Bibliographic record
Abstract
Forming nanomaterials junctions and using plasmons represent two important, promising strategies for realizing broadband photocalysis in strategically important applications such as solar fuels and photocatalytic degradation of pollutants. In this talk, I will present some of our recent work on the rational design of nanohybrids and their applications in solar fuels and photocatalysis. One example is about the in situ synthesis of plasmonic Ag nanoparticles (AgNPs) and Ag-MOF. The intimate and stable interface between the AgNPs and Ag-MOF and hot electron transfer from the plasmonic AgNPs to MOF led to highly efficient visible-light photocatalytic H2 generation in aqueous solution, which surpasses most of reported MOF-based photocatalytic systems. This work sheds light on effective electronic and energy bridging between plasmonic NPs and MOF. References: [1] Nature communications, 12: 1231 (2021); [ 2] Nature communications, 2023, 14: 541; [3] Chemistry of Materials, 2021, 33, 695-705; [4] Adv. Funct. Mater. 2019, 1902486.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.044 | 0.024 |
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".