Titanium catalysis for the synthesis of fine chemicals – development and trends
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Titanium is the second most abundant transition metal and is already a key player in important industrial processes (e.g. polyethylene). Titanium is an attractive metal to use for catalytic transformations as it is a versatile and inexpensive metal of low-toxicity and of established biocompatibility. However, its potential use as a catalyst for the synthesis of fine chemicals, pharmaceuticals and agrochemicals is often overlooked due to its oxophilic, Lewis acidic character, which renders complexes of titanium less functional group tolerant than their late transition metal counterparts. Nevertheless, three different fields of research in titanium catalysis have drawn attention in recent years: formal redox catalysis, hydroamination and hydroaminoalkylation. For these reactions, titanium offers new approaches and alternative pathways/mechanisms that are complementary to late transition metal-based catalysis. This review focuses on advances in fine chemical synthesis by titanium-catalyzed reactions featuring redox transformations and two important hydrofunctionalization reactions, hydroamination and hydroaminoalkylation. Starting from the late 90s, we provide an overview of historic inspirational contributions, both catalytic and stoichiometric, and the latest insights in catalyst design efforts, mechanistic details and utility of the three different classes of transformations. Insights to enhance catalyst activity as well as catalyst controlled regio- and stereoselectivities are presented. Illustrative examples that highlight substrate scope and the application of titanium catalysis to the synthesis of complex organic small molecules, natural products and materials are shown. Finally, opportunities and strategies for on-going research and development activities in titanium catalysis are highlighted.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it