Shedding New Light on Nanostructured Catalysts with Positron Annihilation Spectroscopy
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Bibliographic record
Abstract
Abstract Interest in new tools for the analysis of catalytic materials is growing due to the potential to enhance their functionality through the optimal nanostructuring, for example, of pore networks and surface properties. This prompts the need for improved descriptors to discriminate increasingly complex architectures. As a nondestructive, dynamic, and potentially, temporally, and spatially resolved tool, positron annihilation spectroscopy (PAS) can provide valuable complementary insights to already established (e.g., adsorption, spectroscopy, diffraction, and microscopy) methods. This is possible due to the specific sensitivity of positrons to the electronic environment, which determines their annihilation characteristics. However, despite growing enthusiasm, PAS is not widely known in the catalysis community. This review aims to highlight the many unique features, principles, and potential pitfalls of the technique, expanding on the outdated reviews on the topic, which are now over a decade old. After briefly introducing the principles, progress in the application of PAS to investigate various features of relevant catalytic materials is summarized. This includes the crystalline structure, presence of defects, pore connectivity and evolution, chemical properties, and adsorption phenomena. An improved understanding of the response will contribute not only to guiding the design of nanostructured materials but also to positioning PAS as a mainstream method for catalyst characterization.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it