Density-functional tight-binding investigation of the structure, stability and material properties of nickel hydroxide nanotubes
Bibliographic record
Abstract
Nickel hydroxide is a material composed of two-dimensional layers that can be rolled up to form cylindrical nanotubes belonging to a class of inorganic metal hydroxide nanotubes that are candidates for applications in catalysis, energy storage, and microelectronics. The stabilities and other properties of this class of inorganic nanotubes have not yet been investigated in detail. The present study uses self-consistent-charge density-functional tight-binding calculations to examine the stabilities, mechanical properties, and electronic properties of nickel hydroxide nanotubes along with the energetics associated with the adsorption of water by these systems. The tight-binding model was parametrized for this system based on the results of first-principles calculations. The stabilities of the nanotubes were examined by calculating strain energies and performing molecular dynamics simulations. The results indicate that single-walled nickel hydroxide nanotubes are stable at room temperature, which is consistent with experimental investigations. The nanotubes possess size-dependent mechanical properties that are similar in magnitude to those of other inorganic nanotubes. The electronic properties of the nanotubes were also found to be size-dependent and small nickel oxyhydroxide nanotubes are predicted to be semiconductors. Despite this size-dependence, both the mechanical and electronic properties were found to be almost independent of the helical structure of the nanotubes. The calculations also show that water molecules have higher adsorption energies when binding to the interior of the nickel hydroxide nanotubes when compared to adsorption in nanotubes formed from other two-dimensional materials such as graphene. The increased adsorption energy is due to the hydrophilic nature of nickel hydroxide. Due to the broad applications of nickel hydroxide, the nanotubes investigated here are also expected to be used in catalysis, electronics, and clean energy production.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| 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 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".