Functional mesoporous materials in clean energy: an interview with Dongyuan Zhao
Bibliographic record
Abstract
invited Prof. Dongyuan Zhao of Fudan University for an interview focusing on his team's renowned research on functional mesoporous materials and energy-related applications. Prof. Zhao is a professor of chemistry and materials science, and a member of the Chinese Academy of Sciences. He received his PhD in chemistry from Jilin University in 1990. He has since focused his research on the synthesis and structure of porous materials and molecular sieves. His team received a first-tier national science award in 2021 for their contribution to the research and development of mesoscopic materials. They discovered a method of synthesizing mesoporous organic polymers and carbonaceous materials using organic-organic self-assembly. This work was published in 2005 and since then it has turned into a vibrant new field of more than 40 000 publications so far. His team has named more than 20 of their inventions after Fudan University: the FDU mesoporous series.
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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 | 0.009 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.003 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.006 | 0.011 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".