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Record W4281669405 · doi:10.1002/cjce.24480

Calcium looping carbon capture: Progress and prospects

2022· article· en· W4281669405 on OpenAlex
Seyed Mojtaba Hashemi, Mohammad Hashem Sedghkerdar, Nader Mahinpey

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2022
Typearticle
Languageen
FieldEngineering
TopicChemical Looping and Thermochemical Processes
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCalcium loopingCarbonationCarbon capture and storage (timeline)SorbentFossil fuelProcess engineeringCarbon fibersDurabilityEnvironmental scienceMaterials scienceChemical engineeringWaste managementChemistryEngineering

Abstract

fetched live from OpenAlex

Abstract Carbon capture and utilization/storage is an integral part of a smooth transition to a net‐zero energy portfolio. The distinctive advantages of the calcium looping (CaL) process, including low‐cost and high‐theoretical uptake capacity, make it a promising approach for the decarbonization of fossil fuel power plants and carbon‐intensive industries, including cement and steel. CaL exploits the reversible reaction of CO 2 with CaO to capture and release carbon dioxide in a cyclic process. This paper reviews the fundamentals of the CaL process, the kinetics of the carbonation reaction, and extensive research on the development of sorbent materials with high durability for use in the CaL process. Various optimizing strategies for the improvement of the stability and CO 2 uptake capacity of materials are outlined. Lastly, an overview of bench‐ and pilot‐scale testing facilities around the world is provided. The characteristics, operating conditions, and the main experimental findings of the testing facilities are summarized.

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.

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)0.000
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 score0.010
Threshold uncertainty score0.501

Codex and Gemma teacher scores by category

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 integrity0.0000.001
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 head0.007
GPT teacher head0.178
Teacher spread0.172 · 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