Single atom catalysts: a surface heterocompound perspective
Bibliographic record
Abstract
The concept of single atom catalysts (SACs) originated from reducing the amount of noble metals used, by steadily refining the particle size loaded on a substrate surface. It has been rapidly moving to non-noble elements and their compounds in recent years, notably transition metals and even non-metals. They are of heterogeneous types, where the active species are refined to atomic dispersion scales on the surfaces/sub-surfaces of the solid support. The catalytic performance is governed by both the type and population of accessible active sites, and their bond and coordination environment, largely as a result of the interactions with the substrate surface. Unlike the internal structure within a crystalline solid, there is a large spatial variation in the bond and coordination environment of different atoms on the solid surface across different length scales, and in particular with the unsaturated surface, where there are various defects. They can also be dramatically altered during both the catalyst synthesis and actual catalysis process. In a way, they form a "surface heterocompound", where the local bonds for each metal atom are of a compound type, while there can be a large variation from one to another. Herein, we will look into the evolution from traditional heterogeneous catalysts to SACs, from the surface heterocompound perspective. Discussion will then be made on the on-going strategies and challenges in manipulating and identifying the local bond and coordination environment on the hetero-surfaces, in an attempt to develop efficient catalysts for the targeted applications, where both synthesis techniques and analytical tools are critically important, and computational studies can provide the key guiding principles. With selected paradigm studies, we will briefly examine the future perspectives for this newly emerging catalysis frontier.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".