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Comparative Study of H<sub>2</sub>S Gas Sensing: Pristine vs. Cobalt-Functionalized C<sub>2</sub>N Using First-Principles Modeling

2024· article· en· W4407129305 on OpenAlexaff
Asma Wasfi, Mohamed Atef, Falah Awwad

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMaterials Science
TopicBoron and Carbon Nanomaterials Research
Canadian institutionsLakehead University
FundersUnited Arab Emirates University
KeywordsCobaltMaterials scienceChemical engineeringMetallurgyEngineering

Abstract

fetched live from OpenAlex

The exceptional physical and electrical characteristics of two-dimensional Nitrogenated Holey Graphene (C<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf>N) devices highlight their significance. C<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf>N-based sensors demonstrate remarkable sensitivity, stability, and responsiveness compared to other solid-state sensors. The conductivity of C<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf>N experiences shifts upon exposure to a wide array of organic and inorganic substances, enabling the detection of various target molecules through these conductivity alterations. Using first-principles transport simulations, a sensor device incorporating Nitrogenated Holey Graphene (C<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf>N) is specifically designed to detect varying concentrations of hydrogen sulfide (H<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf>S) gas molecules. Through the utilization of the Quantumwise Atomistix Toolkit (ATK), a simulator for nanoscale semiconductor devices, a C<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf>N-based sensor is simulated in this study. This work studies the effectiveness of C<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf>N sensors, both pristine and functionalized with Co, for detecting varying concentrations of hydrogen sulfide (H<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf>S) gas molecules. Our findings reveal that the Co-functionalized C<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf>N sensor performs better than the pristine counterpart. Through simulations, we demonstrate the sensor's ability to detect single and double H<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf>S molecules with 20% higher sensitivity and 15% improved selectivity compared to pristine C<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf>N. This research highlights the potential of C<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf>N-based sensors in gas sensing applications, including environmental monitoring and industrial safety, and notably in biomedical applications such as medical diagnostics through breath analysis for disease markers. The effectiveness of employing density functional theory for sensor analysis and electronic transport calculations is also highlighted.

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)0.001
metaresearch head score (Gemma)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.383
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.085
GPT teacher head0.320
Teacher spread0.234 · 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.

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

Citations0
Published2024
Admission routes1
Has abstractyes

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