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Record W2379030244

Development of the technology for nuclear production of hydrogen

2011· article· en· W2379030244 on OpenAlexaboutno aff
Ping Zhang, Bo Yu, Jingming Xu

Bibliographic record

VenueHe huaxue yu fangshe huaxue · 2011
Typearticle
Languageen
FieldEngineering
TopicChemical Looping and Thermochemical Processes
Canadian institutionsnot available
Fundersnot available
KeywordsHydrogen productionHydrogenNuclear engineeringChemistryNuclear powerThermochemical cycleNuclear reactorElectricity generationHigh-temperature electrolysisSteam reformingHydrogen fuelProcess engineeringWaste managementNuclear physicsElectrolysisThermodynamicsPower (physics)EngineeringPhysics
DOInot available

Abstract

fetched live from OpenAlex

Hydrogen is a clean energy and must be produced by means of primary energy.To use nuclear energy for producing hydrogen in commercial scale is a promising way in the future.High temperature gas cooled reactor(HTGR) can generate electricity with high efficiency and provide high temperature process heat,therefore,it is most suitable for hydrogen production.Two hydrogen production processes,thermochemical cycle and high temperature steam electrolysis(HTSE),could be used for coupling with HTGR.These processes are being investigated in many countries,such as the United States,Japan,France,Canada and China.The nuclear power is rapidly developing in China.The construction of 200 MWe HTGR-PM demonstration plant has been started.In the meantime,the nuclear production of hydrogen processes are being developed in Institute of Nuclear and New Energy Technology(INET),Tsinghua University.The both processes,S-I thermochemical cycle and HTSE,have been successfully verified in laboratory scale in 2009.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.019
GPT teacher head0.193
Teacher spread0.173 · 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 designNot applicable
Domainnot available
GenreMethods

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

Citations1
Published2011
Admission routes1
Has abstractyes

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