MétaCan
Menu
Back to cohort
Record W4396670358 · doi:10.1103/physrevb.109.195416

Adsorption model for atoms and molecules on doped semiconducting oxides

2024· article· en· W4396670358 on OpenAlex
Abhinav S. Raman, Colin Lehman-Chong, Aleksandra Vojvodić

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenuePhysical review. B./Physical review. B · 2024
Typearticle
Languageen
FieldMaterials Science
TopicElectronic and Structural Properties of Oxides
Canadian institutionsnot available
FundersNational Energy Research Scientific Computing CenterCanadian Institute for Advanced ResearchU.S. Department of EnergyNational Science Foundation
KeywordsDopantAdsorptionMoleculeDopingMaterials scienceOxideChemical physicsMetalCrystallographyPhysical chemistryChemistry

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.545
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.034
GPT teacher head0.367
Teacher spread0.333 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it