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Structure & composition of carbon fibers for electrochemical applications

2025· article· en· W4410359817 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

VenueJournal of Power Sources · 2025
Typearticle
Languageen
FieldEngineering
TopicFiber-reinforced polymer composites
Canadian institutionsUniversity of Toronto
FundersUniversität UlmDeutsche ForschungsgemeinschaftFonds der Chemischen IndustrieExzellenzcluster Ozean der ZukunftVerband der Chemischen Industrie
KeywordsElectrochemistryComposition (language)Carbon fibersMaterials scienceChemistryChemical engineeringElectrodeComposite materialComposite numberEngineeringPhysical chemistry

Abstract

fetched live from OpenAlex

Carbon-based electrode materials are used in a broad range of energy storage systems and influence their performance significantly. Electrode materials must be investigated to optimize the technologies' efficiency. This study examines lab-fabricated and commercial electrode materials for vanadium redox flow batteries (VRFBs), and the influence of thermal treatment on these materials. Scanning electron microscopy images and X-ray nano-computed tomography revealed significant differences between the 3D shapes of the carbon fibers, which are influenced by the choice of precursor material and manufacturing process. Both have a crucial influence on the inner structure of the fibers, such as holes, which lower the mechanical stability. Furthermore, the composition of the fibers was assessed using wide-angle X-ray scattering and X-ray photoelectron spectroscopy highlighting especially differences in the fibers' oxygen- and carbon content. The applied thermal treatment increased the O-content and thus enhanced the material's wettability, which was investigated with dynamic vapor sorption. No structural changes in the fiber shape were monitored after thermal treatment. The materials' electrochemical performance was studied for VRFBs. The study of different electrode materials here shows the importance of choosing a suitable precursor and manufacturing process and the need for a multimodal characterization of materials to identify potential candidates.

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 score0.053
Threshold uncertainty score0.374

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 integrity0.0000.000
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 head0.003
GPT teacher head0.216
Teacher spread0.213 · 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