Toward ICP‐SIFT mass spectrometry and atomic cation ligation as a probe of relativistic effects—A personal journey
Bibliographic record
Abstract
Abstract The ICP–SIFT mass spectrometer at York University, a derivative of flowing afterglow (FA) and selected‐ion flow tube (SIFT) mass spectrometers, has provided a powerful technique to measure the chemistry and kinetics of atomic cation–molecule reactions. Here, I focus on periodic trends in the kinetics of ligation reactions of atomic ions with small molecules. I examine trends in ammonia ligation kinetics across the first two rows of the atomic transition metal cations and their correlation with ligand bond enthalpies and ligand field stabilization energies. Also explored are trends down Groups 1 and 2 in the kinetics of noncovalent electrostatic ligand bonding and the tendency for s electron solvation of the atomic alkaline‐earth cations with ammonia. Finally, I briefly review trends observed with 12 different ligands in the ligation rate down the periodic table with Group 9–12 transition atomic metal cations. These trends provide a compelling probe for the presence of relativistic effects that influence the strengths of the metal‐ion ligand bonds that are formed. There is a clear third‐row rate enhancement with Ir+, Pt+, Au+, and Hg+, the extent of which depends on the nature of the ligand. This large set of kinetic data provides an unprecedented broad perspective of relativistic effects in ligand bonding. With CS2 as a ligand, the third‐row relativistic effect is apparent in the formation of both the first and the second ligand bond with the Groups 10 and 11 atomic cations as predicted by our quantum chemical calculations of ligation energies.
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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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".