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Record W2615230747 · doi:10.1002/clen.201600755

Insight Into the CO<sub>2</sub> Capturer Derived From Graphene/MgO Composite

2017· article· en· W2615230747 on OpenAlexaff
Xin Dong, Yan Yan Li, Shuo Hao Li, Ying Wang, Jian Hua Zhu

Bibliographic record

VenueCLEAN - Soil Air Water · 2017
Typearticle
Languageen
FieldEngineering
TopicMembrane Separation and Gas Transport
Canadian institutionsMinistry of Education and Child Care
FundersNanjing UniversityNational Natural Science Foundation of China
KeywordsGrapheneComposite numberMaterials scienceComposite materialNanotechnology

Abstract

fetched live from OpenAlex

Graphene/MgO composite was studied to develop warm CO 2 capturer. The structure of doped MgO was examined with XRD and nitrogen adsorption‐desorption, and its basicity was assessed with instantaneous adsorption and temperature programmed desorption (TPD) of CO 2 . The surface area of MgO was increased ten times by adding graphene, and the CO 2 adsorption capability was also significantly enhanced. A new method combined CO 2 instantaneous adsorption and TPD technique is proposed here to examine the adsorptive sites of the MgO sorbent, exploring the property‐function relation of the CO 2 capturer.

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 score0.055
Threshold uncertainty score0.900

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)0.0000.001

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 head0.011
GPT teacher head0.212
Teacher spread0.202 · 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

Citations7
Published2017
Admission routes1
Has abstractyes

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