MétaCan
Menu
Back to cohort
Record W3044979885 · doi:10.1039/d0cp02418j

Reaction probability and kinetics of water splitting on the penta-NiAs<sub>2</sub> monolayer from an <i>ab initio</i> molecular dynamics investigation

2020· article· en· W3044979885 on OpenAlexaff
Thi H. Ho, Hieu C. Dong, Viet Q. Bui, Yoshiyuki Kawazoe, Hung M. Le

Bibliographic record

VenuePhysical Chemistry Chemical Physics · 2020
Typearticle
Languageen
FieldMaterials Science
Topic2D Materials and Applications
Canadian institutionsHatch (Canada)
Fundersnot available
KeywordsMonolayerAb initioMolecular dynamicsKineticsChemistryComputational chemistryAb initio quantum chemistry methodsChemical physicsPhysical chemistryThermodynamicsMoleculePhysicsQuantum mechanics

Abstract

fetched live from OpenAlex

The reaction probability and kinetics of the water splitting process on the penta-NiAs2 monolayer are studied using ab initio molecular dynamics simulations. A total of 100 trajectories are investigated, in which a H2O molecule is set to strike the surface with a translational energy of 1 eV or 2 eV. The results show that the NiAs2 monolayer is an excellent candidate for the activation of water splitting with a reaction probability of 94% for both energy levels. Interestingly, the kinetics of two O-H dissociation stages varies greatly with respect to the inletting translational energy. Interpreting the reaction data for the 1 eV case, we conclude that O-H1 and O-H2 dissociations are first-order processes. However, such dissociation steps become pseudo-zeroth order in the 2 eV case. At the time of the dissociation, the force acting on atoms and the principal component analysis suggest that the two OH breaking stages behave like harmonic springs until reaching the dissociation.

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.

How this classification was reachedexpand

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
Threshold uncertainty score0.631

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.020
GPT teacher head0.225
Teacher spread0.205 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2020
Admission routes1
Has abstractyes

Explore more

Same venuePhysical Chemistry Chemical PhysicsSame topic2D Materials and ApplicationsFrench-language works237,207