MétaCan
Menu
Back to cohort
Record W2045211914 · doi:10.4236/snl.2013.34a003

Nickel Decorated Single-Wall Carbon Nanotube as CO Sensor

2013· article· en· W2045211914 on OpenAlexfundno aff
Ngangbam Bedamani Singh, Barnali Bhattacharya, Utpal Sarkar

Bibliographic record

VenueSoft Nanoscience Letters · 2013
Typearticle
Languageen
FieldMaterials Science
TopicCarbon Nanotubes in Composites
Canadian institutionsnot available
FundersMcMaster University
KeywordsCarbon nanotubeNickelMagnetizationDensity functional theoryMoleculeSpin polarizationMulliken population analysisMagnetic momentMaterials scienceCluster (spacecraft)AcceptorChemical physicsNanotechnologyChemistryComputational chemistryElectronCondensed matter physicsMagnetic fieldPhysics

Abstract

fetched live from OpenAlex

Based on spin-polarized density functional theory (DFT) calculations, the interaction between nickel cluster decorated single-wall carbon nanotube (CNT) and CO molecule has been investigated. DFT calculations are performed with generalized gradient approximation (GGA) using Perdew-Burke-Ernzerhof (PBE) functional. Interaction of CNT and cluster induces spin polarization in the CNT. Nickel decorated CNT has a large magnetic moment of 4.00 μB which decreases to 0.10 μB when CO molecule is absorbed to it. Such a drastic reduction in magnetization may be detected by SQUID magnetometer. Hence by measuring magnetization change, CNT-cluster system may be used as gas detectors. The charge transfer between the systems has been discussed through Mulliken charge analysis for different orientations of the adsorbed CO molecule. We observed that CNT-cluster system acts as electron donor and CO molecule acts as electron acceptor in this study.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.007
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.003

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 head0.013
GPT teacher head0.235
Teacher spread0.222 · 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

Citations12
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueSoft Nanoscience LettersSame topicCarbon Nanotubes in CompositesFrench-language works237,207