Designing tandem catalytic reductive functionalisation strategies of carbonyl derivatives
Bibliographic record
Abstract
Chapter 1 introduces tertiary amide-based reductive functionalisation strategies as attractive access points towards medicinally relevant α-branched tertiary amine building blocks. Within the scope of this synthetic transformation, Vaska’s complex is highlighted as a chemoselective transition metal catalyst that has come to the forefront for facilitating tertiary amide and lactam hydrosilylation in a mild and efficient manner in both small molecular systems and complex natural product synthesis. Chapter 2 provides a brief description of the Density Functional Theory-based computational methods that were used in Chapters 3 and 5 to complement the corresponding experimental findings. Chapter 3 describes the development of a dual catalytic umpolung reductive functionalisation strategy that enabled the generation of nucleophilic α-amino radical intermediates from robust tertiary amide starting points under a mild set of hydrosilylative/photocatalytic conditions. The work showcases how a tandem, dual catalytic approach can be utilised to enable reductive coupling of amides with electrophiles, previously inaccessible using Vaska’s complex-based hydrosilylative chemistry. Chapter 4 demonstrates how a derivative of Vaska’s complex can facilitate the hydrosilylation of α,β-unsaturated ketones. This finding provided a new synthetic opportunity for the iridium (I)-catalysed reductive functionalisation strategy to be used with carbonyl functionalities beyond the established tertiary amide motif. Inspired by the dual catalytic methodology developed in Chapter 3, the hydrosilylation step was combined with a secondary, chiral catalytic cycle to access enantioenriched products from feedstock enones, which have been thus far unprecedented for Vaska’s catalyst-based methodologies. Chapter 5 features a computational study that was undertaken to elucidate the mechanism and origins of stereoselectivity for a novel, organocatalytic, nucleophilic desymmetrisation of prochiral phosphonate ester reaction developed in the Dixon group. The systematic approach that was used to construct a computational model of the experimental conditions is presented. An analysis of the key, non-covalent interactions that governed both stereoselectivity and reactivity of the system is also provided.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".