A Density Functional Theory Study of Copper-Doped Nickel Oxide Supercells
Bibliographic record
Abstract
Understanding the effects of defects on the properties of transition metal oxides is of great \nimportance to the chemical, biological and sustainability industries. Nickel oxide is one \nsuch material that is widely used in various forms, and continues to be studied; most notably \nwith vacancies and dopants both being introduced into the material through experiment. The \nelectronic properties of bulk NiO have been calculated using the RSCAN and PBE XC-functionals, \nwith particular focus on spectral and optical properties. \nAdditionally, 108-atom supercells have been constructed, with intrinsic and extrinsic defects \nbeing placed in the supercell. The copper-doped supercell has been studied for various copper \natom positions and concentrations. The doping site type altered the electronic properties in \ndifferent ways, with clear n-type behaviour being exhibited by substitution on oxygen sites and \ninterstitial doping. This increased n-type behaviour and narrowing of the band gap suggests that \ncareful engineering of the chemical environment to favour forming these defects will produce a \nmaterial with higher conductivity and charge transfer rates, which is essential for photocathode \napplications. \nBy varying the distance between dopant Cu atoms, it was found that it is energetically \nfavourable for the Cu atoms to be closer together than further apart, with an energy difference \nof approximately 70 meV. Additionally, the preferential alignment of multiple Cu atom dopants \nwas found to be along the same [111] plane. \nAn exploratory study into the different stable compounds containing Ni, Cu and O has been \ncarried out, with a 2D ternary convex hull being plotted to investigate these compounds’ stability. \nThere is only one predicted stable compound containing all three species, the rhombohedral \nstructure Ni9CuO10.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".