Predicting CO<sub>2</sub> adsorption and reactivity on transition metal surfaces using popular density functional theory methods
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Bibliographic record
Abstract
In this work, with Ni (110) as a model catalyst surface and CO2 as an adsorbate, a performance study of Density Functional Theory methods (functionals) is performed. CO being a possible intermediate in CO2 conversion reactions, binding energies of both, CO2 and CO, are calculated on the Ni surface and are compared with experimental data. OptPBE-vdW functional correctly predicts CO2 binding energy on Ni (−62 kJ/mol), whereas CO binding energy is correctly predicted by the rPBE-vdW functional (−138 kJ/mol). The difference in computed adsorption energies by different functionals is attributed to the calculation of gas phase CO2. Three alternate reaction systems based on a different number of C=O double bonds present in the gas phase molecule are considered to replace CO2. The error in computed adsorption energy is directly proportional to the number of C=O double bonds present in the gas phase molecule. Additionally, both functionals predict similar carbon–oxygen activation barrier (40 kJ/mol) and equivalent C1s shifts for probe species (−2.6 eV for CCH3 and +1.5 eV CO3−), with respect to adsorbed CO2. Thus, by including a correction factor of 28 kJ/mol for the computed CO2 gas phase energy, we suggest using rPBE-vdW functional to investigate CO2 conversion reactions on different metals.
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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 | 0.000 |
| 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) | 0.000 | 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 it