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Record W2801325151 · doi:10.1002/smtd.201700341

Synchrotron‐Based X‐ray Absorption Fine Structures, X‐ray Diffraction, and X‐ray Microscopy Techniques Applied in the Study of Lithium Secondary Batteries

2018· article· en· W2801325151 on OpenAlexafffund
Weihan Li, Minsi Li, Yongfeng Hu, Jun Lü, Andrew Lushington, Ruying Li, Tianpin Wu, Tsun‐Kong Sham, Xueliang Sun

Bibliographic record

VenueSmall Methods · 2018
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsCanadian Light Source (Canada)Western University
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsUniversity of SaskatchewanCanadian Light SourceNational Research Council CanadaWestern UniversityCanada Foundation for InnovationOntario Research FoundationU.S. Department of Energy
KeywordsSynchrotronCharacterization (materials science)Context (archaeology)Synchrotron radiationLithium (medication)Materials scienceNanotechnologyAbsorption (acoustics)Engineering physicsOpticsPhysics

Abstract

fetched live from OpenAlex

Abstract Owing to the recent advance of third‐generation synchrotron radiation (SR) sources, SR‐based X‐ray techniques have been widely applied to study lithium‐ion batteries, lithium–sulfur batteries, and lithium–oxygen batteries to solve material challenges. SR‐based techniques provide high chemical and physical sensitivity and a comprehensive picture of material structure and reaction mechanisms. An in‐depth understanding of batteries is imperative for the development of future energy storage devices with enhanced electrochemical performance to meet societies' growing need for devices with high energy density. Here, recent progress in the application of SR techniques for lithium secondary batteries with a focus on several techniques, including X‐ray absorption fine structure, synchrotron X‐ray diffraction, and synchrotron X‐ray microscopy techniques is reviewed. The working principle for all characterization techniques is introduced to provide context for how the technique is used in the field of energy storage. Through discussing the utilization of SR techniques in different directions of batteries, including electrodes, electrolytes, and interfaces, the practical application strategies of techniques in batteries are clarified. By summarizing and discussing the application of SR techniques in batteries, the aim is to highlight the crucial role of SR characterization in the development of advanced energy materials.

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)0.001
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: none
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.021
GPT teacher head0.326
Teacher spread0.305 · 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

Citations81
Published2018
Admission routes2
Has abstractyes

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