The Sulfur Rich Fluorothiophosphate Dianions [S<sub>5</sub>P<sub>2</sub>F<sub>2</sub>]<sup>2−</sup> and [S<sub>3</sub>PF]<sup>2−</sup> : Cluster and Chelation Control of P‐S Heterolysis
Bibliographic record
Abstract
Abstract The sulfur rich difluoropentathiodiphosphate dianion [S5P2F2]2−, from fluoride addition to P4S10, has a somewhat checkered history and proves to be the main product of the reaction in acetonitrile. Its optimized synthesis, and structural characterization, as either a tetraphenylphosphonium or a tetrapropylammonium salt, [NnPr4]2[S5P2F2] allows for the first coordination chemistry for this dianion. Reactions of [S5P2F2]2− with d10 metal ions of zinc(II), and cadmium(II), and d9 copper(II) resulted in a surprising diverse array of binding modes and structural motifs. In addition to the simple bis‐chelate coordination of [S5P2F2]2− with zinc, cleavage of the P−S bond resulted in complexes with the unusual [S3PF]2− fluorotrithiophosphate dianion. This was observed in two cluster complexes: a trinuclear cadmium complex with mixed [S5P2F2]2−/[S3PF]2− ligands, [Cd3(S5P2F2)3(S3PF)2]4− as well as an octanuclear copper cluster, [Cu8(S3PF)6]4− which form rapidly at room temperature. These new metal/sulfur/ligand clusters are of relevance to understanding multimetal binding to metallothionines, and to potential capping strategies for the condensed nanoparticulate cadmium chalcogenide semiconductors CdS and CdSe.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.001 | 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".