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Record W2032337683 · doi:10.1002/ceat.201100497

Integration of H<sub>2</sub>‐Selective Membrane Reactors in the Integrated Gasification Combined Cycle for CO<sub>2</sub> Separation

2012· article· en· W2032337683 on OpenAlexfundno aff
Sebastian Schiebahn, E. Riensche, M. Weber, Detlef Stolten

Bibliographic record

VenueChemical Engineering & Technology · 2012
Typearticle
Languageen
FieldEngineering
TopicCarbon Dioxide Capture Technologies
Canadian institutionsnot available
FundersHelmholtz-Alberta Initiative
KeywordsIntegrated gasification combined cycleFlue gasWater-gas shift reactionProcess engineeringCarbon capture and storage (timeline)Air separationWaste managementCombined cycleSyngasChemistryEnvironmental scienceHydrogenGas turbinesEngineeringMechanical engineering

Abstract

fetched live from OpenAlex

Abstract The integrated gasification combined cycle (IGCC) offers the opportunity for precombustion CO2 capture. However, recent studies using physical absorption for CO2 separation indicated efficiency penalties only slightly lower than those for postcombustion capture in conventional steam power plants. These efficiency penalties are explained and analyzed. As an alternative, a process using a so‐called water‐gas shift membrane reactor, which combines hydrogen‐selective membranes with water‐gas shift reaction, is presented. It is demonstrated that the use of recirculated flue gas from downstream of the heat recovery steam generator as membrane sweep gas results in an overall efficiency loss of only 4.5 %‐points (including CO2 compression to 120 bar) in comparison to an IGCC without carbon capture and storage (CCS).

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 score0.002
Threshold uncertainty score0.003

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 integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.008
GPT teacher head0.223
Teacher spread0.215 · 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

Citations8
Published2012
Admission routes1
Has abstractyes

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