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Record W4401634802 · doi:10.3390/ma17164079

Enhanced Supercapacitor and Cycle-Life Performance: Self-Supported Nanohybrid Electrodes of Hydrothermally Grown MnO2 Nanorods on Carbon Nanotubes in Neutral Electrolyte

2024· article· en· W4401634802 on OpenAlexafffund
Soraya Bouachma, Xiaoying Zheng, Alonso Moreno Zuria, M. Kechouane, N. Gabouze, Mohamed Mohamedi

Bibliographic record

VenueMaterials · 2024
Typearticle
Languageen
FieldMaterials Science
TopicSupercapacitor Materials and Fabrication
Canadian institutionsInstitut National de la Recherche Scientifique
FundersNatural Sciences and Engineering Research Council of CanadaCentre québécois sur les matériaux fonctionnels
KeywordsSupercapacitorNanorodCarbon nanotubeElectrolyteMaterials scienceNanotechnologyElectrodeChemical engineeringElectrochemistryChemistry

Abstract

fetched live from OpenAlex

Efficient and sustainable energy storage remains a critical challenge in the advancement of energy technologies. This study presents the fabrication and electrochemical evaluation of a self-supporting electrode material composed of MnO2 nanorods grown directly on a carbon paper and carbon nanotube (CNT) substrate using a hydrothermal method. The resulting CNT/MnO2 electrodes exhibit a unique structural architecture with a high surface area and a three-dimensional hierarchical arrangement, contributing to a substantial electrochemical surface area. Electrochemical testing reveals remarkable performance characteristics, including a specific capacitance of up to 316.5 F/g, which is 11 times greater than that of conventional CP/MnO2 electrodes. Moreover, the CNT/MnO2 electrodes demonstrate outstanding retention capacity, exhibiting a remarkable 165% increase over 10,000 cycles. Symmetric supercapacitor devices utilizing CNT/MnO2 electrodes maintain a large voltage window of 3 V and a specific capacitance as high as 200 F/g. These results underscore the potential of free-standing CNT/MnO2 electrodes to advance the development of high-performance supercapacitors, which can be crucial for efficient and sustainable energy storage solutions in various industrial and manufacturing applications.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.003
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.000

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 head0.216
Teacher spread0.209 · 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.

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

Citations22
Published2024
Admission routes2
Has abstractyes

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