Analysis of Corrosion Potential of Zn, Ni, and Zn-Ni Alloy Using Ab Initio Calculations Supported by Experimental Thermodynamics Data
Bibliographic record
Abstract
Abstract The purpose of this study is to investigate the corrosion properties of Zn, Ni, and Zn-Ni alloy using density functional theory (DFT). DFT can assist in predicting the thermodynamic properties of challenging compounds such as metals, alloys, and transition metal oxides. In the present work, DFT is used to predict Zn, Ni, and Zn-Ni alloy phase diagram. The Hubbard correction (U) and dispersion correction (D) are used to minimize the inherent error associated with the DFT. We studied the crystal structure, electronic structures, and thermodynamic energies of Zn and Ni compounds using the generalized gradient approximation (GGA) density functional employing Perdew Burke Ernzerhof (PBE). We have developed the corresponding Pourbaix diagram of Zn, Ni, and their alloy to compare the performance of density functional theory with the experimental observations. The corrosion behavior of various alloys including ZN11, NI2, ZnNi, ZNNi3 are compared and discussed. This can be useful for predicting the corrosion-resistant properties of these alloys.
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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 | 0.001 |
| 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 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".