Shining Light on the Light-Bearing Element: A Brief Review of Photomediated C–H Phosphorylation Reactions
Bibliographic record
Abstract
Abstract Organophosphorus compounds have numerous useful applications, from versatile ligands and nucleophiles in the case of trivalent organophosphorus species to therapeutics, agrochemicals and material additives for pentavalent species. Although phosphorus chemistry is a fairly mature field, the construction of C–P(V) bonds relies heavily on either prefunctionalized substrates such as alkyl or aryl halides, or requires previously oxidized bonds such as C=N or C=O, leading to potential sustainability issues when looking at the overall synthetic route. In light of the recent advances in photochemistry, using photons as a reagent can provide better alternatives for phosphorylations by unlocking radical mechanisms and providing interesting redox pathways. This review will showcase the different photomediated phosphorylation procedures available for converting C–H bonds into C–P(V) bonds. 1 Introduction 1.1 Organophosphorus Compounds 1.2 Phosphorylation: Construction of C–P(V) Bonds 1.3 Photochemistry as an Alternative to Classical Phosphorylations 2 Ionic Mechanisms Involving Nucleophilic Additions 3 Mechanisms Involving Radical Intermediates 3.1 Mechanisms Involving Reactive Carbon Radicals 3.2 Mechanisms Involving Phosphorus Radicals 3.2.1 Photoredox: Direct Creation of Phosphorus Radicals 3.2.2 Photoredox: Indirect Creation of Phosphorus Radicals 3.2.3 Dual Catalysis 3.3 Photolytic Cleavage 4 Conclusion and Outlook
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".