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Record W3210933386 · doi:10.1002/er.7417

Investigation of hydrogen production from sodium borohydride by carbon nano<scp>tube‐graphene</scp>supported<scp>PdRu</scp>bimetallic catalyst for<scp>PEM</scp>fuel cell application

2021· article· en· W3210933386 on OpenAlexaff
Tuqa Majeed Hameed Al‐Msrhad, Yılser Devrim, Arife Uzundurukan, Yağmur Budak

Bibliographic record

VenueInternational Journal of Energy Research · 2021
Typearticle
Languageen
FieldMaterials Science
TopicHydrogen Storage and Materials
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsCatalysisSodium borohydrideProton exchange membrane fuel cellBimetallic stripHydrogen productionHydrolysisChemical engineeringChemistryInorganic chemistryMaterials scienceOrganic chemistry

Abstract

fetched live from OpenAlex

In this study, hydrogen (H2) generation from the hydrolysis of sodium borohydride (NaBH4) catalyzed by bimetallic Palladium-Ruthenium (PdRu) supported on multiwalled carbon nanotube-graphene (MWCNT-GNP) hybrid material is investigated. The effect of various parameters such as temperature, NaBH4 concentration, and catalyst loading and effect of base concentration are examined to observed optimum operating conditions. Experimental results show that the PdRu/MWCNT-GNP bimetallic catalyst has high catalytic activity on NaBH4 hydrolysis reaction. It has been found that PdRu/MWCNT-GNP catalyst shows low activation energy of 22.33 kJ/mol for hydrolysis reaction of NaBH4. The PdRu/MWCNT-GNP catalyst also exhibits H2 generation rate of 79.2 mmol/min·gcat at 45°C. It shows good cycle stability in the catalyst reusability test and retained 89% of its initial catalytic activity after fifth use. The high catalytic activity of the PdRu/MWCNT-GNP catalyst makes it promising in H2 generation from NaBH4 hydrolysis for commercial proton exchange membrane fuel cell (PEMFC) applications.

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)0.003
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 score0.050
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.028
GPT teacher head0.293
Teacher spread0.264 · 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

Citations21
Published2021
Admission routes1
Has abstractyes

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