Effects of reduced dimensionality on the properties of magnesium hydroxide and calcium hydroxide nanostructures
Bibliographic record
Abstract
Metal hydroxides are a class of layered materials that contain two-dimensional metal hydroxide layers that can be isolated to form layered nanostructures. In this work, density functional theory (DFT) and self-consistent-charge density-functional tight-binding (SCC-DFTB) methods have been used to investigate the properties of magnesium hydroxide and calcium hydroxide nanostructures. The properties of single layer and multi layer structures with up to 10 metal hydroxide sheets and nanoparticles containing more than 2000 atoms have been calculated and compared with the bulk properties of these systems. The accuracy of the DFT methods employed and SCC-DFTB parameters developed in this study were validated against available experimental data. The results of the calculations indicate that significant differences exist between the properties of the nanostructures and the corresponding bulk values. In particular, the interlayer binding energies, electronic band gaps, and spectroscopic features are size-dependent and tend to converge to the bulk values as the size of the nanosystem is increased. The calculated binding energies and shear moduli show that all nanostructures are mechanically stable, in agreement with the experimental reports; although, their stabilities may be affected by the presence of intercalated species. Energy decomposition analyses reveal that the intralayer interactions in the investigated systems are predominantly electrostatic in nature, while the interlayer interactions are dominated by dispersion and polarization components. The results presented here quantify various properties of magnesium hydroxide and calcium hydroxide nanostructures, and could be used to understand the properties of other nanosystems containing layers of metal hydroxides in their structure.
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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 | 0.001 |
| 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".