An Immobilized Ortho-Palladated Dimethylbenzylamine Complex as an Efficient Catalyst for the Methanolysis of Phosphorothionate Pesticides
Bibliographic record
Abstract
The methanolysis of a series of P=S phosphorothionate pesticides (fenitrothion, coumaphos, diazinon, and dichlofenthion) catalyzed by an ortho-palladated complex covalently attached to two different solid supports, macroporous polystyrene and amorphous silica gel, was studied. Both the polystyrene and the silica-based catalysts showed excellent activity in methanol near neutral pH (neutral s(s)pH = 8.38) at ambient temperature. These heterogeneous catalysts can be readily recovered and reused without significant loss of activity. Fifty milligrams of the silica-supported catalyst SiPd1 offered an acceleration of up to 8.6 x 10(9)-fold for the methanolysis of fenitrothion (2) over the methoxide-promoted background reaction at s(s)pH = 8.8. For the same reaction, 50 mg of polystyrene-supported complex PSPd2 provided a 3.7 x 10(9)-fold acceleration at s(s)pH = 8.8. When accounting for the amount of palladium in the solid, the slight superiority of silica over polystyrene as a solid support is believed to be a result of several possible factors including a higher concentration of active sites accessible to the reaction solvent and a more hydrophilic surface environment that allows better interaction of the methanol solvent with the attached palladacycle. Unlike the behavior in homogeneous solution, the rate of methanolysis of the substrates catalyzed by the solid catalysts was relatively insensitive to the nature of the substrate, probably indicating that a mass transport process is rate limiting. The solid-supported materials effectively decompose malathion at roughly stoichiometric ratios, but they are strongly inhibited by the thiol product resulting from the cleavage of the P=S(SR) linkage.
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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 | 0.000 | 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".