MétaCan
Menu
Back to cohort
Record W4390668086 · doi:10.1021/acs.iecr.3c03645

Tri-reforming of CH<sub>4</sub> over a Thermally Stable and Carbon-Resistant Nanonickel Metal Catalyst Dispersed on Mesoporous-Zirconia

2024· article· en· W4390668086 on OpenAlexaff
Akansha Pandey, Prakash Biswas, Kamal Kishore Pant, Ajay K. Dalai

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2024
Typearticle
Languageen
FieldMaterials Science
TopicCatalytic Processes in Materials Science
Canadian institutionsUniversity of Saskatchewan
FundersScience and Engineering Research BoardMinistry of Education, IndiaDepartment of Science and Technology, Ministry of Science and Technology, India
KeywordsCatalysisMesoporous materialMaterials scienceNickelCubic zirconiaCarbon dioxide reformingSyngasChemical engineeringCokeMetalMethaneDispersion (optics)Particle sizeCarbon fibersMetallurgyChemistryCeramicComposite materialOrganic chemistryComposite number

Abstract

fetched live from OpenAlex

A novel nanonickel metal catalyst dispersed on mesoporous-zirconia is developed for the controlled production of the synthesis gas with an H 2 /CO molar ratio of 1.5–2 via the tri-reforming of methane (TRM). The catalysts were tested in a fixed-bed reactor at 600–850 °C and 1 atm. At the optimum feed (CH 4 /CO 2 /O 2 /H 2 O/N 2 ) ratio of 1:0.5:0.1:0.0125:1, the maximum CO 2 and CH 4 conversion was ∼28 and ∼86%, respectively, over the 5 wt % Ni/ZrO 2 . At this condition, the syngas with an H 2 /CO ratio of ∼1.5 was achieved at a lower reaction temperature of 700 °C. The superior activity of this catalyst was due to the presence of highly dispersed and reduced nickel particles over the combined tetragonal and monoclinic phases of mesoporous ZrO 2 . The basic strength of the catalyst, the nickel particle size, and metal dispersion played vital roles in controlling the TRM activity as well as the H 2 /CO ratio. The time-on-stream study and the used catalyst characterization results established that the nanosized nickel metal particles dispersed on mesoporous zirconia were thermally stable and coke-resistant.

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)0.003
metaresearch head score (Gemma)0.001
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 score0.003
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
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 science0.0010.000
Research integrity0.0000.001
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 head0.037
GPT teacher head0.294
Teacher spread0.257 · 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

Citations11
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueIndustrial & Engineering Chemistry ResearchSame topicCatalytic Processes in Materials ScienceFrench-language works237,207