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Record W4414577351 · doi:10.1021/acsenergylett.5c01924

Controlled Energy Offloading via Self-Destructing Agents for Safer Li-Ion Batteries

2025· article· en· W4414577351 on OpenAlexaff
Bowen Hou, Yong Peng, Liqi Zhao, Zheng Meng, Xinyu Rui, Zhenwei Wei, Junxian Hou, Xuning Feng, Li Wang, Minggao Ouyang, Xiangming He

Bibliographic record

VenueACS Energy Letters · 2025
Typearticle
Languageen
FieldEngineering
TopicAdvanced Battery Technologies Research
Canadian institutionsNexen (Canada)
FundersNational Key Research and Development Program of ChinaBeijing Municipal Natural Science FoundationNational Natural Science Foundation of China
KeywordsThermal runawaySAFERBridging (networking)Energy densityBattery (electricity)ThermalLithium (medication)Reduction (mathematics)

Abstract

fetched live from OpenAlex

Addressing the critical safety challenge of thermal runaway in lithium-ion batteries, we introduce a self-destruction strategy incorporating spatiotemporal electron capture agents. In LiNi 0.8 Co 0.1 Mn 0.1 O 2 batteries, 7 of 14 tested agents, notably phloroglucinol, effectively modulated thermal runaway pathways, reducing heat release by up to 65% and reducing the peak temperature of 176.1 °C. Phloroglucinol demonstrated particularly positive performance (70% enthalpy reduction and 72% peak temperature-rise rate reduction). Conversely, lithium iron phosphate batteries required alternative approaches as thermal output increased. By correlating agent properties like water-binding energy and phenyl reactivity with performance, we provide actionable guidelines for designing safer battery chemistries, bridging fundamental research with practical applications to mitigate the safety-energy density dilemma.

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)0.000
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: none
Teacher disagreement score0.805
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.009
GPT teacher head0.240
Teacher spread0.231 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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