Single‐Atom Catalysts Supported by Crystalline Porous Materials: Views from the Inside
Bibliographic record
Abstract
Single-atom catalysts (SACs) have recently emerged as an exciting system in heterogeneous catalysis showing outstanding performance in many catalytic reactions. Single-atom catalytic sites alone are not stable and thus require stabilization from substrates. Crystalline porous materials such as zeolites and metal-organic frameworks (MOFs) are excellent substrates for SACs, offering high stability with the potential to further enhance their performance due to synergistic effects. This review features recent work on the structure, electronic, and catalytic properties of zeolite and MOF-protected SACs, offering atomic-scale views from the "inside" thanks to the subatomic resolution of synchrotron X-ray absorption spectroscopy (XAS). The extended X-ray absorption fine structure and associated methods will be shown to be powerful tools in identifying the single-atom site and can provide details into the coordination environment and bonding disorder of SACs. The X-ray absorption near-edge structure will be demonstrated as a valuable method in probing the electronic properties of SACs by analyzing the white line intensity, absorption edge shift, and pre-/postedge features. Emphasis is also placed on in situ/operando XAS using state-of-the-art equipment, which can unveil the changes in structure and properties of SACs during the dynamic catalytic processes in a highly sensitive and time-resolved manner.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".