MnO<sub>2</sub>/Fe<sub>2</sub>O<sub>3</sub> Nanocomposite Sorbent for Gas Capture
Bibliographic record
Abstract
A special type of hydrous MnO 2 /Fe 2 O 3 nanocomposite was prepared using a two-step precipitation method. Fe 2 O 3 · x H 2 O nanoparticles, precipitated from Fe(NO 3 ) 3 and NH 3 ·H 2 O, were proposed to be embedded into the mesoporous network of MnO 2, which was synthesized by the aqueous reaction between KMnO 4 and glucose. The nanocomposite with an equal Mn/Fe molar ratio shows strong synergy, with a specific surface area of 388 m 2 /g, much larger than those of individual MnO 2 or Fe 2 O 3 · x H 2 O samples. As a result, this nanocomposite exhibited the highest adsorption capacity for NH 3 and SO 2 . The isolation of Fe 2 O 3 · x H 2 O by MnO 2, leading to mitigated aggregation of Fe 2 O 3 · x H 2 O nanoparticles, was characterized by transmission electron microscopy, powder X-ray diffraction, and vibrational spectra. X-ray absorption spectroscopy was used to study the interaction between Fe 2 O 3 · x H 2 O and MnO 2 after the formation of composites. This typical method for the preparation of nanocomposites proved to be effective to improve porosity, as demonstrated by N 2 adsorption isotherms and small-angle X-ray scattering.
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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) | 0.001 | 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 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".