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Record W4387121591 · doi:10.1002/aesr.202300148

Revisiting the Roles of Carbon in the Catalysis of Lithium–Sulfur Batteries

2023· article· en· W4387121591 on OpenAlex
Zhonghao Hu, Chuannan Geng, Li Wang, Wei Lv, Quan‐Hong Yang

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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueAdvanced Energy and Sustainability Research · 2023
Typearticle
Languageen
FieldEngineering
TopicAdvanced Battery Materials and Technologies
Canadian institutionsnot available
FundersBasic and Applied Basic Research Foundation of Guangdong ProvinceNational Key Research and Development Program of ChinaFundamental Research Funds for the Central UniversitiesGLABAT Solid-State BatteryShenzhen Fundamental Research ProgramNational Natural Science Foundation of China
KeywordsHeteroatomCarbon fibersCatalysisSulfurLithium (medication)DissolutionMaterials scienceElectrolyteNanotechnologyChemistryChemical engineeringInorganic chemistryElectrodeOrganic chemistryPhysical chemistry

Abstract

fetched live from OpenAlex

Carbon materials are the key hosts for the sulfur cathode to improve the conductivity and confine the lithium polysulfides (LiPSs) in lithium–sulfur batteries (LSBs), owing to their high electronic conductivity and strong confinement effect. However, physical or chemical trapping methods have limitations in preventing the dissolution and accumulation of LiPSs in the electrolyte. Catalysis has emerged as a fundamental solution to accelerate the sluggish redox kinetics, and carbon materials acting as catalyst supports or direct catalysts significantly impact the reaction efficiency. Herein, the roles of carbon in the catalysis of LSBs are systematically discussed, focusing on the influence of surface area, pore structure, and surface chemistry on sulfur conversion. Then, two modification strategies, vacancy defects and heteroatom doping, that endow carbon with catalytic activity are summarized. Finally, the remaining challenges and solutions are outlined in terms of the preparation and characterization of the functional carbon in LSBs. This perspective provides essential insights and guidance for the rational design of carbon‐based catalysts in LSBs.

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)0.001
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.594
Threshold uncertainty score0.235

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 head0.016
GPT teacher head0.294
Teacher spread0.278 · 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