge this paradigm by demonstrating pathway competitions using our newly developed light-induced mechanical absorption spectroscopy (LIMAS), which allows us to probe genuine recombination dynamics in semiconductors via mechanical damping. We show that the total recombination rate in zinc sulfide (ZnS), a model semiconductor material, follows a multiplicative weighting model, r_total \propto Πr_i ^(w_i) with Σw_i=1. Under both steady-state and switch-on illuminations, the weighting factors w_i for each recombination pathway-direct, trap-assisted, and sublinear-are dictated by the carrier generation mechanism: (i) interband transition favors direct recombination; (ii) single-defect level-mediated generation promotes trap-assisted recombination; (iii) generation involving multiple saturated defect levels gives rise to sublinear recombination. Upon light switch-off, localized state changes drive a dynamic evolution of w_i, altering pathway competitions. These findings reshape our fundamental understanding of carrier dynamics and provide a new strategy to optimize next-generation optoelectronic devices.
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How this classification was reachedexpand
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 | 0.000 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".