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Petaloid-shaped hierarchical porous carbon sub-microspheres derived from lignin for high-performance supercapacitor electrodes

2025· article· en· W4414045278 on OpenAlexafffund
Lei Tong, Xiaoqian Gai, Huijie Wang, Ming Yan, Runxian Wang, Farzad Seidi, Huining Xiao, Chao Liu

Bibliographic record

VenueJournal of Power Sources · 2025
Typearticle
Languageen
FieldMaterials Science
TopicSupercapacitor Materials and Fabrication
Canadian institutionsUniversity of New Brunswick
FundersState Key Laboratory of Pulp and Paper EngineeringNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of ChinaNanjing Forestry University
KeywordsSupercapacitorCarbonizationSpecific surface areaCapacitancePorosityElectrolyteCarbon fibersLignin

Abstract

fetched live from OpenAlex

In this study, alkali lignin (AL), a byproduct of the sulfate pulping process, is utilized as a precursor to synthesize hierarchical porous carbon sub-microspheres (HALCS) with high specific surface area through high shear homogenization and chemically activated carbonization. The implementation of high-speed mechanical shear effectively reduces the particle size of lignin, leading to the formation of sub-microparticles. HALCS with distinct grooves and petal-like structures are obtained through a chemical activation-assisted high-temperature carbonization process. HALCS exhibits a hierarchical pore structure comprising macropores, mesopores, and micropores, with a specific surface area reaching 898.8 m 2 /g and a pore volume of 0.634 cm 3 /g, significantly surpassing alkali lignin-derived carbon (ALC) produced under similar carbonization conditions. In the 1 M H 2 SO 4 electrolyte environment, HALCS exhibits a specific capacitance of 433 F/g at a current density of 0.8 A/g. Moreover, a symmetric supercapacitor based on HALCS achieves maximum energy density and corresponding power density values of 17.2 Wh/kg and 100 W/kg, respectively, while maintaining excellent cycling stability undergoing 5000 charge-discharge cycles. Consequently, this straightforward and environmentally friendly synthesis strategy for alkali lignin-derived hierarchical porous carbon sub-microspheres opens up new avenues for the utilization of carbon materials derived from biomass in high-performance energy storage devices.

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 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 score0.026
Threshold uncertainty score0.771

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)0.0000.000

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 head0.007
GPT teacher head0.220
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

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

Citations5
Published2025
Admission routes2
Has abstractyes

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