MétaCan
Menu
Back to cohort
Record W2155504112 · doi:10.1351/pac200476122069

Chemical reactions at surfaces and interfaces from first principles: Theory and application

2004· article· en· W2155504112 on OpenAlexfundno aff
Zhi‐Pan Liu

Bibliographic record

VenuePure and Applied Chemistry · 2004
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Chemical Physics Studies
Canadian institutionsnot available
FundersIsaac Newton TrustQueen's University
KeywordsChemistryDensity functional theoryCatalysisChemical reactionDissociation (chemistry)Chemical physicsComputational chemistryChemical processQuantum chemicalNanotechnologyBiochemical engineeringPhysical chemistryMoleculeOrganic chemistry

Abstract

fetched live from OpenAlex

The last decade has seen rapid expansion and development in the field of density functional theory (DFT) simulation on the complex chemical processes that occur at surfaces and interfaces. The understanding of the phenomena in surface science and heterogeneous catalysis has benefited tremendously from these quantum mechanic calculations. This article reviews current progress in the theory of reactions on surfaces, in particular, those relevant to the barrier and the active site of surface reactions. Two representative reactions, namely, NO dissociation and CO oxidation, are selected to illustrate how these theoretical concepts are applied to understand catalytic reactions. Here, the pathways and energetics of these reactions under various catalytic conditions are described in detail, and the understanding of the reactions is generalized. It is concluded that DFT-based methods can be well applied to catalysis to understand the electronic structure of chemical processes and to elucidate mechanisms of complex surface reactions.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.006
GPT teacher head0.213
Teacher spread0.208 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations32
Published2004
Admission routes1
Has abstractyes

Explore more

Same venuePure and Applied ChemistrySame topicAdvanced Chemical Physics StudiesFrench-language works237,207