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Record W2266182306 · doi:10.14447/jnmes.v15i4.47

Hydrogen Generation of Al-La-Bi Alloy in Aqueous Inorganic Salt Solutions

2012· article· en· W2266182306 on OpenAlexvenueno aff
Jianbo Liu, Lei Tang, Chao Li, Bin Tang, Xia Xiao, Hu Xing, Meiqiang Fan

Bibliographic record

VenueJournal of New Materials for Electrochemical Systems · 2012
Typearticle
Languageen
FieldMaterials Science
TopicHydrogen Storage and Materials
Canadian institutionsnot available
Fundersnot available
KeywordsAlloyHydrogen productionGalvanic cellScanning electron microscopeAqueous solutionMaterials scienceHydrogenChemical engineeringHydrolysisSalt (chemistry)CathodeMolten saltInorganic chemistryMetallurgyNuclear chemistryChemistryComposite material

Abstract

fetched live from OpenAlex

A method for obtaining hydrogen from Al-La-Bi alloy in different solutions was investigated for the production of inexpensive, pure, and safe hydrogen for micro-fuel cells. The hydrogen generation amount and rate could be regulated by changing composition design or salt solutions. Combined with X-ray diffraction (XRD), scanning electron microscopy (SEM) and hydrogen generation experiments, the hydrolysis byproduct La(OH)3 and inorganic salt solution stimulated the hydrolysis reaction of Al-La-Bi alloy and water, which was mostly based on micro galvanic cell between Al and Bi in the previous work. Increasing La content led to decrease particle size in the milling process which led to large special surface area and contact area of aluminum and water. Using inorganic salt solution such as Na2SnO3 solution might produce metal Sn which covered on Al surface and functioned as a cathode of a micro galvanic cell. The Al-13 wt%La-10 wt%Bi alloy yielded 1113 ml/g hydrogen with 100 % efficiency with 60 min at 343 K.

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)0.000
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 score0.003
Threshold uncertainty score0.750

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.032
GPT teacher head0.272
Teacher spread0.240 · 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

Citations0
Published2012
Admission routes1
Has abstractyes

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