Diplatinum Single‐Molecular Photocatalyst Capable of Driving Hydrogen Production from Water via Singlet‐to‐Triplet Transitions
Bibliographic record
Abstract
Abstract Solar‐driven hydrogen production is regarded as one of the most ideal methods to achieve a sustainable society. In order to artificially establish efficient photosynthetic systems, efforts have been made to develop single‐molecular photocatalysts capable of serving both as a photosensitizer (PS) and a catalyst (Cat) in hydrogen evolution reaction (HER). Although examples of such hybrid molecular photocatalysts have been demonstrated in the literature, their solar energy conversion efficiencies still remain quite limited. Here we demonstrate that a new dinuclear platinum(II) complex Pt 2 (bpia)Cl 3 (bpia=bis(2‐pyridylimidoyl)amido) serves as a single‐molecular photocatalyst for HER with its performance significantly higher than that of the PtCl(tpy)‐ and PtCl 2 (bpy)‐type photocatalysts developed in our group (tpy=2,2':6′,2''‐terpyridine, bpy=2,2′‐bipyridine). The outstanding feature is that Pt 2 (bpia)Cl 3 can produce H 2 even by irradiating the lower‐energy light above 500 nm, which is rationalized due to the direct population of triplet states via singlet‐to‐triplet transitions (i.e., S‐T transitions) accelerated by the diplatinum core. To the best of our knowledge, Pt 2 (bpia)Cl 3 is the first example of a single‐molecular photocatalyst enabling hydrogen production from water via the S‐T transitions using lower‐energy light (>580 nm).
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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".