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Optimation PAN/TiO2 Nanofiber Membrane as Separator for Symmetric Supercapacitor

2025· article· en· W4414486056 on OpenAlexaff
Nasikhudin Nasikhudin, Markus Diantoro, Chusnana Insjaf Yogihati, Risa Suryana, Yatimah Alias

Bibliographic record

VenueJournal of Engineering and Technological Sciences · 2025
Typearticle
Languageen
FieldMaterials Science
TopicSupercapacitor Materials and Fabrication
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsThermogravimetric analysisSeparator (oil production)SupercapacitorCyclic voltammetryElectrolyteMembraneScanning electron microscopeElectrospinning

Abstract

fetched live from OpenAlex

Supercapacitor is one of the energy storage systems known for their high-power density, long cycle life, and good cycling stability. To improve supercapacitor performance, we used a polymer PAN composite titanium dioxide (TiO2) as the separator material. Nanofiber separator membranes of PAN/TiO₂ with various masses (0, 5, 10, 15, and 20 wt%) were successfully synthesized using the electrospinning technique. The addition of TiO2 for modified fiber, due to its high absorption rate for energy storage, increased electrolyte uptake and optimized supercapacitor performance. The morphology, functional groups, crystallinity, and thermal stability of the membranes were identified using scanning electron microscope (SEM), Fourier transform infra-red (FTIR), x-ray diffraction (XRD), and thermogravimetric analysis (TGA), respectively. It was found that the membrane with 15 wt% TiO2 exhibited a fiber diameter of 224.73 nm, pore size of 138.98 nm, the highest porosity of 66.50%, electrolyte uptake of 240%, and thermal stability up to 282°C, with a remaining mass of 3.94% after being tested at 1000°C. The electrochemical performance of the supercapacitors was measured using galvanostatic charge-discharge (GCD), cyclic voltammetry (CV), and electrochemical impedance spectroscopy (EIS). The membrane containing 15 wt% TiO2 demonstrated optimum ionic conductivity of 4.4 x 10-4 S/cm, gravimetric capacitance of 57.770 F. g-1, and capacitance retention of 94.22% after 1000 test cycles.

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 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)0.001
metaresearch head score (Gemma)0.001
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 score0.025
Threshold uncertainty score0.258

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.014
GPT teacher head0.256
Teacher spread0.241 · 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 teacher head, 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

Citations0
Published2025
Admission routes1
Has abstractyes

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