MétaCan
Menu
Back to cohort
Record W2735255988 · doi:10.1016/j.jscs.2017.07.001

Al-doped B 80 fullerene as a suitable candidate for H 2 , CH 4 , and CO 2 adsorption for clean energy applications

2017· article· en· W2735255988 on OpenAlexafffund
Farzad Molani, Seifollah Jalili, Jeremy Schofield

Bibliographic record

VenueJournal of Saudi Chemical Society · 2017
Typearticle
Languageen
FieldMaterials Science
TopicBoron and Carbon Nanomaterials Research
Canadian institutionsUniversity of Toronto
FundersUniversity of TorontoCanada Foundation for InnovationGovernment of OntarioIslamic Azad UniversityCompute Canada
KeywordsAdsorptionChemisorptionFullereneDensity functional theoryChemistryImpurityAtom (system on chip)Materials scienceChemical engineeringPhysical chemistryComputational chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Dispersion-corrected density functional theory method was performed to report on a high-performance adsorbent for removal of CO2 from the precombustion and natural gases. At first, the effect of Al atom impurity on the structural and electronic properties of B80 fullerene is studied. Then, the adsorption geometries and energies of gases (H2, CH4, or CO2) on the B80 and AlB79 (amphoteric adsorbents) are explored. The Al atom enhances reactivity of the cage toward the gases and the adsorption processes are more exothermic with low and high energy barriers for chemisorption of H2 and CO2, respectively. Stable chemisorption of CO2 on the AlB79 is validated by the high adsorption energy and large charge transfer, while the CH4 is just physically adsorbed on the AlB79. Further, the physisorbed gases can enhance field emission current of the AlB79 and in the continuous capturing of the gases, the magnetic moment of the cage is quenched. Furthermore, dependency of the electronic structure of the adsorbent on the gas adsorption is intensively studied. We suggest that the AlB79 could be a promising material for capture, storage, and separation of the gases and as a novel material for sustainable energy and sweetening process in the petroleum industry.

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 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 score0.046
Threshold uncertainty score0.388

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.021
GPT teacher head0.320
Teacher spread0.300 · 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

Citations20
Published2017
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Saudi Chemical SocietySame topicBoron and Carbon Nanomaterials ResearchFrench-language works237,207