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Record W4411414149 · doi:10.1021/acsami.5c07304

High-Voltage Lithium Batteries Enabled by Facile In Situ Fabrication of Monophasic Cellulose-Based Single-Ion Conductors

2025· article· en· W4411414149 on OpenAlexaff
Seonghan Yu, Hyeyun Kim, Jaeho Shin, Junsu Kim, Won Il Kim, Hyungyu Cho, Chun‐Jae Yoo, Wooseok Yang, Hyesung Cho, Kwang Ho Kim, Ho Seok Park, Kahyun Hur

Bibliographic record

VenueACS Applied Materials & Interfaces · 2025
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsUniversity of British Columbia
FundersKorea Forest ServiceNational Research Foundation of KoreaKorea Institute of Science and Technology
KeywordsMaterials scienceElectrolyteSeparator (oil production)Chemical engineeringIonic conductivitySulfonateNanotechnologyElectrodeSodium

Abstract

fetched live from OpenAlex

The growing demand for high-energy-density, safe, and sustainable lithium-ion batteries (LIBs) necessitates the development of innovative electrolytes. Herein, we present a facile in situ preparation strategy for fabricating a high-performance single-ion conductor (SC). This SC is based on hydroxypropyl cellulose (HPC) integrated with polyethylene glycol diacrylate cross-linker, in combination with sodium styrene sulfonate (NaSS) as a functional monomer. The introduction of NaSS is crucial, as it introduces sulfonate groups that are immobilized within the polymer network, enabling selective lithium-ion transport. This approach offers a significant advancement over conventional polyether-based gel polymer electrolytes (GPEs), which usually suffer from limited oxidative stability and require the use of separators, particularly in high-voltage battery applications. The in situ polymerization method presented here eliminates the need for a separator and offers several key advantages: rapid processability, excellent scalability, and the formation of a stable solid electrolyte interface. The result is a robust, separator-free GPE. Our HPC-based single-ion conductor (MHPC SC) exhibits a high lithium transference number of 0.89 and an ionic conductivity of 2.4 mS cm –1 at room temperature. These properties are attributed to efficient lithium-ion transport through its synergistic effect of the polyanionic conductor and HPC matrix. The mechanically robust and highly conformal polymer network effectively suppresses detrimental interfacial reactions and mitigates dendrite growth, resulting in an enhanced cycling stability. Notably, the MHPC SC enables stable operation with high-voltage cathodes up to 4.3 V, achieving 94% capacity retention over 100 cycles. These findings highlight the potential of cellulose-based GPEs as a sustainable and high-performance electrolyte that significantly enhances both the safety and performance of advanced LIBs.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.010
GPT teacher head0.221
Teacher spread0.211 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2025
Admission routes1
Has abstractyes

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