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Record W2923766510 · doi:10.1002/er.4440

An overview of the methanol reforming process: Comparison of fuels, catalysts, reformers, and systems

2019· article· en· W2923766510 on OpenAlex

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.

Bibliographic record

VenueInternational Journal of Energy Research · 2019
Typearticle
Languageen
FieldChemical Engineering
TopicCatalysts for Methane Reforming
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsCatalytic reformingMethanolMethane reformerSteam reformingProcess engineeringFuel cellsHydrogenMethanol fuelHydrogen productionWaste managementChemistryEngineeringChemical engineeringOrganic chemistry

Abstract

fetched live from OpenAlex

One of the main challenges facing power generation by fuel cells involves the difficulties related to hydrogen storage. Several methods have been suggested and studied by researchers to overcome this problem. Among these methods, using fuel reformers as a component of the fuel cell system is a practical and promising alternative to hydrogen storage. Among many hydrogen carrier fuels used in reformers, methanol is one of the most attractive ones because of its distinctive properties. To design and improve of the methanol reformate gas fuel cell systems, different aspects such as promising market applications for reformate gas–fueled fuel cell systems, and catalysts for methanol reforming should be considered. Therefore, our goal in this paper is to provide a comprehensive overview on the past and recent studies regarding methanol reforming technologies, while considering different aspects of this topic. Firstly, different fuel reforming processes are briefly explained in the first section of the paper. Then properties of various fuels and reforming of these fuels are compared, and the characteristics of commercial reformate gas–fueled systems are presented. The main objective of the first section of the paper is to give information about studies and market applications related to reformation of various fuels to understand advantages and disadvantages of using various fuels for different practical applications. In the next sections of the paper, advancements in the methanol reforming technology are explained. The methanol reforming catalysts and reaction kinetics studies by various researchers are reviewed, and the advantages and disadvantages of each catalyst are discussed, followed by presenting the studies accomplished on different types of reformers. The effects of operating parameters on methanol reforming are also discussed. In the last section of this paper, methanol reformate gas–fueled fuel cell systems are reviewed. Overall, this review paper provides insight to researchers on what has been accomplished so far in the field of methanol reforming for fuel cell power generation applications to better plan the next stage of studies in this field.

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)0.002
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 score0.018
Threshold uncertainty score0.288

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 science0.0010.000
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 head0.096
GPT teacher head0.430
Teacher spread0.334 · 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