Low temperature reaction kinetics inside an extended Laval nozzle : REMPI characterization and detection by broadband rotational spectroscopy
Bibliographic record
Abstract
The importance of reaction kinetics at low temperatures cannot be overstated, for its impact on human understanding of atmospheric and astrochemical environments is fundamental. Bringing the study of these interactions from nature into a controlled laboratory setting where they can be measured is no simple feat. The coupling of CRESU (a French acronym, cinetique de reaction en ecoulement supersonique uniforme or "Reactions Kinetics in Uniform Supersonic Flow") with the revolutionary Chirped-Pulse Fourier Transform Microwave Spectroscopy (CP-FTMW) method forming what has been dubbed CPUF (Chirped-Pulse/ Uniform Flow) has allowed just this to occur. A cold, uniform column of gas is obtained via the use of a Laval nozzle and measured using CP- FTMW. Instrumental sensitivity is best achieved at low temperature and pressure conditions for this setup, but obtaining and maintaining these conditions is experimentally challenging. Sampling methods such as airfoil and skimmer have been used previously by the Suits group and others. Here, a new solution, a Laval nozzle extension, was developed and implemented. Reactions take place within the nozzle, after which a second expansion occurs. This shock-free secondary expansion provides a low-density region of gas to examine, ideal for CP-FTMW detection. The flow resulting from this expansion from the nozzle extension was characterized via resonance enhanced multi-photon ionization (REMPI). This approach was then applied to the reactions, HCO + NO and HCO + O2, with their rate coefficients being measured for the first time under low temperature conditions. This thesis describes the development and use of that nozzle as well as relevant experimental and theoretical data necessary in its 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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".