Probing Adsorption, Pore Condensation, and Hysteresis Behavior of Pure Fluids in Three-Dimensional Cubic Mesoporous KIT-6 Silica
Bibliographic record
Abstract
In order to investigate the details of the process of pore condensation and hysteresis mechanisms in three-dimensional (3-D) pore networks, we performed a systematic study of the adsorption and pore condensation behavior of N 2 (77.4 K) and Ar (77.4 and 87.3 K) in a 3-D ordered pore system, i.e., cubic Ia 3̅ d mesoporous KIT-6 silica materials with mode pore diameters ranging from ca. 5 nm up to 11 nm. KIT-6 silica is a porous material composed of two intertwined mesoporous subnetworks similar as in MCM-48, but this material can be prepared with much larger mean pore diameters. Accurate pore size analysis was performed by X-ray diffraction modeling and by state-of the art application of nonlocal density functional theory (NLDFT) on N 2 (77.4 K) and Ar (87.3 K) sorption data. Furthermore, our data suggest that the width of the adsorption/desorption hysteresis loop observed for 3-D KIT-6 silica can be narrower as compared to that of pseudo-one-dimensional SBA-15 silica of the same pore size (i.e., in the pore diameter range from 6 to 8 nm). This specific behavior correlates well with the existence of the highly interconnected 3-D pore network of the KIT-6 material. Moreover, the results of our investigations are also consistent with previous observations that the SBA-15 pore system becomes more and more interconnected with increasing aging temperatures, i.e., SBA-15 changes from being a material with a pseudo-one-dimensional mesopore system to a material exhibiting a three-dimensional pore system resembling KIT-6 silica. These results provide new insights into the effects of pore interconnectivity on pore condensation and hysteresis behavior in both KIT-6 and SBA-15 silica materials and enable a more thorough understanding of the pore structure and textural properties of these materials.
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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 | 0.000 | 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 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".