Differential hysteresis scanning of non-templated monomodal amorphous aerogels
Bibliographic record
Abstract
We perform Differential Hysteresis Scanning (DHS) Porosimetry of amorphous silicon oxycarbide aerogels to quantify hierarchical connectivity in these porous materials. We contrast high-resolution argon sorption scanning isotherms of samples obtained through a non-templated synthesis using different solvents, and characterize respective changes after calcination at 1000 °C. The multi-scan DHS data sets are analyzed through non-negative least-squares deconvolution using a kernel of theoretically derived isotherms for a selection of hierarchical geometries using non-local density functional theory (NL-DFT). We obtain two-dimensional contour plots that characterize mesopores according to the ratio between pore diameter and its connecting window. Combined information from DHS and complementary BET and BJH approaches reveals one system with monomodal distribution both in pore diameters and in window diameters. Hence, this amorphous material exhibits a uniformity usually only observed for crystalline systems. We demonstrate that DHS analysis provides quantitative data analyzing the hierarchical structure of mesoporous materials and unlocks pathways towards tailored materials with control of surface heterogeneity, localization, and sequential accessibility - even for amorphous systems.
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How this classification was reachedexpand
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) | 0.001 | 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) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".