Adsorption model for atoms and molecules on doped semiconducting oxides
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Bibliographic record
Abstract
Fundamental understanding of the interaction between atoms and molecules with the surfaces of oxides including semiconducting oxides is crucial for the development of several thermo-, photo-, and electrocatalytic reactions as well as any application where surfaces are exposed to an environment beyond vacuum. While previous studies have postulated material features (descriptors) that to some extent suggest the adsorption energy trends on semiconducting oxides, a physics based model to describe the interaction of atoms and molecules with the surfaces of these materials is still lacking. In this study, we perform a series of controlled in silico experiments involving doping of quintessential semiconducting oxides (${\mathrm{SrTiO}}_{3}, {\mathrm{SrZrO}}_{3}$, and ${\mathrm{TiO}}_{2}$) to identify the perturbation by the dopant to the electronic structure of the host oxide and its resultant effect on the adsorption energies of simple atoms and molecules. We identify that a combination of three surface features: unique surface resonance states of the host-metal and lattice oxygen atoms of the terminating surface oxide layer as well as the gap states dominated by the introduced dopants contribute to the adsorption energy in a concerted fashion. We find that this intricate interplay between on the one hand host-metal and on the other hand oxygen surface resonance states with the adsorbate, respectively, results in a deviation from the well-established adsorbate scaling relations seen for ${\mathrm{NH}}_{x}$ ($x=0$--2) and ${\mathrm{CH}}_{x}$ ($x=0$--3) but not ${\mathrm{OH}}_{x}$ and ${\mathrm{SH}}_{x}$. Through this lens, we develop a physics based adsorption model hitherto referred as the generalized concerted coupling model (GCC model). The introduced model provides a physical understanding with an associated electronic structure descriptor rooted in the unique surfaces resonances that accurately captures the adsorption energy trends on doped semiconducting oxides. This paves the way for the atomistic design of doped semiconducting oxides for different catalytic applications, including sustainable energy applications such as electrochemical water splitting.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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