Light-Activated Metal-Coordinated Supramolecular Complexes with Charge-Directed Self-Assembly
Bibliographic record
Abstract
Metal-coordinated materials are attractive for many applications including catalysis, sensing, and controlled release. Adenine and its derivatives have been widely used to generate many coordination complexes, polymers, and nanoparticles. However, few of these materials display fluorescence. Herein, we report fluorescent gold complexes and nanoclusters formed with adenosine, deoxyadenosine, AMP, and ATP, where the former two produced micrometer-sized particles and the latter two produced molecular clusters. Only weak fluorescence was produced with adenine, while no emission was observed with uridine, cytidine, or guanosine. We found that adding citrate and light exposure are two key factors to generate fluorescence, and their mechanistic roles have been explored. In all the products, the ratio between gold and adenine was determined to be 1:1 using UV–vis spectroscopy. Mass spectrometry showed clusters containing 2, 4, and 6 gold atoms in the gas phase. The fluorescence peak is around 470 nm for the AMP and ATP complex and 480 nm for the (deoxy)adenosine complexes. This work has provided a systematic approach to obtain fluorescent metal coordinated polymers and materials with tunable sizes, which will find applications in analytical chemistry, drug delivery, and imaging. The fundamental physical chemistry of these materials has been systematically explored.
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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".