On Inventing <scp>Cross‐Dehydrogenative</scp> Coupling (<scp>CDC</scp>): Forming C—C Bond from Two Different C—H Bonds
Bibliographic record
Abstract
Comprehensive Summary Constructing C—C bonds is central to the synthesis of all chemical products. While conventional C—C bond formation methods always require one or two functional groups, 20 years ago, our establishment of the concept of Cross‐Dehydrogenative Coupling (CDC), wherein C—C bonds are directly formed from two different C—H bonds via the “formal” removal of two H atoms, has revolutionized chemical synthesis and has become one of the most active research subjects in chemistry. This perspective article will provide an insight of the origin of this concept and its early development in our laboratory. What are your favorite scientific discoveries from your lab? Over the past 30 years, we have made many discoveries. The most important ones are the developments of various Grignard‐type reactions in water which contradict textbook knowledge, the Aldehyde‐Alkyne‐Amine (A 3 ) coupling, the Cross‐Dehydrogenative Coupling that forms C—C bond from two C—H bonds, and the umpolung of carbonyl as organometallic reagent surrogate that allows to carry out organometallic reactions without using stoichiometric organometallic reagents. Did you plan to be a chemist when you were young? Not really. I was planning to be an artist when I was young but really felt deep affection for chemistry after I entered college. How did you get into Green Chemistry? When I was a graduate student, I became fascinated about natural product synthesis. However, I felt that most reported total syntheses are very lengthy and difficult. As a result, I have been constantly asking myself: can we have novel chemistry to simplify organic syntheses? By coincidence, this was also during the dawn of Green Chemistry, which has the same philosophy. Besides chemistry, what are your hobbies? Besides chemistry research, I still have an eye on art. Also, I enjoy reading philosophy books, traveling and meeting people from different walks of life. What advice do you give to young academics? Be unique, creative and different from others. These might be difficult to do at the beginning but they will be beneficial in the long run. In your personal view, what are the important future developments for chemistry? As chemistry is the central science, important future developments will mostly arise from interdisciplinary areas. These are already occurring between biology and chemistry, environment and chemistry, materials and chemistry, energy and chemistry, but will also be between chemistry and some emerging fields. One of them is with artificial intelligence. Currently, it requires a great amount of time and effort to carry out a large number of experiments for most reactions, Artificial intelligence can greatly change and simplify future chemistry research.
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How this classification was reachedexpand
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 | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".