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Record W4401976693 · doi:10.1021/acsenergylett.4c01417

Electrochemical Hydrogenation of a Liquid Organic Hydrogen Carrier Using a Pd Membrane Reactor

2024· article· en· W4401976693 on OpenAlexafffund
Mia D. Stankovic, Natalie E. LeSage, Jessica F. Sperryn, Aiko Kurimoto, Curtis P. Berlinguette

Bibliographic record

VenueACS Energy Letters · 2024
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsCanadian Institute for Advanced ResearchUniversity of British Columbia
FundersStewart Blusson Quantum Matter Institute, University of British ColumbiaUniversity of British Columbia Graduate SchoolNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsCanada First Research Excellence FundCanada Foundation for InnovationUniversity of British ColumbiaCanadian Institute for Advanced Research
KeywordsElectrochemistryHydrogenMembraneMembrane reactorMaterials scienceChemical engineeringHydrogen productionChemistryInorganic chemistryElectrodeOrganic chemistryPhysical chemistryEngineering

Abstract

fetched live from OpenAlex

Liquid organic hydrogen carriers (LOHCs) store hydrogen in the chemical bonds of organic molecules. Unsaturated molecules, like toluene, can store hydrogen at densities comparable to compressed gas, but have the distinct advantage of being transportable as liquids under ambient conditions. Thermochemical hydrogenation using H 2(g) requires high temperatures and pressures, whereas electrochemical hydrogenation can proceed at ambient conditions and without H 2(g) . However, the electrochemical hydrogenation of toluene is limited by the low solubility of toluene (<6 mM) in water. Here, we demonstrate the hydrogenation of neat liquid toluene electrochemically by using a palladium membrane reactor. We show that this reactor prevents toluene permeation to the anode chamber, which is a persistent issue for other forms of electrochemical hydrogenation. This paper outlines how the membrane reactor also overcomes many other issues associated with electrochemical hydrogenation, thereby enabling the hydrogenation of LOHCs without H 2(g) .

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 score0.005

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 communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.007
GPT teacher head0.210
Teacher spread0.203 · 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

Citations13
Published2024
Admission routes2
Has abstractyes

Explore more

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