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Record W2617223270 · doi:10.11159/icnfa17.103

DFT Based Simulation of H2S Gas Sensing Properties of Doped Graphene

2017· article· en· W2617223270 on OpenAlexvenueno aff
Seba Sara Varghese, Sundaram Swaminathan, K. K. Singh, Vikas Mittal

Bibliographic record

VenueProceedings of the World Congress on New Technologies · 2017
Typearticle
Languageen
FieldEngineering
TopicGas Sensing Nanomaterials and Sensors
Canadian institutionsnot available
Fundersnot available
KeywordsGrapheneDopingMaterials scienceComputer scienceOptoelectronicsNanotechnology

Abstract

fetched live from OpenAlex

The interactions of P-and S-doped graphene sheets with H2S molecule are investigated based on density functional theory based simulations to analyze the reactivity of these doped graphenes towards H2S. The energetically favourable adsorption configurations of H2S on doped graphene sheets are determined and adsorption energies are calculated. Our results indicate that the structural properties of doped graphene sheets are not influenced much by the adsorption of H2S. The results from charge distribution analysis, electronic band structures and density of states of H2S adsorbed on the doped graphene sheets show that the interactions between H2S and doped graphene sheets does not induce any significant changes in the electronic properties of P-and S-doped graphene.

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 score0.018
Threshold uncertainty score0.514

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 science0.0010.000
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 head0.024
GPT teacher head0.227
Teacher spread0.203 · 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

Citations1
Published2017
Admission routes1
Has abstractyes

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