Excited-State Processes in Slow Motion: An Experiment in the Undergraduate Laboratory
Bibliographic record
Abstract
Lasers have transformed chemistry and the everyday world. Therefore, it is not surprising that undergraduate chemistry students are frequently exposed to fairly advanced laser techniques. The usual topics studied with lasers are molecular spectroscopy and chemical kinetics. Static and dynamic fluorescence experiments seem to be particularly popular. The phenomenon of phosphorescence, on the other had, has received much less attention in the undergraduate physical chemistry laboratory. A few years ago, we developed a laser experiment that introduced students to the phosphorescence quenching of the carbazole−naphthalene system under steady-state and pulse-excitation conditions. The purpose of that experiment was to demonstrate the experimental and theoretical aspects of triplet−triplet nonradiative energy transfer between two aromatic molecules. Subsequently, we modernized the experiment by introducing an inexpensive and easy-to-use Ocean Optics data acquisition system. This not only greatly simplified the experiment, but also made it more accessible to students. This article presents the upgraded version of the experiment together with suggestions for practical implementation.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".