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Record W4213048552 · doi:10.53063/synsint.2022.21105

Molecular hydrogen production by radiolysis of water on the surface of nano-ZrO2 under the influence of gamma rays

2022· article· en· W4213048552 on OpenAlexvenueno aff
Gunel Imanova

Bibliographic record

VenueSynthesis and Sintering · 2022
Typearticle
Languageen
FieldMaterials Science
TopicNuclear Materials and Properties
Canadian institutionsnot available
Fundersnot available
KeywordsRadiolysisDecompositionZirconium dioxideChemistryNanoparticleHydrogenKineticsHydrogen productionEnthalpyOxideChemical engineeringMaterials scienceRadicalNanotechnologyOrganic chemistryThermodynamics

Abstract

fetched live from OpenAlex

In this research, the radiation-heterogeneous processes of water decomposition on the surface of zirconium dioxide nanoparticles (n-ZrO2) were studied. The kinetics of buildup of molecular hydrogen during the radiolytic processes of water decomposition was also examined. The production of H2 and H2O2 through water radiolysis was investigated to develop a computational model and disclose the kinetic behavior of water radiolysis. The enthalpy of ZrO2 nanoparticles was studied at the temperature range T=1200-2900 K, in which ZrO2 nanoparticles has a two-phase transition. Some of the electrons were transported to the surface of the nanoparticles during the physical and physicochemical stages of the process and emitted into the water. At the same time, the migration of energy carriers in radioactively active oxide compounds changed at different intervals depending on the composition, structural stability, and electro-physical properties of the oxides.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0000.000

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 head0.011
GPT teacher head0.189
Teacher spread0.179 · 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 source (direct Gemma or distilled Codex), 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

Citations16
Published2022
Admission routes1
Has abstractyes

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